title
Informatica Transformations with Examples | Informatica Tutorial | Informatica Training | Edureka

description
( Informatica Tutorial - https://www.edureka.co/informatica-certification-training ) This Edureka Informatica tutorial will help you in understanding the various Informatica Transformations with examples ( Informatica Transformation Blog: https://goo.gl/97BPpi ). You will begin by first understanding why we need transformations and what is a transformation. It will also then help you understand 5 commonly used transformations with different examples. Check our Informatica playlist here https://goo.gl/TmX6Fv. This video helps you to learn following topics : 1:26 Why do we need Transformation 5:10 What is Transformation 6:57 Types of Transformation in Informatica 12:26 Commonly used Transformation in Informatica 19:09 Source Qualifier Transformation 39:30 Joiner Transformation 59:30 Union Transformation 1:11:11 Expression Transformation 1:25:58 Normalizer Transformation 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 #InformaticaTransformations 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 Transformations with Examples | Informatica Tutorial | Informatica Training | Edureka', 'heatmap': [{'end': 653.505, 'start': 592.65, 'weight': 1}], 'summary': 'This informatica tutorial covers an overview of transformations, including 11 commonly used types, informatica power center processes, data integration transformations, joiner transformation, creating workflows, and expression and normalizer transformations, with practical demonstrations and use cases.', 'chapters': [{'end': 397.167, 'segs': [{'end': 74.77, 'src': 'embed', 'start': 15.955, 'weight': 0, 'content': [{'end': 22.337, 'text': "After that we'll look at what is a transformation followed by the various types of transformations that are present in Informatica.", 'start': 15.955, 'duration': 6.382}, {'end': 27.096, 'text': 'Now Informatica offers us 33 different types of transformations,', 'start': 23.393, 'duration': 3.703}, {'end': 31.179, 'text': "but we'll mainly be concentrating on five of the most commonly used transformations today.", 'start': 27.096, 'duration': 4.083}, {'end': 35.402, 'text': 'The first of those is the source qualified transformation,', 'start': 32.02, 'duration': 3.382}, {'end': 40.246, 'text': 'which is a basic transformation used to convert the data types to Informatica supported data types.', 'start': 35.402, 'duration': 4.844}, {'end': 43.489, 'text': 'After that we have the joiner and the union transformation.', 'start': 41.067, 'duration': 2.422}, {'end': 47.472, 'text': 'Now these transformations help you combine the data from various sources.', 'start': 44.169, 'duration': 3.303}, {'end': 50.194, 'text': 'Then we have the expression transformation.', 'start': 48.393, 'duration': 1.801}, {'end': 57.579, 'text': 'Now the expression transformation can be used to perform or calculate certain expressions which can be applied to each row.', 'start': 50.855, 'duration': 6.724}, {'end': 61.181, 'text': "Finally, we'll be looking at the normalizer transformation.", 'start': 58.66, 'duration': 2.521}, {'end': 65.284, 'text': 'This transformation helps us in converting the data to a normalized format.', 'start': 61.762, 'duration': 3.522}, {'end': 70.907, 'text': "So are we clear with today's agenda guys? So Matthew says he's clear.", 'start': 65.964, 'duration': 4.943}, {'end': 73.569, 'text': 'John says it looks promising.', 'start': 72.168, 'duration': 1.401}, {'end': 74.77, 'text': "That's good to hear John.", 'start': 73.829, 'duration': 0.941}], 'summary': 'Informatica offers 33 types of transformations, focusing on 5 commonly used ones: source qualified, joiner, union, expression, and normalizer.', 'duration': 58.815, 'max_score': 15.955, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o15955.jpg'}, {'end': 186.024, 'src': 'embed', 'start': 154.401, 'weight': 6, 'content': [{'end': 156.662, 'text': 'So this is where transformation comes into picture.', 'start': 154.401, 'duration': 2.261}, {'end': 162.024, 'text': 'Using transformations, you can convert the data in these various formats to a common format.', 'start': 157.222, 'duration': 4.802}, {'end': 166.566, 'text': 'Once you have the data into a common format, the process of analysis becomes easier.', 'start': 162.245, 'duration': 4.321}, {'end': 170.248, 'text': 'Are we clear with this guys? Okay, so John wants another example.', 'start': 166.846, 'duration': 