title
Informatica Interview Questions | Informatica Tutorial | Informatica Training | Edureka

description
( Informatica Tutorial - https://www.edureka.co/informatica-certification-training ) This Edureka Informatica training will help you to prepare yourself for Informatica Interviews ( Informatica Interview Questions Blog: https://goo.gl/z4jVff ). Learn about the most important Informatica interview questions and answers and know what will set you apart in the interview process. Below are the topics covered in this Informatica Interview Questions and Answers Tutorial: Informatica Interview Questions on: 1. Generic Informatica Interview Questions. 2. Informatica Transformation Questions. 3. Informatica Lookup Questions. 4. Informatica Scenario Based questions. 5. Informatica Workflow Questions. 6. Informatica Administrator Questions Check our Informatica playlist here https://goo.gl/TmX6Fv. Other Related Blog Post: https://goo.gl/tq8qBu https://goo.gl/ey7YMC https://goo.gl/bUFckp https://goo.gl/c6ttKu Subscribe to our channel to get video updates. Hit the subscribe button above. #Informatica #Informaticatutorial #Informaticapowercenter #Informaticaonlinetraining How it Works? 1. This is a 6 Week Instructor led Online Course, 25 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Informatica PowerCenter Certification training is designed to help you become a top Informatica Developer and Administrator. During this course, our expert Informatica instructors will help you: 1. Understand and identify different Informatica Products 2. Describe Informatica PowerCenter architecture & its different components 3. Use PowerCenter 9.x components to build Mappings, Tasks, Workflows 4. Describe the basic and advanced features functionalities of PowerCenter 9.X transformations 5. Understand Workflow Task and job handling 6. Describe Mapping Parameter and Variables 7. Perform debugging, troubleshooting, error handling and recovery 8. Learn to calculate cache requirement and implement session cache 9. Execute performance tuning and Optimisation 10. Recognise and explain the functionalities of the Repository Manager tool. 11. Identify how to handle services in the Administration Console 12. Understand techniques of SCD, XML Processing, Partitioning, Constraint based loading and Incremental Aggregation 13. Gain insight on ETL best practices using Informatica - - - - - - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course : 1. Software Developers 2. Analytics Professionals 3. BI/ETL/DW Professionals 4. Mainframe developers and Architects 5. Individual Contributors in the field of Enterprise Business Intelligence - - - - - - - - - - - - - - - - Why learn Informatica? Informatica provides the market's leading data integration platform. Tested on nearly 500,000 combinations of platforms and applications, the data integration platform interoperates with the broadest possible range of disparate standards, systems, and applications. This unbiased and universal view makes Informatica unique in today's market as a leader in the data integration platform. It also makes Informatica the ideal strategic platform for companies looking to solve data integration issues of any size. The topics related to Informatica have extensively been covered in our course 'Informatica PowerCenter 9.X Developer & Admin’. For more information, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka

detail
{'title': 'Informatica Interview Questions | Informatica Tutorial | Informatica Training | Edureka', 'heatmap': [{'end': 5050.368, 'start': 4941.808, 'weight': 0.773}, {'end': 7523.577, 'start': 7418.225, 'weight': 1}], 'summary': 'Introduces informatica, highlighting its dominance in the etl market with 70% market share and expected revenue growth from $1.06 billion in 2015 to $10 billion in 2021. it covers job trends, data warehousing schemas, workflow partitioning, optimization methods, transformations, joins, reusable transformations, lookup, job performance optimization, workflow, and data integration.', 'chapters': [{'end': 412.476, 'segs': [{'end': 275.467, 'src': 'embed', 'start': 248.62, 'weight': 0, 'content': [{'end': 252.123, 'text': 'And the second leading will be your data stage,', 'start': 248.62, 'duration': 3.503}, {'end': 261.362, 'text': "because that's an IBM product and they are providing a number of things also within data stage with data stage, because IBM's policy is just like.", 'start': 252.123, 'duration': 9.239}, {'end': 269.405, 'text': 'they provide a complete suite of the tools, like they will be providing your ETL, they will be providing your database, your reporting on Cognos,', 'start': 261.362, 'duration': 8.043}, {'end': 273.186, 'text': 'then your MDM metadata management, as well as master data management also.', 'start': 269.405, 'duration': 3.781}, {'end': 275.467, 'text': 'So people take that also.', 'start': 273.707, 'duration': 1.76}], 'summary': "Ibm's datastage offers a suite of tools including etl, database, reporting, mdm, and master data management.", 'duration': 26.847, 'max_score': 248.62, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI248620.jpg'}], 'start': 0.509, 'title': 'Informatica and etl market', 'summary': 'Introduces an informatica session with abhishek and team, and also discusses the dominance of informatica in the etl tools market, capturing 70% of the market share with expected revenue growth from $1.06 billion in 2015 to $10 billion in 2021, partnering with over 550 organizations and serving over 12,000 customers in 104 countries.', 'chapters': [{'end': 183.542, 'start': 0.509, 'title': 'Informatica intro session', 'summary': 'Introduces an informatica session with 10+ years experienced data architect abhishek leading a discussion with three team members about their experience, expectations, and questions regarding informatica training and interviews.', 'duration': 183.033, 'highlights': ["Abhishek, a 10-plus years experienced data architect, leads the Informatica session and discusses the current IT industry's expectations for Informatica developers. Abhishek has 10-plus years of industry experience and works as a data architect in an MNC, leading the discussion on the current IT industry's expectations for Informatica developers.", 'The team members, including Vishal, Lakshmi, Ishwari, Seelam, and Bindu, express their desire for Informatica training, interview preparation, and career advancement. The team members express their interest in Informatica training, interview preparation, and career advancement.', 'The team members share their experiences and expectations regarding Informatica training and interviews, seeking clarification on scenario-based questions and real-time environment. The team members share their experiences and expectations, seeking clarification on scenario-based questions and real-time environment in Informatica training and interviews.']}, {'end': 412.476, 'start': 183.942, 'title': 'Etl tools market overview', 'summary': 'Discusses the dominance of informatica and ibm data stage in the etl tools market, with informatica capturing 70% of the market share and expecting a revenue growth from 1.06 billion in 2015 to $10 billion in 2021, partnering with over 550 organizations and catering to over 12,000 customers in 104 countries.', 'duration': 228.534, 'highlights': ["Informatica's revenue is expected to grow from 1.06 billion in 2015 to $10 billion in 2021. Informatica is projected to experience a significant revenue growth from 1.06 billion in 2015 to $10 billion in 2021, indicating a substantial increase in market dominance.", 'Informatica holds 70% of the ETL tools market share. Informatica is the leading ETL tool, capturing 70% of the total market share, indicating its strong dominance in the industry.', 'Informatica is partnered with over 550 organizations and caters to over 12,000 customers in 104 countries. Informatica has established partnerships with more than 550 organizations and serves over 12,000 customers across 104 countries, signifying its widespread global presence and influence.']}], 'duration': 411.967, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI509.jpg', 'highlights': ['Informatica holds 70% of the ETL tools market share.', "Informatica's revenue is expected to grow from 1.06 billion in 2015 to $10 billion in 2021.", "Abhishek, a 10-plus years experienced data architect, leads the Informatica session and discusses the current IT industry's expectations for Informatica developers.", 'The team members, including Vishal, Lakshmi, Ishwari, Seelam, and Bindu, express their desire for Informatica training, interview preparation, and career advancement.', 'Informatica is partnered with over 550 organizations and caters to over 12,000 customers in 104 countries.']}, {'end': 2010.28, 'segs': [{'end': 458.321, 'src': 'embed', 'start': 431.458, 'weight': 5, 'content': [{'end': 435.581, 'text': "So I think I'm audible to everyone and Silam is also saying that yes, now it's good.", 'start': 431.458, 'duration': 4.123}, {'end': 436.482, 'text': 'Okay, perfect.', 'start': 435.801, 'duration': 0.681}, {'end': 437.983, 'text': "All right, so let's move ahead.", 'start': 436.882, 'duration': 1.101}, {'end': 440.765, 'text': 'Overall, if you see, we were talking about the job trends.', 'start': 438.283, 'duration': 2.482}, {'end': 442.867, 'text': "That's a major key factor.", 'start': 441.446, 'duration': 1.421}, {'end': 450.636, 'text': 'If I talk about myself also, then I want to grow myself in such an industry that is going to have lots of job opportunity.', 'start': 442.927, 'duration': 7.709}, {'end': 458.321, 'text': "I just put in the technology name and see that how much or how frequently the jobs that are coming into the today's in that portal.", 'start': 450.936, 'duration': 7.385}], 'summary': 'Discussion on job trends and industry growth for job opportunities.', 'duration': 26.863, 'max_score': 431.458, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI431458.jpg'}, {'end': 900.83, 'src': 'embed', 'start': 876.508, 'weight': 2, 'content': [{'end': 883.414, 'text': 'Like if you take particular domains, like for customer, if you have multiple domains in the data warehouse, like customer.', 'start': 876.508, 'duration': 6.906}, {'end': 884.415, 'text': 'I got it.', 'start': 883.434, 'duration': 0.981}, {'end': 885.416, 'text': 'I got it.', 'start': 884.595, 'duration': 0.821}, {'end': 887.278, 'text': 'Okay Let me elaborate.', 'start': 885.776, 'duration': 1.502}, {'end': 888.539, 'text': 'Customer as a data model.', 'start': 887.478, 'duration': 1.061}, {'end': 891.381, 'text': 'Only customer-related data, you can take it as a data model.', 'start': 888.579, 'duration': 2.802}, {'end': 893.183, 'text': 'You only have particular thing.', 'start': 891.842, 'duration': 1.341}, {'end': 894.064, 'text': 'Perfect, Lakshmi.', 'start': 893.463, 'duration': 0.601}, {'end': 895.625, 'text': "So that's correct.", 'start': 894.504, 'duration': 1.121}, {'end': 900.83, 'text': 'The answer that Lakshmi provided is absolutely correct, that data models are the subset of a data warehouse.', 'start': 895.805, 'duration': 5.025}], 'summary': 'Data models are subsets of a data warehouse, e.g. customer-related data model.', 'duration': 24.322, 'max_score': 876.508, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI876508.jpg'}, {'end': 1454.557, 'src': 'embed', 'start': 1432.522, 'weight': 1, 'content': [{'end': 1440.945, 'text': "So that's the grid concept that we have as we have multiple nodes in the domain So they come into the picture and we can distribute the tasks.", 'start': 1432.522, 'duration': 8.423}, {'end': 1442.967, 'text': "That's a grid processing, basically.", 'start': 1441.326, 'duration': 1.641}, {'end': 1447.531, 'text': "And the benefits, it's already mentioned here, right? Jent is raising his hand and Silam.", 'start': 1443.167, 'duration': 4.364}, {'end': 1449.052, 'text': 'Okay, Silam is raising his hand.', 'start': 1447.811, 'duration': 1.241}, {'end': 1450.814, 'text': 'Okay Yes, Silam, please go ahead.', 'start': 1449.252, 'duration': 1.562}, {'end': 1452.395, 'text': "Yes, Silam, I've just unmuted you.", 'start': 1451.254, 'duration': 1.141}, {'end': 1454.557, 'text': 'Yes, Silam, you can speak up now.', 'start': 1452.955, 'duration': 1.602}], 'summary': 'Grid concept for distributing tasks among multiple nodes in the domain.', 'duration': 22.035, 'max_score': 1432.522, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI1432522.jpg'}, {'end': 1554.015, 'src': 'embed', 'start': 1520.938, 'weight': 3, 'content': [{'end': 1526.723, 'text': 'So, with the help of integration service and grid processing, we are doing this thing at the background side.', 'start': 1520.938, 'duration': 5.785}, {'end': 1527.443, 'text': 'You got me?', 'start': 1527.043, 'duration': 0.4}, {'end': 1533.128, 'text': 'Okay, so there will be one integration process that does this job?', 'start': 1528.084, 'duration': 5.044}, {'end': 1536.39, 'text': "There will be integration service that's been created while the installation.", 'start': 1533.148, 'duration': 3.242}, {'end': 1540.954, 'text': 'if you remember, when you was doing the installation, there was the integration service that you created.', 'start': 1536.39, 'duration': 4.564}, {'end': 1542.855, 'text': 'So that comes into the picture over here.', 'start': 1541.314, 'duration': 1.541}, {'end': 1554.015, 'text': "Okay, the other question is, Abhishek, using this power grid processing, let's suppose we have a workflow which is running 20 different sessions.", 'start': 1543.015, 'duration': 11}], 'summary': 'Integration service and grid processing are utilized for background tasks. a single integration process is created during installation.', 'duration': 33.077, 'max_score': 1520.938, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI1520938.jpg'}, {'end': 1943.243, 'src': 'embed', 'start': 