3.402}, {'end': 175.255, 'text': "All right John, can I know which domain you are in presently? So you're from the manufacturing domain.", 'start': 170.973, 'duration': 4.282}, {'end': 177.056, 'text': "Okay, let's look at your domain itself.", 'start': 175.495, 'duration': 1.561}, {'end': 180.438, 'text': "Now John, let's say you cater to about 200 to 300 different vendors.", 'start': 177.957, 'duration': 2.481}, {'end': 186.024, 'text': 'Now each of these vendors may give their requirement in different formats.', 'start': 182.423, 'duration': 3.601}], 'summary': 'Using transformations, data from 200-300 vendors in manufacturing domain is converted to a common format for easier analysis.', 'duration': 31.623, 'max_score': 154.401, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o154401.jpg'}, {'end': 257.315, 'src': 'embed', 'start': 228.123, 'weight': 7, 'content': [{'end': 233.005, 'text': "Let's say you're processing various datas and you wish to add timestamp on when the data is being processed.", 'start': 228.123, 'duration': 4.882}, {'end': 235.266, 'text': 'You can do that as well using transformations.', 'start': 233.445, 'duration': 1.821}, {'end': 241.708, 'text': 'Now one of the major problems faced by all industries is that identification of error present in their data.', 'start': 235.966, 'duration': 5.742}, {'end': 247.351, 'text': "Now through transformations, you can identify if there's any error or any inconsistencies in your data.", 'start': 242.209, 'duration': 5.142}, {'end': 250.352, 'text': "Once you've identified this, it becomes easier for you to correct it.", 'start': 247.751, 'duration': 2.601}, {'end': 257.315, 'text': 'Now it may all look like magic to you, but trust me guys, at the end of the session, you will be able to do these operations by yourself.', 'start': 251.012, 'duration': 6.303}], 'summary': 'Using transformations, identify and correct errors in data; gain self-sufficiency in data operations.', 'duration': 29.192, 'max_score': 228.123, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o228123.jpg'}, {'end': 290.627, 'src': 'embed', 'start': 264.024, 'weight': 1, 'content': [{'end': 270.591, 'text': 'This choice in turn led to a lot of inconsistencies and when the time came to analyze this data you are facing a lot of troubles.', 'start': 264.024, 'duration': 6.567}, {'end': 277.477, 'text': 'Now through transformations you can convert this inconsistent and unstructured data to a structured and consistent format.', 'start': 271.311, 'duration': 6.166}, {'end': 281.137, 'text': "From here on, it's quite easier for you to analyze this data.", 'start': 278.134, 'duration': 3.003}, {'end': 284.16, 'text': 'Now Informatica mainly operates on structured data.', 'start': 281.638, 'duration': 2.522}, {'end': 290.627, 'text': 'However, if you do have an unstructured or a semi-structured data format, you can also transform that as per your requirements.', 'start': 284.501, 'duration': 6.126}], 'summary': 'Transform unstructured data to structured for easier analysis.', 'duration': 26.603, 'max_score': 264.024, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o264024.jpg'}, {'end': 326.163, 'src': 'embed', 'start': 301.929, 'weight': 8, 'content': [{'end': 310.014, 'text': "All right, so I assume you've all understood this, but then we all come across the question, what is a transformation? So let us look at that next.", 'start': 301.929, 'duration': 8.085}, {'end': 318.499, 'text': 'Now a transformation is basically used to represent the set of rules which define how the data is being transferred from the source to the target definition.', 'start': 310.934, 'duration': 7.565}, {'end': 326.163, 'text': "Now in these rules you'll define what data has to be transferred, the format of the data or let's say, you wish to have only certain data.", 'start': 319.179, 'duration': 6.984}], 'summary': 'A transformation defines rules for data transfer from source to target.', 'duration': 24.234, 'max_score': 301.929, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o301929.jpg'}, {'end': 388.581, 'src': 'embed', 'start': 356.939, 'weight': 9, 'content': [{'end': 361.621, 'text': "You may select only data that meets your condition or, let's say, you wish to normalize this data.", 'start': 356.939, 'duration': 4.682}, {'end': 364.702, 'text': 'you wish to convert an encoded data to a decoded format.', 'start': 361.621, 'duration': 3.081}, {'end': 366.203, 'text': 'all this can be done in this playground.', 'start': 364.702, 'duration': 1.501}, {'end': 372.266, 'text': "Once you've performed all the operations that you wish on this data, you can then go ahead and load it into a target data warehouse.", 'start': 366.563, 'duration': 5.703}, {'end': 374.687, 'text': 'Are we clear on what is a transformation?', 'start': 373.046, 'duration': 1.641}, {'end': 377.248, 'text': "So John says he's clear.", 'start': 375.347, 'duration': 1.901}, {'end': 378.048, 'text': "Matthew's also clear.", 'start': 377.248, 'duration': 0.8}, {'end': 382.216, 'text': 'So Jessica has a question here what are the common data formats??', 'start': 379.434, 'duration': 2.782}, {'end': 388.581, 'text': "Now, Jessica, the format of the data depends on what application that you're using to store this data.", 'start': 383.617, 'duration': 4.964}], 'summary': 'Playground allows data selection, normalization, encoding, and transformation before loading into a data warehouse.', 'duration': 31.642, 'max_score': 356.939, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o356939.jpg'}], 'start': 0.249, 'title': 'Data transformation overview', 'summary': 'Provides an overview of informatica transformations, including the need for transformations, types of transformations, and commonly used informatica transformations. it also discusses data transformation for multi-format data, addressing the challenge of analyzing data from different applications using various formats, and the solution of data transformation to convert data into a common format.', 'chapters': [{'end': 94.571, 'start': 0.249, 'title': 'Informatica transformations overview', 'summary': 'Provides an overview of informatica transformations, covering the need for transformations, types of transformations, and commonly used informatica transformations, including source qualified, joiner, union, expression, and normalizer transformations.', 'duration': 94.322, 'highlights': ['Informatica offers 33 types of transformations, but the session focuses on five commonly used transformations: source qualified, joiner, union, expression, and normalizer.', 'The source qualified transformation is used to convert data types to Informatica supported data types.', 'Joiner and union transformations assist in combining data from various sources.', 'Expression transformation enables the performance of calculations and expressions on each row of data.', 'The normalizer transformation aids in converting data to a normalized format.']}, {'end': 397.167, 'start': 95.191, 'title': 'Data transformation for multi-format data', 'summary': 'Discusses the challenge of analyzing data from different applications using various formats, and the solution of data transformation to convert data into a common format, enabling easier analysis. it also covers the operations that can be performed using transformations and the definition of a transformation.', 'duration': 301.976, 'highlights': ['Data transformation solves the challenge of analyzing data from different applications using various formats Data from different applications using various formats need to be validated and transformed into a common format for easier analysis.', 'Data transformation enables conversion of inconsistent and unstructured data to a structured and consistent format Transformation allows conversion of inconsistent and unstructured data to a structured and consistent format, facilitating easier analysis.', 'Transformation operations include decoding encoded data, adding timestamps, and identifying errors in data Transformation operations include decoding encoded data, adding timestamps, and identifying errors in data, enabling data correction and processing.', 'The definition of a transformation involves rules for data transfer, specifying data format and selection criteria A transformation involves rules for data transfer, specifying data format, selection criteria, and defining how data is transferred from source to target.', 'Data can be extracted from various sources, processed in the transformation playground, and loaded into a target data warehouse Data is extracted from various sources, processed in the transformation playground, and then loaded into a target data warehouse after performing required operations.']