1919.975, 'weight': 0, 'content': [{'end': 1927.458, 'text': 'So overall, the main motor of discussing this point is that we can easily partition a particular workflow, we can partition a particular job.', 'start': 1919.975, 'duration': 7.483}, {'end': 1931.498, 'text': 'It will break it into small chunks, execute it in parallel.', 'start': 1928.597, 'duration': 2.901}, {'end': 1934.6, 'text': 'That will definitely enhance the performance.', 'start': 1931.558, 'duration': 3.042}, {'end': 1943.243, 'text': 'But with this, if you want to go ahead and get more optimized, or rather if you want to execute a job in a more faster manner,', 'start': 1934.92, 'duration': 8.323}], 'summary': 'Partitioning workflow enhances performance by executing in parallel.', 'duration': 23.268, 'max_score': 1919.975, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI1919975.jpg'}], 'start': 412.796, 'title': 'Informatica job trends and data warehousing schemas', 'summary': 'Discusses informatica job trends including job postings, average salary, and interview questions, and highlights the differences between star and snowflake schemas with emphasis on maintenance, queries, and suitability for data warehousing core.', 'chapters': [{'end': 584.869, 'start': 412.796, 'title': 'Informatica job trends and interview questions', 'summary': 'Discusses the job trends in informatica with a focus on job postings, average salary, and the requirement for informatica developers, and also covers the agenda for the session which includes interview questions, transformation-related questions, lookup concepts, and scenario-based questions.', 'duration': 172.073, 'highlights': ["Informatica has average salary of jobs, the highest being 21500, with a high demand for Informatica developers in today's IT industry. The average salary for Informatica jobs is 21500, indicating high earning potential, and there is a high demand for Informatica developers in the IT industry.", 'The session agenda covers interview questions, transformation related questions, lookup concepts, and scenario-based questions, providing a comprehensive understanding of the Informatica environment. The session agenda includes a variety of interview questions, which cover data warehousing concepts, data integration concepts, different types of transformations, lookup concepts, and scenario-based questions, providing a comprehensive understanding of the Informatica environment.', 'The requirement for Informatica developers is the highest compared to architects, administrators, consultants, specialists, analysts, leads, and project managers, indicating a strong need for Informatica developers in the industry. There is a strong need for Informatica developers as the requirement for them is the highest compared to other roles such as architects, administrators, consultants, specialists, analysts, leads, and project managers.']}, {'end': 1181.548, 'start': 585.447, 'title': 'Data warehouse schema differences: star vs snowflake', 'summary': 'Discusses the differences between star and snowflake schemas, emphasizing that a star schema has redundant data, leading to easier maintenance, simpler queries, and shorter execution times, while a snowflake schema has more complex queries due to its dependency and is suitable for data warehousing core to simplify complex relationships.', 'duration': 596.101, 'highlights': ['A star schema has redundant data, leading to easier maintenance, simpler queries, and shorter execution times, while a snowflake schema has more complex queries due to its dependency. In a star schema, redundant data leads to easier maintenance, simpler queries, and shorter execution times, while a snowflake schema has more complex queries due to its dependency.', 'The snowflake schema is suitable for data warehousing core to simplify complex relationships. Snowflake schema is suitable for data warehousing core to simplify complex relationships, while a star schema is always good for a data mart.', 'In real-time environments, the choice between star and snowflake schemas depends on the project, with an equal proportion of usage observed. In real-time environments, the choice between star and snowflake schemas depends on the project, with an equal proportion of usage observed.', 'A bottom-up approach is used for snowflake schema, while a top-down approach is employed for a star schema. A bottom-up approach is used for snowflake schema, while a top-down approach is employed for a star schema.']}, {'end': 1699.247, 'start': 1181.609, 'title': 'Informatica power center grid processing', 'summary': 'Discusses informatica power center grid processing, which enables workflows and sessions to run across multiple domain nodes, providing benefits such as load balancing, high availability, and dynamic partitions. the key features include the distribution of tasks, communication between nodes, and the role of the integration service in increasing performance and scalability.', 'duration': 517.638, 'highlights': ['Informatica Power Center grid processing enables workflows and sessions to run across multiple domain nodes, providing benefits such as load balancing, high availability, and dynamic partitions. The grid processing feature of Power Center allows workflows and sessions to run across multiple domain nodes, aiding in load balancing, high availability, and dynamic partitions.', 'The integration service plays an important role in increasing performance and scalability by running service processes on each available node of the grid. The integration service enhances performance and scalability by running service processes on every available node of the grid, contributing to increased performance and scalability.', 'The configuration of workflows to run on specific grids and the distribution of session threads to multiple DTM processes on different nodes contribute to performance and scalability. Configuring workflows to run on specific grids and distributing session threads to multiple DTM processes on different nodes aid in performance and scalability.', 'Enabling the grid processing option can cause performance issues, especially when the same workflow switches between different nodes, leading to delays and lags. Enabling the grid processing option may cause performance issues, particularly when the same workflow switches between different nodes, resulting in delays and lags.']}, {'end': 2010.28, 'start': 1699.807, 'title': 'Understanding grid processing and partitioning', 'summary': "Highlights the importance of understanding grid processing in developer interviews, discusses the benefits and challenges of partitioning for performance enhancement, and explains the concept of partitioning for parallel data processing with an example of optimizing a job's performance.", 'duration': 310.473, 'highlights': ["The importance of understanding grid processing in developer interviews It's crucial for developers to be aware of grid processing in interviews, but the specific type used in past projects is not typically cross-checked.", 'Benefits and challenges of partitioning for performance enhancement Partitioning a session can lead to parallel data processing, increasing performance, and reducing load time, with additional optimization methods such as index management for further enhancement.', "Explanation of partitioning for parallel data processing with an optimization example Partitioning a workflow or job can break it into smaller chunks for parallel execution, as demonstrated by an example of optimizing a job's performance through partitioning and other optimization methods."]}], 'duration': 1597.484, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI412796.jpg', 'highlights': ['Informatica jobs have an average salary of 21500, indicating high earning potential and a strong demand for developers.', 'The session agenda covers a variety of interview questions, providing a comprehensive understanding of the Informatica environment.', 'Snowflake schema is suitable for data warehousing core to simplify complex relationships, while a star schema is always good for a data mart.', 'The grid processing feature of Power Center allows workflows and sessions to run across multiple domain nodes, aiding in load balancing, high availability, and dynamic partitions.', 'The integration service enhances performance and scalability by running service processes on every available node of the grid.', 'Partitioning a session can lead to parallel data processing, increasing performance and reducing load time, with additional optimization methods such as index management for further enhancement.']}, {'end': 2581.048, 'segs': [{'end': 2065.655, 'src': 'embed', 'start': 2032.191, 'weight': 5, 'content': [{'end': 2034.192, 'text': 'Let me take a highlighter so that I can show it to you.', 'start': 2032.191, 'duration': 2.001}, {'end': 2039.255, 'text': 'Can you see this? This portion on the navigator panel? This is a session properties tab.', 'start': 2034.573, 'duration': 4.682}, {'end': 2044.661, 'text': 'Over here, there are two options, transformation and partitioning.', 'start': 2041.694, 'duration': 2.967}, {'end': 2048.128, 'text': 'Once you go to the partitioning, you can easily go ahead and..', 'start': 2044.961, 'duration': 3.167}, {'end': 2051.004, 'text': 'If you see here, there are two sections.', 'start': 2048.962, 'duration': 2.042}, {'end': 2057.549, 'text': "Once you will go, you will design it in the normal workflow session properties, you'll find this transformation step.", 'start': 2051.384, 'duration': 6.165}, {'end': 2060.19, 'text': 'Once you will go ahead and start doing the partitioning,', 'start': 2057.849, 'duration': 2.341}, {'end': 2065.655, 'text': 'you need to switch on to this partition step and then the complete workflow will appear over here.', 'start': 2060.19, 'duration': 5.465}], 'summary': 'The transcript discusses using session properties for transformation and partitioning in a workflow.', 'duration': 33.464, 'max_score': 2032.191, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2032191.jpg'}, {'end': 2258.333, 'src': 'embed', 'start': 2229.36, 'weight': 2, 'content': [{'end': 2237.344, 'text': 'right. so obviously that would be a enhancement towards the partitioning or the parallel processing right, the second one round robin partitioning, right,', 'start': 2229.36, 'duration': 7.984}, {'end': 2238.204, 'text': "if i'll talk about this.", 'start': 2237.344, 'duration': 0.86}, {'end': 2240.625, 'text': 'this is an algorithm, right.', 'start': 2238.204, 'duration': 2.421}, {'end': 2243.807, 'text': 'so using this algorithm, the, we have the integration service right.', 'start': 2240.625, 'duration': 3.182}, {'end': 2258.333, 'text': 'so the integration service is going to distribute data evenly among all the different partitions that we have created and it uses this algo when we need to distribute rows evenly and do not need to group the data among different partitions.', 'start': 2243.807, 'duration': 14.526}], 'summary': 'Round robin partitioning evenly distributes data among partitions for parallel processing.', 'duration': 28.973, 'max_score': 2229.36, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2229360.jpg'}, {'end': 2382.649, 'src': 'embed', 'start': 2345.955, 'weight': 8, 'content': [{'end': 2350.177, 'text': 'then you have to push your data based on the group by conditions.', 'start': 2345.955, 'duration': 4.222}, {'end': 2358.121, 'text': 'So to push the data to the particular condition or to the particular group, we will be using this hash auto key partitioning.', 'start': 2350.457, 'duration': 7.664}, {'end': 2363.304, 'text': "This hash auto key partitioning, we won't be defining the keys here.", 'start': 2358.541, 'duration': 4.763}, {'end': 2371.301, 'text': 'The integration service itself will determine what key or the column it has to use and then, based on those values,', 'start': 2363.695, 'duration': 7.606}, {'end': 2382.649, 'text': 'this partition will push the values to the group transformations like aggregator sorter, rank joiner and unsorted aggregators.', 'start': 2371.301, 'duration': 11.348}], 'summary': 'Data is pushed using hash auto key partitioning based on group by conditions.', 'duration': 36.694, 'max_score': 2345.955, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2345955.jpg'}, {'end': 2562.093, 'src': 'embed', 'start': 2532.405, 'weight': 0, 'content': [{'end': 2533.185, 'text': 'Just give me a moment.', 'start': 2532.405, 'duration': 0.78}, {'end': 2535.247, 'text': 'In order to go ahead and find out the partitioning.', 'start': 2533.485, 'duration': 1.762}, {'end': 2537.9, 'text': 'You can go to the mapping, then partitions.', 'start': 2535.698, 'duration': 2.202}, {'end': 2540.822, 'text': 'Then once you go to partition, there will be an option.', 'start': 2538.32, 'duration': 2.502}, {'end': 2542.843, 'text': 'We say add and modify partitions.', 'start': 2540.882, 'duration': 1.961}, {'end': 2547.826, 'text': 'Then you can choose any type of transformation and then just click on add partition point over there.', 'start': 2543.023, 'duration': 4.803}, {'end': 2552.81, 'text': 'After that, you can edit a particular partition point or you can create a partition point from there.', 'start': 2548.046, 'duration': 4.764}, {'end': 2556.132, 'text': 'I just gave you a process that you need to go to the mappings and then partition.', 'start': 2552.83, 'duration': 3.302}, {'end': 2559.234, 'text': 'And from there, you can manage your different partitionings.', 'start': 2556.212, 'duration': 3.022}, {'end': 2560.252, 'text': 'Okay All right.', 'start': 2559.611, 'duration': 0.641}, {'end': 2562.093, 'text': 'Harveen is asking that which is the best method.', 'start': 2560.292, 'duration': 1.801}], 'summary': 'Process explained for managing partitioning in mappings and creating partition points.', 'duration': 29.688, 'max_score': 2532.405, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2532405.jpg'}], 'start': 2010.621, 'title': 'Workflow partitioning and parallel processing in informatica', 'summary': 'Explains how developers control workflow partitioning in informatica and the methods to implement parallel processing, highlighting benefits and various types such as database, round robin, hash auto keys, hash user keys, and key range partitioning.', 'chapters': [{'end': 2071.32, 'start': 2010.621, 'title': 'Workflow partitioning by developers', 'summary': 'Explains that partitioning in the workflow is controlled by developers, not administrators, and can be done through the session properties tab, allowing for the creation of different partitions within the job.', 'duration': 60.699, 'highlights': ['Developers control the partitioning in the workflow, not administrators.', 'Partitioning is done through the session properties tab, offering options for transformation and partitioning.', 'The partitioning process allows for the creation of different partitions within the job.']