}], 'duration': 396.918, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o249.jpg', 'highlights': ['Informatica offers 33 types of transformations, but the session focuses on five commonly used transformations: source qualified, joiner, union, expression, and normalizer.', 'Data transformation enables conversion of inconsistent and unstructured data to a structured and consistent format, facilitating easier analysis.', 'The source qualified transformation is used to convert data types to Informatica supported data types.', 'Joiner and union transformations assist in combining data from various sources.', 'Expression transformation enables the performance of calculations and expressions on each row of data.', 'The normalizer transformation aids in converting data to a normalized format.', 'Data transformation solves the challenge of analyzing data from different applications using various formats.', 'Transformation operations include decoding encoded data, adding timestamps, and identifying errors in data, enabling data correction and processing.', 'The definition of a transformation involves rules for data transfer, specifying data format, selection criteria, and defining how data is transferred from source to target.', 'Data can be extracted from various sources, processed in the transformation playground, and loaded into a target data warehouse after performing required operations.']}, {'end': 1252.727, 'segs': [{'end': 444.709, 'src': 'embed', 'start': 417.535, 'weight': 0, 'content': [{'end': 424.099, 'text': 'Now when we look at the various types of transformations in Informatica, they can be broadly classified on the basis of two major factors.', 'start': 417.535, 'duration': 6.564}, {'end': 427.62, 'text': 'The first factor is based on their connectivity.', 'start': 425.119, 'duration': 2.501}, {'end': 429.922, 'text': 'When we talk about connectivity,', 'start': 428.121, 'duration': 1.801}, {'end': 435.604, 'text': 'it basically means we check if the transformation is either connected to at least another transformation or the target definition.', 'start': 429.922, 'duration': 5.682}, {'end': 438.626, 'text': 'So we have the connected as well as the unconnected.', 'start': 436.305, 'duration': 2.321}, {'end': 444.709, 'text': "If it is connected to another transformation, it's a connected transformation, but if it's not, it's an unconnected transformation.", 'start': 439.246, 'duration': 5.463}], 'summary': 'Informatica transformations can be broadly classified based on connectivity as connected or unconnected.', 'duration': 27.174, 'max_score': 417.535, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o417535.jpg'}, {'end': 653.505, 'src': 'heatmap', 'start': 592.65, 'weight': 1, 'content': [{'end': 599.998, 'text': 'Similarly, if you look at the unconnected transformation, here we have a pipeline, and the unconnected lookup is not part of this pipeline.', 'start': 592.65, 'duration': 7.348}, {'end': 604.643, 'text': 'A pipeline basically is the connection from the source through the transformations to the target.', 'start': 600.599, 'duration': 4.044}, {'end': 609.445, 'text': 'So as you can see, the unconnected lookup is not part of our pipeline.', 'start': 605.802, 'duration': 3.643}, {'end': 615.148, 'text': 'However, it is part of our mapping because it is being remotely called in the expression transformation.', 'start': 609.785, 'duration': 5.363}, {'end': 620.687, 'text': 'Are we clear on the two types based on their connectivity? Janice says yes.', 'start': 615.749, 'duration': 4.938}, {'end': 622.528, 'text': 'So Dave has a question here.', 'start': 621.247, 'duration': 1.281}, {'end': 626.592, 'text': "Why do we use unconnected transformations? So that's a really good question, Dave.", 'start': 622.728, 'duration': 3.864}, {'end': 631.656, 'text': 'Unconnected transformations are mainly used when we need specific data that meets a condition.', 'start': 626.992, 'duration': 4.664}, {'end': 635.419, 'text': "Let's say, while you're looking up the details of all the employees,", 'start': 632.316, 'duration': 3.103}, {'end': 639.983, 'text': 'you just wish to understand the salary of the employees who are working under a specific manager.', 'start': 635.419, 'duration': 4.564}, {'end': 647.029, 'text': 'So in that case, you can use the unconnected lookup transformation and extract the details of those employees under that manager.', 'start': 640.463, 'duration': 6.566}, {'end': 653.505, 'text': "Was that clear, Dave? All right, so now let's move ahead and look at the second category of transformations.", 'start': 647.509, 'duration': 5.996}], 'summary': 'Unconnected transformations are used for specific data extraction based on conditions.', 'duration': 60.855, 'max_score': 592.65, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o592650.jpg'}, {'end': 726.443, 'src': 'embed', 'start': 701.312, 'weight': 2, 'content': [{'end': 707.576, 'text': 'So coming back to your question, Matthew, does this answer your question? Why do we use passive transformations? All right.', 'start': 701.312, 'duration': 6.264}, {'end': 715.239, 'text': "Now to give you examples of active transformation, let's say the source qualifier transformation, the aggregator transformation,", 'start': 708.416, 'duration': 6.823}, {'end': 719.26, 'text': 'the expression transformations are some of the most widely used active transformation.', 'start': 715.239, 'duration': 4.021}, {'end': 721.641, 'text': 'So Dave wants me to repeat passive transformation.', 'start': 719.68, 'duration': 1.961}, {'end': 726.443, 'text': 'Now in a passive transformation, the number of rows that pass through it is constant.', 'start': 722.181, 'duration': 4.262}], 'summary': 'Active transformations include source qualifier, aggregator, and expression transformations, while passive transformation maintains a constant number of rows passing through it.', 'duration': 25.131, 'max_score': 701.312, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o701312.jpg'}, {'end': 771.758, 'src': 'embed', 'start': 742.782, 'weight': 1, 'content': [{'end': 744.563, 'text': 'Is it clear now, Dave? All right.', 'start': 742.782, 'duration': 1.781}, {'end': 750.848, 'text': 'So moving ahead, let us look at some of the commonly used transformations in Informatica.', 'start': 745.264, 'duration': 5.584}, {'end': 755.812, 'text': 'So here we have list of 11 transformations that are active and connected transformations.', 'start': 751.689, 'duration': 4.123}, {'end': 758.954, 'text': "Don't worry, we'll be looking at some of the passive transformations as well.", 'start': 756.092, 'duration': 2.862}, {'end': 762.537, 'text': "So we'll start off by first looking at the aggregator transformation.", 'start': 759.715, 'duration': 2.822}, {'end': 767.152, 'text': 'Now, the aggregator transformation is mainly used to perform aggregator functions.', 'start': 763.086, 'duration': 4.066}, {'end': 771.758, 'text': "Let's say, you wish to find the sum of the overall money that you need to pay.", 'start': 767.592, 'duration': 4.166}], 'summary': 'Informatica covers 11 active and connected transformations, including the aggregator function for summing money.', 'duration': 28.976, 'max_score': 742.782, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o742782.jpg'}], 'start': 398.348, 'title': 'Informatica transformations', 'summary': 'Discusses various types of transformations in informatica, such as connected and unconnected, active and passive transformations, covering 11 commonly used transformations and addressing audience questions.', 'chapters': [{'end': 647.029, 'start': 398.348, 'title': 'Types of informatica transformations', 'summary': 'Discusses the various types of transformations in informatica, including connected and unconnected transformations, active and passive transformations, and their usage in data processing, with examples and explanations, while addressing questions from the audience.', 'duration': 248.681, 'highlights': ['The chapter explains the classification of Informatica transformations based on connectivity and change in the number of rows, with examples and usage scenarios, addressing questions from the audience.', 'The instructor addresses questions about the use of passive transformations and the possibility of a transformation being both connected and active or passive, providing clear explanations and examples.', 'The explanation of connected and unconnected transformations in Informatica, with a focus on their usage and relevance in data processing, includes examples and clarifications addressing audience inquiries.', 'The instructor provides a detailed explanation of unconnected transformations, their usage in specific data retrieval scenarios, and their role in the mapping process, addressing questions from the audience.']