}, {'end': 2581.048, 'start': 2071.56, 'title': 'Implementing parallel processing in informatica', 'summary': 'Explains the different ways to implement parallel processing in informatica, including the benefits of partitioning and the various types such as database, round robin, hash auto keys, hash user keys, and key range partitioning.', 'duration': 509.488, 'highlights': ['The different ways to perform parallel processing in Informatica include database partitioning, round robin partitioning, hash auto keys partitioning, hash user keys partitioning, and key range partitioning. This highlights the key point of the chapter, outlining the different methods of parallel processing in Informatica.', 'Partitioning in Informatica can enhance the performance of Power Center by splitting large datasets into smaller subsets for parallel processing, leading to improved performance. This provides a quantifiable benefit of partitioning in Informatica, stating that it can lead to improved performance.', 'The integration service queries the database for table partition information and reads partition data from the corresponding nodes in database partitioning, which enhances performance by interacting with specific partitions. This explains the specific operation and benefit of database partitioning in Informatica.', 'Round robin partitioning evenly distributes data among different partitions to balance the load and execute data processing in parallel, leading to load balancing and improved performance. This highlights the functionality and benefit of round robin partitioning in Informatica.', 'Hash auto keys partitioning is used to group and push data based on group by conditions without defining the keys, and it is beneficial for group transformations like aggregator, sorter, and joiner. This gives a clear explanation of hash auto keys partitioning and its benefits for group transformations in Informatica.', 'Hash user keys partitioning groups data based on user-defined partitioning keys, allowing the selection of ports defining the partitioning key within the transformation. This highlights the specific operation and benefit of hash user keys partitioning in Informatica.']}], 'duration': 570.427, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2010621.jpg', 'highlights': ['Developers control the partitioning in the workflow, not administrators.', 'The different ways to perform parallel processing in Informatica include database partitioning, round robin partitioning, hash auto keys partitioning, hash user keys partitioning, and key range partitioning.', 'Partitioning in Informatica can enhance the performance of Power Center by splitting large datasets into smaller subsets for parallel processing, leading to improved performance.', 'The integration service queries the database for table partition information and reads partition data from the corresponding nodes in database partitioning, which enhances performance by interacting with specific partitions.', 'Round robin partitioning evenly distributes data among different partitions to balance the load and execute data processing in parallel, leading to load balancing and improved performance.', 'Hash auto keys partitioning is used to group and push data based on group by conditions without defining the keys, and it is beneficial for group transformations like aggregator, sorter, and joiner.', 'Hash user keys partitioning groups data based on user-defined partitioning keys, allowing the selection of ports defining the partitioning key within the transformation.', 'Partitioning is done through the session properties tab, offering options for transformation and partitioning.', 'The partitioning process allows for the creation of different partitions within the job.']}, {'end': 3168.769, 'segs': [{'end': 2628.658, 'src': 'embed', 'start': 2598.499, 'weight': 1, 'content': [{'end': 2603.24, 'text': 'Any specific reason for that? No, because it distributes the data evenly among all the partitions.', 'start': 2598.499, 'duration': 4.741}, {'end': 2610.003, 'text': 'Okay And if I say that it can be hash auto key also, then I think I got a reply.', 'start': 2603.681, 'duration': 6.322}, {'end': 2611.124, 'text': 'Jain is saying the same thing.', 'start': 2610.043, 'duration': 1.081}, {'end': 2612.364, 'text': 'All right.', 'start': 2611.284, 'duration': 1.08}, {'end': 2615.385, 'text': 'If I talk about hash auto key, that is better.', 'start': 2612.424, 'duration': 2.961}, {'end': 2616.666, 'text': 'Okay All right, guys.', 'start': 2615.986, 'duration': 0.68}, {'end': 2618.333, 'text': 'Let me explain to you.', 'start': 2617.233, 'duration': 1.1}, {'end': 2622.715, 'text': "It's nothing like a specific partitioning method is better.", 'start': 2618.654, 'duration': 4.061}, {'end': 2628.658, 'text': 'If it would have been better, then that should be the only option that would have been given in a particular job.', 'start': 2623.275, 'duration': 5.383}], 'summary': 'Distributing data evenly among partitions is important; no specific partitioning method is better.', 'duration': 30.159, 'max_score': 2598.499, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2598499.jpg'}, {'end': 2672.693, 'src': 'embed', 'start': 2641.695, 'weight': 3, 'content': [{'end': 2644.136, 'text': 'A specific partitioning method is better.', 'start': 2641.695, 'duration': 2.441}, {'end': 2652.978, 'text': 'If we are working on the optimization part, we need to go ahead and check that, which is the partitioning that is helping me a lot,', 'start': 2644.496, 'duration': 8.482}, {'end': 2657.138, 'text': 'or helping us a lot, in order to increase the performance.', 'start': 2652.978, 'duration': 4.16}, {'end': 2660.279, 'text': 'It will vary from one job to another job.', 'start': 2657.679, 'duration': 2.6}, {'end': 2665.9, 'text': "We can't go ahead and say that this one is the better or this one is the most beneficial one.", 'start': 2660.419, 'duration': 5.481}, {'end': 2668.161, 'text': 'Harveen, I hope I answered your question.', 'start': 2666.12, 'duration': 2.041}, {'end': 2672.693, 'text': "Hey, Harveen, am I audible? Okay, Harveen is saying, can you unmute? Sure, Harveen, I'll unmute you.", 'start': 2668.421, 'duration': 4.272}], 'summary': 'Partitioning method varies by job, no definitive best option.', 'duration': 30.998, 'max_score': 2641.695, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2641695.jpg'}, {'end': 2751.624, 'src': 'embed', 'start': 2726.192, 'weight': 2, 'content': [{'end': 2735.056, 'text': "So this is just a concept that if I need to group by, then obviously, if I'm using rank sorter, any aggregator where I'm grouping up the data,", 'start': 2726.192, 'duration': 8.864}, {'end': 2737.297, 'text': "then I'll go and use hash auto key partitioning.", 'start': 2735.056, 'duration': 2.241}, {'end': 2747.022, 'text': "And then if I have some other transformations, like union, and if I'm using expression, multiple expressions, then I'll go ahead and use round robin.", 'start': 2737.758, 'duration': 9.264}, {'end': 2751.624, 'text': 'So it depends on the scenario that you are using at the moment in a particular job.', 'start': 2747.402, 'duration': 4.222}], 'summary': 'Use hash auto key partitioning for grouping, round robin for other transformations.', 'duration': 25.432, 'max_score': 2726.192, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2726192.jpg'}, {'end': 2937.17, 'src': 'embed', 'start': 2905.072, 'weight': 0, 'content': [{'end': 2908.113, 'text': 'It can be daily, weekly, monthly, yearly, anything, quarterly.', 'start': 2905.072, 'duration': 3.041}, {'end': 2909.973, 'text': 'We have a clerical user.', 'start': 2908.413, 'duration': 1.56}, {'end': 2913.714, 'text': 'We have knowledge users like the higher management, obviously.', 'start': 2910.553, 'duration': 3.161}, {'end': 2923.264, 'text': 'Why we are creating a data warehouse? So that our management can come to a specific conclusion and they can find out that how their business is doing.', 'start': 2914.181, 'duration': 9.083}, {'end': 2930.947, 'text': 'Or if they want to reach out to the customers for a relevant product, then which all are the customers that they need to approach?', 'start': 2923.825, 'duration': 7.122}, {'end': 2937.17, 'text': 'So all these type of information can be find or they can easily conclude using OLAP.', 'start': 2931.047, 'duration': 6.123}], 'summary': 'Data warehouse supports management in making informed decisions based on customer data, enabling targeted product outreach.', 'duration': 32.098, 'max_score': 2905.072, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2905072.jpg'}], 'start': 2581.088, 'title': 'Optimizing and using partitioning methods in informatica power center', 'summary': 'Discusses considerations for choosing partitioning methods, emphasizing the importance of assessing performance impact based on workflow, transformations, and logic. it also covers informatica power center partitioning concepts, including hash auto key and round robin techniques, differences between oltp and olap, and key points such as data types, access methods, and user types.', 'chapters': [{'end': 2686.584, 'start': 2581.088, 'title': 'Optimizing partitioning methods', 'summary': 'Discusses the considerations for choosing partitioning methods, emphasizing the need to assess performance impact based on workflow, transformations, and logic, rather than favoring a specific method, thereby highlighting the importance of trial and error.', 'duration': 105.496, 'highlights': ['The key factor for choosing a partitioning method is based on the performance impact on the workflow, transformations, and logic used in a particular job.', 'There is no specific partitioning method that is universally better, as its effectiveness varies depending on the scenario and job requirements.', 'Emphasizing the importance of trial and error in determining the most beneficial partitioning method for optimizing performance.']}, {'end': 3168.769, 'start': 2687.064, 'title': 'Informatica power center partitioning', 'summary': 'Discusses the concept of informatica power center partitioning, including techniques such as hash auto key and round robin, as well as the differences between oltp and olap, highlighting key points such as data types, access methods, and user types.', 'duration': 481.705, 'highlights': ['Informatica Power Center partitioning techniques The instructor discusses the use of hash auto key and round robin partitioning techniques based on different types of transformations and scenarios.', 'Differences between OLTP and OLAP Key differences between OLTP and OLAP are explained, including data types, access methods, user types, and data redundancy.', 'Explanation of surrogate keys The concept of surrogate keys is explained as unique identification keys, often used in slowly changing dimensions, with examples such as incrementing integers and sequence generators.', 'Output files created by Informatica server The types of output files created during session execution, including log files and bad files for rejected records, are discussed.']}], 'duration': 587.681, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI2581088.jpg', 'highlights': ['The key factor for choosing a partitioning method is based on the performance impact on the workflow, transformations, and logic used in a particular job.', 'Emphasizing the importance of trial and error in determining the most beneficial partitioning method for optimizing performance.', 'Differences between OLTP and OLAP are explained, including data types, access methods, user types, and data redundancy.', 'Informatica Power Center partitioning techniques The instructor discusses the use of hash auto key and round robin partitioning techniques based on different types of transformations and scenarios.']}, {'end': 3971.328, 'segs': [{'end': 3802.173, 'src': 'embed', 'start': 3761.996, 'weight': 0, 'content': [{'end': 3770.751, 'text': 'If I talk about a session level, That means it instructs the integration service to either create all row in the same way, insert, update, or delete.', 'start': 3761.996, 'duration': 8.755}, {'end': 3772.833, 'text': 'We have the check boxes over there if you remember.', 'start': 3770.832, 'duration': 2.001}, {'end': 3778.759, 'text': 'Or use instructions coded in the session mapping to flag for different database operations.', 'start': 3773.534, 'duration': 5.225}, {'end': 3782.923, 'text': 'Whereas in time mapping level, we will be using update strategy transformation.', 'start': 3779.26, 'duration': 3.663}, {'end': 3790.107, 'text': 'So you remember, on the session properties and the mapping tab, the target site, you will find those three to four checkboxes,', 'start': 3783.023, 'duration': 7.084}, {'end': 3793.268, 'text': 'which says insert as insert or up cert.', 'start': 3790.107, 'duration': 3.161}, {'end': 3793.909, 'text': 'do you remember that?', 'start': 3793.268, 'duration': 0.641}, {'end': 3797.03, 'text': 'So we are talking about those four checkboxes.', 'start': 3794.329, 'duration': 2.701}, {'end': 3802.173, 'text': 'Bindu, I think that you have raised your hand, is it from the past or you have a question? Okay, let me unmute you.', 'start': 3797.21, 'duration': 4.963}], 'summary': 'Instructs integration service on row operations and update strategy transformation at session and time mapping levels, with checkboxes for different database operations.', 'duration': 40.177, 'max_score': 3761.996, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI3761996.jpg'}], 'start': 3169.169, 'title': 'Informatica transformations', 'summary': 'Discusses active vs passive transformations, informatica transformations overview and the update strategy transformation. it emphasizes the differences, performance optimization, and keywords used, providing examples and highlighting join conditions.', 'chapters': [{'end': 3298.758, 'start': 3169.169, 'title': 'Active vs passive transformations', 'summary': 'Discusses the difference between active and passive transformations in informatica, emphasizing that active transformations can change the number of rows passing through, while passive transformations do not alter the row count. harveen provides examples to illustrate the concept.', 'duration': 129.589, 'highlights': ['Harveen explains that an active transformation can potentially change the number of records passing through, while a passive transformation does not alter the row count.', 'The speaker emphasizes that active transformations can change the number of rows passing through, the transaction boundary, or the row type, whereas passive transformations do not affect these aspects.', 'A specific example is given to illustrate active transformation, where a filter transformation reduces 10 source records to 2 output rows.', 'Another example is provided to demonstrate passive transformation, where an expression transformation does not change the number of rows (10) after trimming a column length.']}, {'end': 3643.614, 'start': 3298.938, 'title': 'Informatica transformations overview', 'summary': 'Discusses the active and passive transformations, focusing on the sorter, router, filter, and joiner transformations in informatica, highlighting the differences and performance optimization techniques, with emphasis on the distinct and join conditions.', 'duration': 344.676, 'highlights': ['Sorter is considered an active transformation due to the distinct option and fluctuation in row count, not because of sorting ascending and descending. The sorter is categorized as an active transformation due to its distinct option, leading to a fluctuation in the count of rows, emphasizing its status as an active transformation.', 'Router and filter transformations differ in handling rows that do not meet conditions, with router being a single input and multiple output group transformation, while filter is a single input and single output group transformation. The router and filter transformations vary in handling rows that do not meet conditions, with the router being a single input and multiple output group transformation, while the filter is a single input and single output group transformation.', 'Performance optimization for joiner transformation involves designating the source with fewer rows as the master source and avoiding joining using a joiner transformation for improved performance. The performance optimization for joiner transformation includes designating the source with fewer rows as the master source and avoiding joining using a joiner transformation for improved performance in Informatica.']}, {'end': 3971.328, 'start': 3644.054, 'title': 'Informatica update strategy transformation', 'summary': 'Covers the update strategy transformation in informatica, including its importance, keywords used, implementation levels, and types of joins, with a focus on the four major keywords used in the update strategy transformation and the types of joins.', 'duration': 327.274, 'highlights': ['The update strategy transformation is used to insert, delete, and update records in the target table, with four major keywords - DD insert, DD update, DD delete, and DD reject. The update strategy transformation allows insertion, deletion, and updating of records in the target table using keywords such as DD insert, DD update, DD delete, and DD reject.', 'The update strategy helps in tagging records for insert, update, delete, or reject, and can be set at session and mapping levels, providing instructions for different database operations. The update strategy facilitates tagging records for insert, update, delete, or reject, and can be implemented at session and mapping levels, offering instructions for varied database operations.', 'Types of joins that can be performed using a joiner transformation include normal join, master outer join, detail outer join, and full outer join. The joiner transformation supports various types of joins such as normal join, master outer join, detail outer join, and full outer join.']}], 'duration': 802.159, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI3169169.jpg', 'highlights': ['Active transformations can change the number of records passing through, while passive transformations do not alter the row count.', 'The update strategy transformation allows insertion, deletion, and updating of records in the target table using keywords such as DD insert, DD update, DD delete, and DD reject.', 'Performance optimization for joiner transformation includes designating the source with fewer rows as the master source and avoiding joining using a joiner transformation for improved performance in Informatica.', 'The router and filter transformations vary in handling rows that do not meet conditions, with the router being a single input and multiple output group transformation, while the filter is a single input and single output group transformation.']}, {'end': 4564.511, 'segs': [{'end': 4155.312, 'src': 'embed', 'start': 4111.194, 'weight': 0, 'content': [{'end': 4115.015, 'text': "All right, Bindu, so as Bindu just explained, I'll come to your question, Bindu.", 'start': 4111.194, 'duration': 3.821}, {'end': 4115.736, 'text': 'Just give me a moment.', 'start': 4115.036, 'duration': 0.7}, {'end': 4118.496, 'text': 'As Bindu explained, that reusable.', 'start': 4116.156, 'duration': 2.34}, {'end': 4126.938, 'text': 'we generally go ahead and create a reusable transformation if we need to use the same type of transformation with the same logic in another mapping.', 'start': 4118.496, 'duration': 8.442}, {'end': 4131.339, 'text': 'So we are just making it reusable and it will be globally available.', 'start': 4127.238, 'duration': 4.101}, {'end': 4136.18, 'text': 'We can easily drag it to one of the other mapping and we can use it over there.', 'start': 4131.799, 'duration': 4.381}, {'end': 4144.209, 'text': 'But yes, we can only reuse the transformation only if the metadata requirements in the mapping are exactly the same.', 'start': 4136.546, 'duration': 7.663}, {'end': 4149.45, 'text': 'By the term metadata, the number, the structure of the table, or the structure of the columns.', 'start': 4144.569, 'duration': 4.881}, {'end': 4155.312, 'text': 'The columns, same type of columns should be there, and then we can easily go ahead and make it reusable.', 'start': 4150.031, 'duration': 5.281}], 'summary': 'Reusable transformations are created for same logic in another mapping, requiring identical metadata.', 'duration': 44.118, 'max_score': 4111.194, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI4111194.jpg'}, {'end': 4573.962, 'src': 'embed', 'start': 4549.283, 'weight': 4, 'content': [{'end': 4559.328, 'text': 'And a shortcut is creating by assigning shared status to a folder within the repository manager and then dragging objects from this folder to another open folder.', 'start': 4549.283, 'duration': 10.045}, {'end': 4564.511, 'text': 'As I just told, we can easily create a shortcut by dragging it from one folder to another folder.', 'start': 4559.488, 'duration': 5.023}, {'end': 4573.962, 'text': "Whereas if I'll talk about reusable transformation A reusable transformation, if we have the same logic to implement across multiple mappings,", 'start': 4564.811, 'duration': 9.151}], 'summary': 'Create shortcuts by assigning shared status to folders and dragging objects between them. reusable transformation allows implementing the same logic across multiple mappings.', 'duration': 24.679, 'max_score': 4549.283, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI4549283.jpg'}], 'start': 3971.88, 'title': 'Informatica joins and reusable transformations', 'summary': 'Discusses informatica joins, master outer join and detail outer join differences, creation of reusable transformations and maplets, emphasizing their usage and limitations, with a mention of the percentage of real-time usage for reusable transformations.', 'chapters': [{'end': 4363.749, 'start': 3971.88, 'title': 'Informatica joins and reusable transformations', 'summary': 'Discusses informatica joins, highlighting the difference between master outer join and detail outer join, and the process of creating reusable transformations and maplets, emphasizing their usage and limitations, with a mention of the percentage of real-time usage for reusable transformations.', 'duration': 391.869, 'highlights': ['The chapter discusses the difference between master outer join and detail outer join. The chapter highlights the difference between a master outer join and a detail outer join within Informatica.', 'The process of creating reusable transformations is irreversible, and once changed, they cannot be reverted back to non-reusable. The process of changing a transformation to a reusable form is irreversible, and once changed, it cannot be reverted back to a non-reusable state.', 'The difference between a reusable and non-reusable transformation is explained, highlighting that reusable transformations can be used in different mappings, reducing complexity and enabling global availability. The difference between a reusable and non-reusable transformation is explained, emphasizing that reusable transformations can be used in different mappings, reducing complexity and enabling global availability.', 'The usage of reusable transformations in real-time is mentioned to be around 15-20%, with a focus on mapping-specific transformations for achieving specific targets. The usage of reusable transformations in real-time is mentioned to be around 15-20%, with a focus on mapping-specific transformations for achieving specific targets.', 'The difference between a maplet and a mapping is explained, with emphasis on a maplet being a collection of transformations that can be reused in multiple mappings, while a mapping is developed for data movement to the target and modifications. The difference between a maplet and a mapping is explained, emphasizing that a maplet is a collection of transformations that can be reused in multiple mappings, while a mapping is developed for data movement to the target and modifications.', 'The differences between a reusable transformation and a maplet are outlined, highlighting the creation process and the limitations of using mapping variables or parameters. The differences between a reusable transformation and a maplet are outlined, highlighting the creation process and the limitations of using mapping variables or parameters.']}, {'end': 4564.511, 'start': 4363.769, 'title': 'Mapping parameters and reusable transformations', 'summary': 'Discussed mapping variables and parameters, the use of reusable transformations within maplets, and the creation of shortcuts for shared objects, with an emphasis on the importance of parameterizing values and the limitations of certain transformations within maplets.', 'duration': 200.742, 'highlights': ['Creating a maplet automatically makes the transformation within it reusable. Once a maplet is created, the transformations within it become automatically reusable.', 'Shortcut creation involves referencing an object in a shared folder and dragging it to another folder for shared usage. Shortcuts are used for sharing sources and targets between different environments or projects by referencing objects from a shared folder and dragging them to another folder.', 'Maplets have limitations on using COBOL source qualifier, joiner, and normalizer transformations. Certain transformations like COBOL source qualifier, joiner, and normalizer cannot be used within maplets, whereas reusable joiner and normalizer transformations can be created and reused.', 'Parameterizing values is essential to avoid hard-coded values and enable flexibility in mapping. The importance of using mapping parameters and variables is to avoid hard-coded values and enable the parameterization of values for flexibility in mapping.']}], 'duration': 592.631, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI3971880.jpg', 'highlights': ['The usage of reusable transformations in real-time is mentioned to be around 15-20%, with a focus on mapping-specific transformations for achieving specific targets.', 'The difference between a maplet and a mapping is explained, emphasizing that a maplet is a collection of transformations that can be reused in multiple mappings, while a mapping is developed for data movement to the target and modifications.', 'The process of creating reusable transformations is irreversible, and once changed, they cannot be reverted back to non-reusable.', 'The difference between a reusable and non-reusable transformation is explained, emphasizing that reusable transformations can be used in different mappings, reducing complexity and enabling global availability.', 'Shortcut creation involves referencing an object in a shared folder and dragging it to another folder for shared usage.', 'Parameterizing values is essential to avoid hard-coded values and enable flexibility in mapping.', 'Creating a maplet automatically makes the transformation within it reusable.', 'The differences between a reusable transformation and a maplet are outlined, highlighting the creation process and the limitations of using mapping variables or parameters.', 'Maplets have limitations on using COBOL source qualifier, joiner, and normalizer transformations.']}, {'end': 5286.791, 'segs': [{'end': 5050.368, 'src': 'heatmap', 'start': 4921.354, 'weight': 0, 'content': [{'end': 4923.194, 'text': "I'll let you know what's the difference between them.", 'start': 4921.354, 'duration': 1.84}, {'end': 4927.416, 'text': "Basically, if we'll talk about a static cache, let me tell you that.", 'start': 4923.755, 'duration': 3.661}, {'end': 4934.618, 'text': "If we'll talk about a static cache, it's the same as a cached lookup, in which one sort of cache is created.", 'start': 4927.876, 'duration': 6.742}, {'end': 4941.628, 'text': 'right?. the integration service is going to always query the cache instead of the lookup table.', 'start': 4934.618, 'duration': 7.01}, {'end': 4951.791, 'text': 'So once the cache will be created, the integration service is always going to find out the value in the created cache rather than the lookup table.', 'start': 4941.808, 'duration': 9.983}, {'end': 4960.092, 'text': "That's the static cache and basically one important thing that I would like to highlight that in case of static cache,", 'start': 4952.211, 'duration': 7.881}, {'end': 4963.253, 'text': 'we cannot insert or update the cache.', 'start': 4960.092, 'duration': 3.161}, {'end': 4966.435, 'text': "We can't go ahead and insert or update that particular cache.", 'start': 4963.632, 'duration': 2.803}, {'end': 4970.118, 'text': "Whereas, it's a bit different in case of dynamic cache.", 'start': 4966.815, 'duration': 3.303}, {'end': 4977.544, 'text': 'In dynamic cache, we can insert or update the rows in the cache whenever we pass the rows.', 'start': 4970.598, 'duration': 6.946}, {'end': 4980.587, 'text': 'So, we can go ahead and insert and update those rows.', 'start': 4978.085, 'duration': 2.502}, {'end': 4989.715, 'text': 'Whereas the integration service dynamically inserts or updates data in the lookup cache and passes the data to the target right?', 'start': 4981.167, 'duration': 8.548}, {'end': 4994.495, 'text': 'So, basically, the dynamic cache is always synchronized with the target system.', 'start': 4990.051, 'duration': 4.444}, {'end': 4997.857, 'text': "So that's static cache as well as a dynamic cache.", 'start': 4994.675, 'duration': 3.182}, {'end': 5002.321, 'text': "If I'll talk about a few more caches concept that we have, it's a shared cache.", 'start': 4998.098, 'duration': 4.223}, {'end': 5010.688, 'text': 'It is the cache when Informatica server creates a cache memory for multiple lookup transformations in a specific mapping.', 'start': 5002.641, 'duration': 8.047}, {'end': 5013.97, 'text': 'And once the lookup is done for the first lookup,', 'start': 5011.088, 'duration': 2.882}, {'end': 5019.754, 'text': "then the memory is going to be released from it and it's going to be used for the next lookup transformation.", 'start': 5013.97, 'duration': 5.784}, {'end': 5021.895, 'text': "So that's shared cache basically.", 'start': 5019.934, 'duration': 1.961}, {'end': 5025.538, 'text': "And if I'll talk about the persistent one, right?", 'start': 5022.116, 'duration': 3.422}, {'end': 5032.282, 'text': "So we can use persistent caches because, basically, if you're going to use it,", 'start': 5025.958, 'duration': 6.324}, {'end': 5039.707, 'text': 'Informatica service processes a lookup transformation and saves the lookup cache files and reuses them for the next level.', 'start': 5032.282, 'duration': 7.425}, {'end': 5050.368, 'text': 'And basically, in order to the integration service, it saves or delete the lookup cache files after the successful run.', 'start': 5041.76, 'duration': 8.608}], 'summary': 'Static cache does not allow insert/update, while dynamic cache allows it. shared cache is used for multiple lookup transformations, and persistent cache saves and reuses lookup cache files.', 'duration': 45.081, 'max_score': 4921.354, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI4921354.jpg'}], 'start': 4564.811, 'title': 'Reusable vs. shortcut transformations and lookup in informatica', 'summary': 'Discusses the difference between reusable and shortcut transformations, emphasizing the ability of reusable transformations to be implemented across multiple mappings with the same metadata requirement, while a shortcut transformation cannot be reused. additionally, it covers the concept of lookup transformation in informatica, including its types, differences between connected and unconnected lookups, and various types of cache involved, focusing on performance enhancement.', 'chapters': [{'end': 4608.223, 'start': 4564.811, 'title': 'Difference between reusable and shortcut transformation', 'summary': 'Discusses the difference between reusable and shortcut transformations, emphasizing that reusable transformations allow the same logic to be implemented across multiple mappings, provided the metadata requirement is exactly the same, while a shortcut transformation cannot be reused and may be a potential interview question.', 'duration': 43.412, 'highlights': ['Reusable transformations allow the same logic to be implemented across multiple mappings, provided the metadata requirement is exactly the same.', 'Shortcut transformations cannot be reused and may be a potential interview question.']}, {'end': 5286.791, 'start': 4608.563, 'title': 'Lookup transformation in informatica', 'summary': 'Discusses the concept of lookup transformation in informatica, covering its types, differences between connected and unconnected lookups, and the various types of cache involved, including their functionalities and differences, with a focus on enhancing performance.', 'duration': 678.228, 'highlights': ['Lookup types and differences The chapter explains the two types of lookups - connected and unconnected - and highlights the differences between them, such as their association with the data flow, usage of expression transformation, and the sources they can look up into, providing a clear understanding of their functionalities and usage.', 'Types of cache in lookup transformation The discussion covers the various types of caches involved in lookup transformation, including static cache, dynamic cache, shared cache, persistent cache, and re-cache from source, with detailed explanations on their functionalities and impact on performance, providing a comprehensive understanding of cache usage in Informatica.', 'Difference between static and dynamic caching The chapter elaborates on the major difference between static and dynamic caching, emphasizing that dynamic cache refreshes its memory upon record insertion, update, or deletion in the lookup table, whereas static cache does not, providing a clear distinction between the two caching mechanisms and their impact during runtime.']}], 'duration': 721.98, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI4564811.jpg', 'highlights': ['Reusable transformations allow the same logic to be implemented across multiple mappings, provided the metadata requirement is exactly the same.', 'Types of cache in lookup transformation The discussion covers the various types of caches involved in lookup transformation, including static cache, dynamic cache, shared cache, persistent cache, and re-cache from source, with detailed explanations on their functionalities and impact on performance, providing a comprehensive understanding of cache usage in Informatica.', 'Lookup types and differences The chapter explains the two types of lookups - connected and unconnected - and highlights the differences between them, such as their association with the data flow, usage of expression transformation, and the sources they can look up into, providing a clear understanding of their functionalities and usage.']}, {'end': 6271.023, 'segs': [{'end': 5365.518, 'src': 'embed', 'start': 5334.653, 'weight': 4, 'content': [{'end': 5335.853, 'text': 'After the execution, it will drop it.', 'start': 5334.653, 'duration': 1.2}, {'end': 5337.372, 'text': 'Yeah Okay.', 'start': 5336.232, 'duration': 1.14}, {'end': 5338.253, 'text': 'All right.', 'start': 5337.892, 'duration': 0.361}, {'end': 5339.693, 'text': 'So thank you.', 'start': 5338.373, 'duration': 1.32}, {'end': 5340.593, 'text': "Let's move forward.", 'start': 5339.733, 'duration': 0.86}, {'end': 5346.735, 'text': 'Now there can be one of the important question how do you improve the performance of a lookup transformation?', 'start': 5340.953, 'duration': 5.782}, {'end': 5352.176, 'text': 'right?. So just you can go through these points wherein we can improve the performance.', 'start': 5346.735, 'duration': 5.441}, {'end': 5357.818, 'text': 'We can create an index on the columns that we are using for the lookup condition.', 'start': 5352.517, 'duration': 5.301}, {'end': 5365.518, 'text': "That means if I'm just extracting the salary on the basis of department ID, then I'll go ahead and create an index on department ID.", 'start': 5358.171, 'duration': 7.347}], 'summary': 'Improving lookup transformation performance by creating an index on the lookup condition columns.', 'duration': 30.865, 'max_score': 5334.653, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI5334653.jpg'}, {'end': 5514.424, 'src': 'embed', 'start': 5466.985, 'weight': 0, 'content': [{'end': 5474.73, 'text': 'And we cannot override how the data is fetched into the joiner, whereas we can override that thing in case of lookup.', 'start': 5466.985, 'duration': 7.745}, {'end': 5477.517, 'text': 'So this is one of the major differences.', 'start': 5475.196, 'duration': 2.321}, {'end': 5484.519, 'text': 'And there is no separate type of caches that can be used to improve performance in case of a joiner transformation.', 'start': 5477.937, 'duration': 6.582}, {'end': 5490.741, 'text': 'But we have different types of caches which can improve its performance in case of a lookup cache.', 'start': 5484.919, 'duration': 5.822}, {'end': 5500.304, 'text': 'So when do we use a lookup override transformation? So there can be multiple factors that we can use a particular override.', 'start': 5491.501, 'duration': 8.803}, {'end': 5508.278, 'text': 'And we generally override or use the SQL query in order to select specific columns to apply different logic to a specific columns.', 'start': 5500.971, 'duration': 7.307}, {'end': 5511.321, 'text': 'So we go ahead and write down the SQL query for them.', 'start': 5508.398, 'duration': 2.923}, {'end': 5514.424, 'text': 'So or the lookup override for them.', 'start': 5511.942, 'duration': 2.482}], 'summary': 'Lookup can be overridden for improved performance, unlike joiner.', 'duration': 47.439, 'max_score': 5466.985, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI5466985.jpg'}, {'end': 5560.867, 'src': 'embed', 'start': 5535.508, 'weight': 2, 'content': [{'end': 5543.53, 'text': 'So these all are the few reasons why we need a lookup override in order to go ahead and compile it to get the desired results.', 'start': 5535.508, 'duration': 8.022}, {'end': 5548.211, 'text': 'Okay, so we have covered two of the sections over here.', 'start': 5544.05, 'duration': 4.161}, {'end': 5551.632, 'text': 'Now we have workflow related questions that we need to cover.', 'start': 5548.391, 'duration': 3.241}, {'end': 5553.323, 'text': 'What do you say, guys?', 'start': 5552.182, 'duration': 1.141}, {'end': 5560.867, 'text': 'Shall we split for a break of 10 minutes more than more minutes and then we will be back and then we will cover the remaining questions as well as the scenarios.', 'start': 5553.363, 'duration': 7.504}], 'summary': 'Discussion on lookup override and workflow questions, planning a 10-minute break', 'duration': 25.359, 'max_score': 5535.508, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI5535508.jpg'}, {'end': 5987.278, 'src': 'embed', 'start': 5962.802, 'weight': 7, 'content': [{'end': 5968.786, 'text': 'And then I check for the indexes, then I check for the SQL query, then I check for the insert option,', 'start': 5962.802, 'duration': 5.984}, {'end': 5973.089, 'text': "whether it's a bulk or normal mode that we want to select.", 'start': 5968.786, 'duration': 4.303}, {'end': 5975.55, 'text': 'Are you aware of these things, right? Yes, yes.', 'start': 5973.249, 'duration': 2.301}, {'end': 5977.452, 'text': 'Perfect So you can discuss these things.', 'start': 5976.131, 'duration': 1.321}, {'end': 5982.175, 'text': 'And then, finally, I came to the conclusion that if we are going to perform this activity in parallel,', 'start': 5977.512, 'duration': 4.663}, {'end': 5984.196, 'text': "then obviously it's going to save time as a whole.", 'start': 5982.175, 'duration': 2.021}, {'end': 5985.877, 'text': "And that's what I did.", 'start': 5984.356, 'duration': 1.521}, {'end': 5987.278, 'text': 'Simple Okay.', 'start': 5986.197, 'duration': 1.081}], 'summary': 'Checked indexes, sql query, insert options, and concluded parallel activity saves time.', 'duration': 24.476, 'max_score': 5962.802, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI5962802.jpg'}, {'end': 6121.642, 'src': 'embed', 'start': 6090.641, 'weight': 6, 'content': [{'end': 6095.081, 'text': "we'll go to the contents and then There is a performance tuning guide.", 'start': 6090.641, 'duration': 4.44}, {'end': 6096.163, 'text': 'Here it is.', 'start': 6095.722, 'duration': 0.441}, {'end': 6099.568, 'text': 'Right? Performance tuning overview.', 'start': 6097.525, 'duration': 2.043}, {'end': 6101.911, 'text': 'Okay See.', 'start': 6099.588, 'duration': 2.323}, {'end': 6107.76, 'text': 'Okay You can just go through simple these steps.', 'start': 6103.313, 'duration': 4.447}, {'end': 6109.434, 'text': "It's a small PDF.", 'start': 6108.573, 'duration': 0.861}, {'end': 6111.235, 'text': 'You can read it whenever you get time.', 'start': 6109.454, 'duration': 1.781}, {'end': 6113.517, 'text': 'And it will definitely help you with this.', 'start': 6111.955, 'duration': 1.562}, {'end': 6114.617, 'text': 'Okay? Yeah.', 'start': 6114.197, 'duration': 0.42}, {'end': 6116.599, 'text': 'Yeah Got it.', 'start': 6115.118, 'duration': 1.481}, {'end': 6117.699, 'text': 'Thank you.', 'start': 6117.299, 'duration': 0.4}, {'end': 6119.461, 'text': 'Okay Thanks, Bindu.', 'start': 6117.98, 'duration': 1.481}, {'end': 6119.881, 'text': 'All right.', 'start': 6119.541, 'duration': 0.34}, {'end': 6121.642, 'text': 'So I can see I have a raised hand.', 'start': 6119.961, 'duration': 1.681}], 'summary': 'Performance tuning guide provided in a small pdf for better performance. it will definitely help with tuning.', 'duration': 31.001, 'max_score': 6090.641, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI6090641.jpg'}], 'start': 5286.791, 'title': 'Optimizing informatica job performance', 'summary': 'Covers cache deletion in static lookup, improving lookup transformation performance through indexing and caching strategies, and optimizing complex informatica jobs by breaking down tasks and addressing performance issues, workflow interviews, and bottlenecks.', 'chapters': [{'end': 5333.232, 'start': 5286.791, 'title': 'Cache deletion in static lookup', 'summary': 'Discusses the deletion of cache in a static lookup where the cache memory will not get refreshed until the next run, impacting the execution and data retrieval process.', 'duration': 46.441, 'highlights': ['The cache in static lookup gets deleted only in the next run, impacting the data retrieval process.', 'In static lookup, the cache memory will not get refreshed, even though the record is inserted in a lookup table.', 'Once the transaction completes in static lookup, the cache gets executed and then removed.']}, {'end': 5594.576, 'start': 5334.653, 'title': 'Improving lookup transformation performance', 'summary': 'Discusses ways to improve the performance of a lookup transformation, including creating an index on lookup columns, using cache for small lookup tables, joining tables in the same database, and using persistent cache for static lookups.', 'duration': 259.923, 'highlights': ['Creating an index on lookup columns Creating an index on the columns used in the lookup condition can significantly enhance performance, especially when extracting data based on specific conditions. This can be done at the database level.', 'Using cache for small lookup tables Utilizing cache for small lookup tables can enhance performance by reducing the need for repeated data retrieval from the database.', 'Joining tables in the same database Joining tables in the same database instead of using a lookup transformation can improve performance, particularly when both the source and lookup tables are in the same database.', "Using persistent cache for static lookups and avoiding order by Implementing persistent cache for static lookups and avoiding the use of 'order by' can further optimize the performance of lookup transformations."]}, {'end': 6271.023, 'start': 5595.056, 'title': 'Optimizing complex informatica job', 'summary': 'Discusses optimizing a complex informatica job, involving breaking down a job into two parts, tuning performance, and handling challenging interview questions, such as handling bottlenecks and workflow interview questions.', 'duration': 675.967, 'highlights': ['Breaking down a job into two parts helped in optimizing a complex Informatica job, reducing the overall job runtime from four hours to one hour and 40 minutes. Breaking down a job into two parts reduced the overall runtime from four hours to one hour and 40 minutes.', 'Optimizing SQL queries and breaking down the job into smaller segments resulted in significant time savings during execution. Optimizing SQL queries and breaking down the job into smaller segments resulted in significant time savings during execution, reducing the time from multiple hours to one hour and 40 minutes.', 'Discussing handling bottlenecks and performance tuning techniques, including identifying bottlenecks at target, source, mapping, session, and system levels. Discussion on handling bottlenecks and performance tuning techniques, including identifying bottlenecks at target, source, mapping, session, and system levels.', 'Addressing challenging interview questions related to optimizing Informatica jobs and explaining workflow concepts and differences between stop and abort commands. Addressing challenging interview questions related to optimizing Informatica jobs, explaining workflow concepts, and differences between stop and abort commands.']}], 'duration': 984.232, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI5286791.jpg', 'highlights': ['Creating an index on lookup columns can significantly enhance performance, especially when extracting data based on specific conditions.', 'Utilizing cache for small lookup tables can enhance performance by reducing the need for repeated data retrieval from the database.', 'Joining tables in the same database instead of using a lookup transformation can improve performance, particularly when both the source and lookup tables are in the same database.', "Using persistent cache for static lookups and avoiding the use of 'order by' can further optimize the performance of lookup transformations.", 'Breaking down a job into two parts reduced the overall runtime from four hours to one hour and 40 minutes.', 'Optimizing SQL queries and breaking down the job into smaller segments resulted in significant time savings during execution, reducing the time from multiple hours to one hour and 40 minutes.', 'Discussion on handling bottlenecks and performance tuning techniques, including identifying bottlenecks at target, source, mapping, session, and system levels.', 'Addressing challenging interview questions related to optimizing Informatica jobs, explaining workflow concepts, and differences between stop and abort commands.']}, {'end': 7931.884, 'segs': [{'end': 6494.526, 'src': 'embed', 'start': 6462.317, 'weight': 3, 'content': [{'end': 6463.478, 'text': 'I want to segregate it.', 'start': 6462.317, 'duration': 1.161}, {'end': 6468.759, 'text': 'So how can we do that? We can do that by the help of concurrent workflow.', 'start': 6463.898, 'duration': 4.861}, {'end': 6475.321, 'text': 'A concurrent workflow is a workflow that can run as a multiple instances concurrently.', 'start': 6469.119, 'duration': 6.202}, {'end': 6478.939, 'text': 'a workflow instance representation of a workflow.', 'start': 6475.757, 'duration': 3.182}, {'end': 6484.101, 'text': 'That means it will be executing, but it will go ahead and execute it in parallel.', 'start': 6478.959, 'duration': 5.142}, {'end': 6494.526, 'text': "That means at the same, if I want to go ahead and load only department 20 data, then I will right click on it and I'll say execute with department 20.", 'start': 6484.281, 'duration': 10.245}], 'summary': 'Using concurrent workflow to run multiple instances in parallel for segregation.', 'duration': 32.209, 'max_score': 6462.317, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI6462317.jpg'}, {'end': 7020.92, 'src': 'embed', 'start': 6998.358, 'weight': 2, 'content': [{'end': 7009.101, 'text': 'We can go ahead and use indirect file load option in order to go ahead and load similar structured data files by mentioning the path in the text file,', 'start': 6998.358, 'duration': 10.743}, {'end': 7011.441, 'text': 'the new text file that we are creating.', 'start': 7009.101, 'duration': 2.34}, {'end': 7012.922, 'text': 'We can mention the path over there.', 'start': 7011.661, 'duration': 1.261}, {'end': 7014.422, 'text': 'We can load it accordingly.', 'start': 7013.282, 'duration': 1.14}, {'end': 7016.959, 'text': 'This concept is known as indirect file load.', 'start': 7014.798, 'duration': 2.161}, {'end': 7020.92, 'text': 'Okay, Lakshmi is saying, select indirect file load on session level.', 'start': 7017.479, 'duration': 3.441}], 'summary': 'Use indirect file load to load similar structured data files by specifying the path in a new text file. select indirect file load on session level.', 'duration': 22.562, 'max_score': 6998.358, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI6998358.jpg'}, {'end': 7523.577, 'src': 'heatmap', 'start': 7418.225, 'weight': 1, 'content': [{'end': 7422.707, 'text': 'The two will go to the one target, and all the records will go to the another target.', 'start': 7418.225, 'duration': 4.482}, {'end': 7423.768, 'text': 'Agreed, okay.', 'start': 7423.047, 'duration': 0.721}, {'end': 7426.05, 'text': 'You can do that.', 'start': 7424.889, 'duration': 1.161}, {'end': 7428.132, 'text': 'There is one more approach that is mentioned here.', 'start': 7426.07, 'duration': 2.062}, {'end': 7437.581, 'text': 'Rather than sorting it, they have taken an aggregator, right? Can we do it with the aggregator also, Lakshmi? Yes, yes, yeah, we can do that.', 'start': 7428.553, 'duration': 9.028}, {'end': 7441.245, 'text': "So they're performing the same action, but with the help of aggregator.", 'start': 7437.601, 'duration': 3.644}, {'end': 7446.157, 'text': "Okay, so that's, let's see one more quick scenario.", 'start': 7441.493, 'duration': 4.664}, {'end': 7446.998, 'text': 'What do you say?', 'start': 7446.418, 'duration': 0.58}, {'end': 7457.432, 'text': 'how you can load every nth record or every nth row from a flat file to relational database to the target, or relational database to the target?', 'start': 7446.998, 'duration': 10.434}, {'end': 7458.732, 'text': 'Every nth row.', 'start': 7457.772, 'duration': 0.96}, {'end': 7462.153, 'text': "nth row means, let's assume, n is equal to five.", 'start': 7458.732, 'duration': 3.421}, {'end': 7470.194, 'text': 'then in the same way, even in odd the same concept, we can divide by five or nth row anything that we want to take, the value of n.', 'start': 7462.153, 'duration': 8.041}, {'end': 7473.155, 'text': 'whatever we want to take, we can process it in the same manner.', 'start': 7470.194, 'duration': 2.961}, {'end': 7475.215, 'text': 'It is the same thing, more or less the same thing.', 'start': 7473.475, 'duration': 1.74}, {'end': 7478.816, 'text': "Okay, let's quickly move on to a different scenario.", 'start': 7475.575, 'duration': 3.241}, {'end': 7486.497, 'text': 'How to produce rows in target table, with every row as sum of all previous rows in source table?', 'start': 7479.232, 'duration': 7.265}, {'end': 7487.617, 'text': 'Okay, you got it?', 'start': 7486.697, 'duration': 0.92}, {'end': 7494.562, 'text': 'They mean to say that this is a source table where the number one record is 200, number two is 300..', 'start': 7488.218, 'duration': 6.344}, {'end': 7499.825, 'text': 'But in the target we want to add we are taking a cumulative sum.', 'start': 7494.562, 'duration': 5.263}, {'end': 7504.269, 'text': "you're just taking a cumulative sum of the complete column, right?", 'start': 7500.287, 'duration': 3.982}, {'end': 7512.892, 'text': "So if you see the cumulative sum at second quarter, I'm taking row number two, it becomes 500, and row number three, it becomes 1,000,", 'start': 7504.489, 'duration': 8.403}, {'end': 7514.713, 'text': 'because we are adding it.', 'start': 7512.892, 'duration': 1.821}, {'end': 7523.577, 'text': 'What do you say, guys? Anybody? Ishwari, would you like to take it? Or Bindu, Dhruv, Ishwari? Yeah, please, go ahead.', 'start': 7515.093, 'duration': 8.484}], 'summary': 'Discussing methods to process and load data, including using aggregators and producing cumulative sums in a target table.', 'duration': 105.352, 'max_score': 7418.225, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI7418225.jpg'}, {'end': 7892.8, 'src': 'embed', 'start': 7860.585, 'weight': 1, 'content': [{'end': 7863.151, 'text': 'We should be aware of these administrator interview questions.', 'start': 7860.585, 'duration': 2.566}, {'end': 7865.985, 'text': 'But please do practice all these scenarios.', 'start': 7863.584, 'duration': 2.401}, {'end': 7869.047, 'text': 'Okay, Lakshmi is saying normalize the incremental aggregate.', 'start': 7866.206, 'duration': 2.841}, {'end': 7869.708, 'text': 'Okay, perfect.', 'start': 7869.167, 'duration': 0.541}, {'end': 7870.808, 'text': 'The same thing I was saying.', 'start': 7869.868, 'duration': 0.94}, {'end': 7874.47, 'text': 'So these are a few of the scenarios that we just discussed.', 'start': 7870.908, 'duration': 3.562}, {'end': 7883.936, 'text': 'So an interviewer can go ahead and just give you these type of scenarios and ask you to go ahead and explain it on a piece of paper and a pen.', 'start': 7874.911, 'duration': 9.025}, {'end': 7885.217, 'text': 'That can also happen.', 'start': 7884.216, 'duration': 1.001}, {'end': 7892.8, 'text': 'But trust me, once you will start giving the interview, Make it a habit, once you will come back, write down those questions.', 'start': 7885.537, 'duration': 7.263}], 'summary': 'Prepare for administrator interview questions and practice scenarios to excel in interviews.', 'duration': 32.215, 'max_score': 7860.585, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI7860585.jpg'}, {'end': 7919.333, 'src': 'embed', 'start': 7894.762, 'weight': 0, 'content': [{'end': 7901.446, 'text': "And that's for sure that in the next three or third or fourth time, or fifth time at the most, you will be able to crack those interviews.", 'start': 7894.762, 'duration': 6.684}, {'end': 7912.093, 'text': "Because there's a similar set pattern of the scenarios of those transformations of the architecture questions that is going to be asked in an Informatica interview.", 'start': 7901.746, 'duration': 10.347}, {'end': 7919.333, 'text': 'So just make it a habit, start giving your interviews and just write down in a piece of paper and a pen, whenever you will be back,', 'start': 7912.454, 'duration': 6.879}], 'summary': 'With practice, crack informatica interviews in 3-5 attempts due to predictable question patterns.', 'duration': 24.571, 'max_score': 7894.762, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI7894762.jpg'}], 'start': 6271.603, 'title': 'Informatica workflow and data transformation', 'summary': 'Covers informatica workflow concepts, bulk and normal load differences, rank and sequence transformation for data analysis, and data transformation techniques emphasizing practical examples and real-time applications.', 'chapters': [{'end': 6665.208, 'start': 6271.603, 'title': 'Informatica workflow concepts', 'summary': 'Discusses the differences between stopping and aborting a workflow, the concept of worklets as reusable workflows, and the creation and execution of concurrent workflows, including how to configure and start them.', 'duration': 393.605, 'highlights': ['The difference between stopping and aborting a workflow There is a discussion about the difference between stopping and aborting a workflow, where stopping terminates the session and aborting terminates the session and kills the DTM access if the integration service cannot finish processing data within the timeout period.', 'Creation and execution of concurrent workflows Details about the creation and execution of concurrent workflows are provided, including the ability to run multiple instances concurrently and the steps to configure and start a concurrent workflow.', 'Concept of worklets as reusable workflows The concept of worklets as reusable workflows is explained, emphasizing their ability to specify or apply reusability at the Informatica workflow level, similar to maplets at the mapping level.']}, {'end': 7273.589, 'start': 6665.708, 'title': 'Understanding bulk and normal load', 'summary': 'Discusses the difference between bulk load and normal load, emphasizing that bulk load is suitable for one-time load activities of large data sets, while normal load is used for scheduled daily jobs, with the key point being that bulk load offers high performance and is selected for loading complete sets of records within a short time frame.', 'duration': 607.881, 'highlights': ["Bulk load is generally used for performance purposes and doesn't create database logs, making it suitable for one-time load activities of large data sets. In bulk load, Power Center doesn't create logs and directly dumps data into the database, offering high performance and efficiency.", 'Normal load creates database logs, allowing data recovery, and is suitable for scheduled daily jobs. Normal load creates database logs for data recovery and is used for scheduled daily jobs, even though it has lower performance compared to bulk load.', 'Bulk load is selected for loading complete sets of records within a short time frame window, such as during business shutdowns, offering quick data population. Bulk load is preferred for quick data population during short time frames, such as business shutdowns, while normal load is suitable for regular intervals and daily schedule jobs.', 'Indirect file load method is used to load similar structured data files by creating a text file with the file paths, known as indirect file load. The indirect file load method involves creating a text file with file paths to load similar structured data files, providing a flexible and efficient approach for loading data.', 'Sequence generator and expression transformation are used to load alternate records into different tables through mapping flow, demonstrating the need to develop a thought process to select the appropriate transformations for achieving desired results. The use of sequence generator and expression transformation to segregate even and odd records showcases the importance of developing a thoughtful approach to select suitable transformations for achieving specific outcomes.']}, {'end': 7594.777, 'start': 7275.77, 'title': 'Rank and sequence transformation for data analysis', 'summary': 'Discusses using rank and sequence transformations to identify first and last records, loading unique and duplicate records into different target tables, and calculating cumulative sum using expression transformation, with practical examples and real-time applications.', 'duration': 319.007, 'highlights': ['Using rank and sequence transformation to identify first and last records The instructor explains using two rank transformations and a sequence generator to identify and populate the first and last records, emphasizing the importance of practicing such scenarios and its relevance to real-world applications.', 'Loading unique and duplicate records into different target tables The discussion covers using two sorter transformations, one with distinct option for unique records and another without distinct option for duplicate records, or employing an aggregator to achieve the same action, providing multiple approaches to the task.', 'Calculating cumulative sum using expression transformation The chapter outlines using an expression transformation with a variable port to calculate cumulative sum, citing real-time application in the insurance industry for tracking policy claims and closures based on monthly data.']}, {'end': 7931.884, 'start': 7595.097, 'title': 'Data transformation techniques', 'summary': 'Discusses various data transformation techniques such as segregating dollar sign from a salary column using substring expression, splitting data column-wise based on a primary key, normalizing duplicate values in a column to comma-separated values, and emphasizes the importance of practicing and understanding interview scenarios to excel in informatica interviews.', 'duration': 336.787, 'highlights': ['The chapter discusses various data transformation techniques such as segregating dollar sign from a salary column using substring expression. The discussion focuses on using substring expression to segregate dollar signs from the salary column, providing a practical approach to data transformation.', 'Emphasizes the importance of practicing and understanding interview scenarios to excel in Informatica interviews. The importance of practicing and understanding interview scenarios is stressed, suggesting that it can be instrumental in excelling in Informatica interviews.', 'The chapter explains the process of splitting data column-wise based on a primary key. A detailed explanation is provided on splitting data column-wise based on a primary key, emphasizing the practical approach to achieving this data transformation.', 'Discusses the technique of normalizing duplicate values in a column to comma-separated values. The discussion covers the technique of normalizing duplicate values in a column to comma-separated values, offering a practical approach to this data transformation.']}], 'duration': 1660.281, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI6271603.jpg', 'highlights': ['Creation and execution of concurrent workflows', "Bulk load is generally used for performance purposes and doesn't create database logs", 'Using rank and sequence transformation to identify first and last records', 'Calculating cumulative sum using expression transformation', 'The chapter discusses various data transformation techniques such as segregating dollar sign from a salary column using substring expression']}, {'end': 9507.494, 'segs': [{'end': 8196.847, 'src': 'embed', 'start': 8171.073, 'weight': 0, 'content': [{'end': 8177.277, 'text': "So these all are, this is the difference between a PMCMD and PMREP, that's a PMREP actually.", 'start': 8171.073, 'duration': 6.204}, {'end': 8185.563, 'text': 'Okay, so if I talk about one more question that how we can go to the older version of a mapping.', 'start': 8177.597, 'duration': 7.966}, {'end': 8187.744, 'text': "It's in the versioning part.", 'start': 8186.363, 'duration': 1.381}, {'end': 8190.465, 'text': 'Once you need to go ahead, let me show it to you.', 'start': 8188.244, 'duration': 2.221}, {'end': 8191.365, 'text': 'This is a mapping.', 'start': 8190.665, 'duration': 0.7}, {'end': 8196.847, 'text': "I can simply go ahead and I'll right click over here, say versioning, I'll say view history.", 'start': 8191.465, 'duration': 5.382}], 'summary': 'Comparison of pmcmd and pmrep, with versioning example.', 'duration': 25.774, 'max_score': 8171.073, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI8171073.jpg'}, {'end': 8284.588, 'src': 'embed', 'start': 8245.239, 'weight': 1, 'content': [{'end': 8246.58, 'text': 'Do you practice on Unix??', 'start': 8245.239, 'duration': 1.341}, {'end': 8248.421, 'text': 'I mean, did you work on Unix or not?', 'start': 8246.639, 'duration': 1.782}, {'end': 8253.545, 'text': 'Yes, most of the times the Informatica is always installed on Unix boxes, right?', 'start': 8248.861, 'duration': 4.684}, {'end': 8265.112, 'text': "And Unix boxes means are you aware of a Unix box like, let's say, let me, have you ever worked on a Unix box with SCP or the Putty?", 'start': 8254.545, 'duration': 10.567}, {'end': 8267.361, 'text': "no? No, no, I didn't get it.", 'start': 8265.112, 'duration': 2.249}, {'end': 8275.445, 'text': "Okay, let me show you a quick review, but I'll not be able to log in and show it to you because it has my client sensitive data.", 'start': 8267.382, 'duration': 8.063}, {'end': 8277.266, 'text': "so I'll not be able to show that.", 'start': 8275.445, 'duration': 1.821}, {'end': 8279.466, 'text': 'but I can show you the application at least right?', 'start': 8277.266, 'duration': 2.2}, {'end': 8282.307, 'text': 'This is, you know the command prompt right?', 'start': 8279.706, 'duration': 2.601}, {'end': 8283.768, 'text': 'That how exactly it looks like?', 'start': 8282.548, 'duration': 1.22}, {'end': 8284.588, 'text': 'Yes,', 'start': 8284.348, 'duration': 0.24}], 'summary': 'Discussion about working on unix, mentioning informatica and tools like scp and putty.', 'duration': 39.349, 'max_score': 8245.239, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI8245239.jpg'}, {'end': 8606.399, 'src': 'embed', 'start': 8567.891, 'weight': 2, 'content': [{'end': 8570.472, 'text': 'Again, I will use those set of ETL jobs.', 'start': 8567.891, 'duration': 2.581}, {'end': 8575.452, 'text': 'But this time, I want to load my data as per my target requirement.', 'start': 8570.851, 'duration': 4.601}, {'end': 8576.513, 'text': 'By the term.', 'start': 8575.833, 'duration': 0.68}, {'end': 8582.055, 'text': 'target requirement means going forward once my data will be loaded to the target environment.', 'start': 8576.513, 'duration': 5.542}, {'end': 8586.196, 'text': 'after that, the reporting tools like QlikView, Cognos, Tableau.', 'start': 8582.055, 'duration': 4.141}, {'end': 8595.059, 'text': 'they are going to use my target database as their source in order to go ahead and reflect the data into the reports or the dashboards.', 'start': 8586.196, 'duration': 8.863}, {'end': 8606.399, 'text': 'You got me? So accordingly, put the business logic in my new ETL jobs now that is populating the data from the staging area and to the database.', 'start': 8595.279, 'duration': 11.12}], 'summary': 'Etl jobs to load data to target database for reporting tools.', 'duration': 38.508, 'max_score': 8567.891, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI8567891.jpg'}, {'end': 8683.193, 'src': 'embed', 'start': 8654.543, 'weight': 7, 'content': [{'end': 8662.349, 'text': "In order to go ahead and just have you ever worked or it's the first time you're preparing for an IT interview?", 'start': 8654.543, 'duration': 7.806}, {'end': 8666.112, 'text': "I'm first time preparing, yeah.", 'start': 8662.85, 'duration': 3.262}, {'end': 8668.534, 'text': 'Then just think in this manner.', 'start': 8666.773, 'duration': 1.761}, {'end': 8674.539, 'text': "You need to simply go ahead and think like interacting or I'll give you a scenario.", 'start': 8669.435, 'duration': 5.104}, {'end': 8678.402, 'text': "I have a company A, that's a big company.", 'start': 8675.079, 'duration': 3.323}, {'end': 8680.803, 'text': 'They took over one more company B.', 'start': 8678.602, 'duration': 2.201}, {'end': 8683.193, 'text': "Okay Okay, I'm just giving you an example.", 'start': 8680.803, 'duration': 2.39}], 'summary': 'First-time it interviewee advised to think in terms of company scenarios and acquisitions.', 'duration': 28.65, 'max_score': 8654.543, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI8654543.jpg'}, {'end': 8897.996, 'src': 'embed', 'start': 8871.14, 'weight': 6, 'content': [{'end': 8878.932, 'text': "And that's really nice that you're asking it, because, at the end of the day, what our motto is to make you equipped for the interview.", 'start': 8871.14, 'duration': 7.792}, {'end': 8880.713, 'text': 'only right? For the interview.', 'start': 8878.932, 'duration': 1.781}, {'end': 8885.333, 'text': "So that's our main goal from Edureka, from me.", 'start': 8881.073, 'duration': 4.26}, {'end': 8887.134, 'text': 'We are putting in efforts to do the same.', 'start': 8885.694, 'duration': 1.44}, {'end': 8890.234, 'text': "So that's why it's very good that if you are asking the question.", 'start': 8887.414, 'duration': 2.82}, {'end': 8897.996, 'text': 'In fact, in my batch, I love to take up the questions and I just make sure that nobody is sitting idle or nobody is sitting silent.', 'start': 8891.095, 'duration': 6.901}], 'summary': "Edureka's main goal is to equip candidates for interviews, ensuring active participation and engagement.", 'duration': 26.856, 'max_score': 8871.14, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI8871140.jpg'}, {'end': 8993.085, 'src': 'embed', 'start': 8966.198, 'weight': 5, 'content': [{'end': 8971.864, 'text': 'that once the first job will execute and then only the second will execute.', 'start': 8966.198, 'duration': 5.666}, {'end': 8976.447, 'text': "Then in the condition I'll give them In the second jobs condition.", 'start': 8972.345, 'duration': 4.102}, {'end': 8981.853, 'text': 'that first should be succeeded, then only the second should click at this desired time.', 'start': 8976.447, 'duration': 5.406}, {'end': 8984.356, 'text': 'So this is how we have in market.', 'start': 8981.853, 'duration': 2.503}, {'end': 8986.858, 'text': 'We have multiple tools that are available.', 'start': 8984.376, 'duration': 2.482}, {'end': 8988.82, 'text': "I'll again request you to go to YouTube.", 'start': 8986.858, 'duration': 1.962}, {'end': 8993.085, 'text': "It's a very good way to learn the things in a short span of time.", 'start': 8988.82, 'duration': 4.265}], 'summary': 'Multiple tools available in market for job execution, success required for second job to execute, recommended to learn from youtube.', 'duration': 26.887, 'max_score': 8966.198, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI8966198.jpg'}, {'end': 9091.595, 'src': 'embed', 'start': 9068.244, 'weight': 3, 'content': [{'end': 9078.611, 'text': 'Yeah Can we load only few records, like three records or five records using parameter file? Three records or five records using parameter file.', 'start': 9068.244, 'duration': 10.367}, {'end': 9081.213, 'text': "That is not, I didn't get you by that.", 'start': 9078.891, 'duration': 2.322}, {'end': 9086.712, 'text': "It means In the source you have 100 records, let's suppose, and in the target you want to load only three records right?", 'start': 9081.233, 'duration': 5.479}, {'end': 9088.673, 'text': 'Using parameter fill.', 'start': 9087.753, 'duration': 0.92}, {'end': 9089.334, 'text': 'can we do that?', 'start': 9088.673, 'duration': 0.661}, {'end': 9091.595, 'text': 'Using parameter yes, you can do that.', 'start': 9089.954, 'duration': 1.641}], 'summary': 'Using a parameter file, it is possible to load a specified number of records from source to target, e.g., 3 or 5 records.', 'duration': 23.351, 'max_score': 9068.244, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI9068244.jpg'}, {'end': 9375.824, 'src': 'embed', 'start': 9348.223, 'weight': 8, 'content': [{'end': 9353.168, 'text': "when you're going to execute it, you will say right click and execute advanced option.", 'start': 9348.223, 'duration': 4.945}, {'end': 9359.673, 'text': 'Once you will go to that, it will give you a pop-up that with which flow you want to go.', 'start': 9353.688, 'duration': 5.985}, {'end': 9367.481, 'text': 'So if you want to select go with the department ID 20 table, Then only that flow will execute, not the 31.', 'start': 9360.114, 'duration': 7.367}, {'end': 9370.362, 'text': 'And after that, the 30 will execute, not the 21.', 'start': 9367.481, 'duration': 2.881}, {'end': 9371.702, 'text': 'So it works like this.', 'start': 9370.362, 'duration': 1.34}, {'end': 9375.824, 'text': 'Let me explain you that.', 'start': 9372.383, 'duration': 3.441}], 'summary': 'To execute, right click and select flow by department id. works accordingly.', 'duration': 27.601, 'max_score': 9348.223, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI9348223.jpg'}], 'start': 7932.064, 'title': 'Informatica tools and data integration', 'summary': 'Covers informatica repository, unix usage, etl process, data integration, interview preparation, parameterization, data cleansing, and concurrent workflows, emphasizing key differences and functionalities for each tool and process.', 'chapters': [{'end': 8334.88, 'start': 7932.064, 'title': 'Informatica repository and service', 'summary': 'Discusses the concept of repositories, repository services, integration services, pmrep, pmcmd, versioning of mappings, and unix usage in informatica, highlighting key differences and functionalities.', 'duration': 402.816, 'highlights': ['A repository in Informatica is a segment of a database that stores metadata information such as source and target definitions, mapping details, and workflows. The repository stores metadata information, including source and target definitions, mapping details, and workflows.', 'The repository service is a service that facilitates the integration service or domain to connect to the repository, managing connections from client applications and updating metadata in the repository database tables. The repository service manages connections from client applications and updates metadata in the repository database tables.', 'The integration service in Informatica is an application service that runs workflows and sessions, directing the flow of data from source to target. The integration service runs workflows and sessions, directing the flow of data from source to target.', 'PMREP and PMCMD are commands used in Informatica, where PMCMD is used to start workflows and PMREP is used for tasks like connecting to a repository, taking backups, and managing repository objects. PMCMD is used to start workflows, while PMREP is used for tasks like connecting to a repository, taking backups, and managing repository objects.', 'Versioning of mappings in Informatica allows users to view the history of changes made to a mapping, including check-ins, check-outs, and comments. Versioning of mappings allows users to view the history of changes made, including check-ins, check-outs, and comments.']}, {'end': 8630.767, 'start': 8335.501, 'title': 'Unix environment and informatica folder structure', 'summary': 'Discusses the unix environment, the informatica folder structure for different environments, methods of accessing it, etl process from source to target, and the role of etl developers in data population and business logic application.', 'duration': 295.266, 'highlights': ['The chapter discusses the Unix environment, the Informatica folder structure for different environments, methods of accessing it, ETL process from source to target, and the role of ETL developers in data population and business logic application. The transcript covers the Unix environment, Informatica folder structure for different environments, methods of accessing it, ETL process from source to target, and the role of ETL developers.', 'Informatica folders are organized for dev, QA, and prod environments, with dedicated folders containing different parameter files, objects, and information. Informatica folders are organized for dev, QA, and prod environments, with dedicated folders containing different parameter files, objects, and information.', 'Two methods of accessing Informatica folders are through Putty and WinSCP, allowing for data population and access to the target database. Two methods of accessing Informatica folders are through Putty and WinSCP, allowing for data population and access to the target database.', 'ETL developers apply business rules and populate data from the staging area to the database, which serves as the source for reporting tools like QlikView, Cognos, and Tableau. ETL developers apply business rules and populate data from the staging area to the database, which serves as the source for reporting tools like QlikView, Cognos, and Tableau.', 'ETL developers are not involved in the reporting side and focus on populating data to the database, while a different set of developers are trained in the reporting areas. ETL developers are not involved in the reporting side and focus on populating data to the database, while a different set of developers are trained in the reporting areas.']}, {'end': 9067.984, 'start': 8630.767, 'title': 'Data integration process and interview preparation', 'summary': 'Discusses a data integration process involving merging data from two companies a and b, using a parallel ods and staging area, applying a column flag for source type, and populating data to the target database, and emphasizes the importance of unit testing in it interviews.', 'duration': 437.217, 'highlights': ['The process involves creating a parallel ODS and staging area for merging data from two companies A and B, followed by applying a column flag for source type, and populating data to the target database, with the emphasis on unit testing for data accuracy.', 'Utilizing third-party tools like Autosys and Control-M to schedule and execute interdependent jobs in IT systems, ensuring proper dependency conditions and desired timing for job execution.', 'Explaining the integration project as a method of merging data from companies A and B, emphasizing the use of FTP for receiving flat files and populating data to the RDBMS system, while stressing the importance of being well-equipped for IT interviews through interactive learning and preparation.']}, {'end': 9507.494, 'start': 9068.244, 'title': 'Informatica: parameterization, data cleansing, and concurrent workflows', 'summary': 'Discusses using parameter files to load a specific number of records, the use of informatica data quality for data cleansing, and the execution of concurrent workflows with different targets and mappings.', 'duration': 439.25, 'highlights': ['Using parameter file to load specific number of records In the source you have 100 records, and in the target, you want to load only three records using parameter file.', 'Informatica Data Quality for data cleansing Informatica Data Quality is available for data cleansing, with separate jobs and the ability to cleanse data by data profiling.', 'Execution of concurrent workflows with different targets and mappings Concurrent workflows allow for the execution of different flows with different targets, and the use of different targets with a single mapping.']}], 'duration': 1575.43, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/GYY7ns8oVhI/pics/GYY7ns8oVhI7932064.jpg', 'highlights': ['The repository service manages connections from client applications and updates metadata in the repository database tables.', 'The integration service runs workflows and sessions, directing the flow of data from source to target.', 'Versioning of mappings allows users to view the history of changes made, including check-ins, check-outs, and comments.', 'Informatica folders are organized for dev, QA, and prod environments, with dedicated folders containing different parameter files, objects, and information.', 'Two methods of accessing Informatica folders are through Putty and WinSCP, allowing for data population and access to the target database.', 'ETL developers apply business rules and populate data from the staging area to the database, which serves as the source for reporting tools like QlikView, Cognos, and Tableau.', 'The process involves creating a parallel ODS and staging area for merging data from two companies A and B, followed by applying a column flag for source type, and populating data to the target database, with the emphasis on unit testing for data accuracy.', 'Utilizing third-party tools like Autosys and Control-M to schedule and execute interdependent jobs in IT systems, ensuring proper dependency conditions and desired timing for job execution.', 'Using parameter file to load specific number of records In the source you have 100 records, and in the target, you want to load only three records using parameter file.', 'Informatica Data Quality is available for data cleansing, with separate jobs and the ability to cleanse data by data profiling.', 'Concurrent workflows allow for the execution of different flows with different targets, and the use of different targets with a single mapping.']}], 'highlights': ['Informatica holds 70% of the ETL tools market share.', "Informatica's revenue is expected to grow from 1.06 billion in 2015 to $10 billion in 2021.", 'Informatica jobs have an average salary of 21500, indicating high earning potential and a strong demand for developers.', 'The grid processing feature of Power Center allows workflows and sessions to run across multiple domain nodes, aiding in load balancing, high availability, and dynamic partitions.', 'Developers control the partitioning in the workflow, not administrators.', 'The different ways to perform parallel processing in Informatica include database partitioning, round robin partitioning, hash auto keys partitioning, hash user keys partitioning, and key range partitioning.', 'Active transformations can change the number of records passing through, while passive transformations do not alter the row count.', 'The usage of reusable transformations in real-time is mentioned to be around 15-20%, with a focus on mapping-specific transformations for achieving specific targets.', 'Types of cache in lookup transformation The discussion covers the various types of caches involved in lookup transformation, including static cache, dynamic cache, shared cache, persistent cache, and re-cache from source, with detailed explanations on their functionalities and impact on performance, providing a comprehensive understanding of cache usage in Informatica.', 'Creating an index on lookup columns can significantly enhance performance, especially when extracting data based on specific conditions.', 'The repository service manages connections from client applications and updates metadata in the repository database tables.', 'The integration service runs workflows and sessions, directing the flow of data from source to target.', 'ETL developers apply business rules and populate data from the staging area to the database, which serves as the source for reporting tools like QlikView, Cognos, and Tableau.', 'Utilizing third-party tools like Autosys and Control-M to schedule and execute interdependent jobs in IT systems, ensuring proper dependency conditions and desired timing for job execution.']}