}, {'end': 1252.727, 'start': 647.509, 'title': 'Transformations in informatica', 'summary': 'Explores active and passive transformations in informatica, covering 11 commonly used transformations such as aggregator, source qualifier, joiner, union, normalizer, rank, router, sorter, filter, transactional control, and update strategy transformations.', 'duration': 605.218, 'highlights': ['The chapter explores active and passive transformations in Informatica, covering 11 commonly used transformations such as aggregator, source qualifier, joiner, union, normalizer, rank, router, sorter, filter, transactional control, and update strategy transformations. It provides an overview of the types of transformations and their functionalities, including examples and use cases.', 'The source qualifier transformation is considered an active transformation as it allows defining how data is fetched from the source and can perform operations such as extracting distinct data and joining two tables using a common link. The source qualifier transformation allows defining SQL queries to fetch specific data and perform operations like extracting distinct values and joining tables, providing flexibility in data retrieval.', 'The aggregator transformation is used for performing aggregator functions such as finding the sum of overall money or the maximum value within a group. It is utilized to perform functions like finding the sum of money or the maximum value within a group, offering functionalities for data aggregation.']}], 'duration': 854.379, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o398348.jpg', 'highlights': ['The chapter explains the classification of Informatica transformations based on connectivity and change in the number of rows, with examples and usage scenarios, addressing questions from the audience.', 'The chapter explores active and passive transformations in Informatica, covering 11 commonly used transformations such as aggregator, source qualifier, joiner, union, normalizer, rank, router, sorter, filter, transactional control, and update strategy transformations. It provides an overview of the types of transformations and their functionalities, including examples and use cases.', 'The instructor addresses questions about the use of passive transformations and the possibility of a transformation being both connected and active or passive, providing clear explanations and examples.', 'The explanation of connected and unconnected transformations in Informatica, with a focus on their usage and relevance in data processing, includes examples and clarifications addressing audience inquiries.']}, {'end': 2253.624, 'segs': [{'end': 1319.154, 'src': 'embed', 'start': 1291.224, 'weight': 1, 'content': [{'end': 1293.965, 'text': "and it'll launch the Informatica Power Center Repository Manager.", 'start': 1291.224, 'duration': 2.741}, {'end': 1300.367, 'text': "Now, if you've had any troubles while installing Informatica Power Center or while configuring the Repository Manager,", 'start': 1294.285, 'duration': 6.082}, {'end': 1303.748, 'text': 'you can check out our blog Informatica installation in nine easy steps.', 'start': 1300.367, 'duration': 3.381}, {'end': 1309.01, 'text': 'So here select the repository that you have configured and click on the connect icon to connect to the repository.', 'start': 1304.009, 'duration': 5.001}, {'end': 1312.712, 'text': 'You will get a pop up asking for your username and password for the repository.', 'start': 1309.25, 'duration': 3.462}, {'end': 1315.953, 'text': 'So specify that and click on the option to connect to it.', 'start': 1313.192, 'duration': 2.761}, {'end': 1319.154, 'text': "So now we'll begin by creating a new work folder.", 'start': 1316.853, 'duration': 2.301}], 'summary': 'Informatica power center repository manager launched, new work folder created.', 'duration': 27.93, 'max_score': 1291.224, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1291224.jpg'}, {'end': 1371.92, 'src': 'embed', 'start': 1330.121, 'weight': 0, 'content': [{'end': 1334.022, 'text': "This comes in to help when you're working on various process using Informatica.", 'start': 1330.121, 'duration': 3.901}, {'end': 1338.944, 'text': 'Now to create a new work folder, go to the folders tab and select on the create option.', 'start': 1334.683, 'duration': 4.261}, {'end': 1343.348, 'text': 'Here you can specify the name of the work folder that you wish to set.', 'start': 1340.305, 'duration': 3.043}, {'end': 1349.954, 'text': 'Please make sure you do not make use of white spaces because Informatica does not support spaces in its naming convention.', 'start': 1343.768, 'duration': 6.186}, {'end': 1356.98, 'text': 'Click on OK to create the new work folder and now we can go ahead and begin with the designing process.', 'start': 1351.035, 'duration': 5.945}, {'end': 1364.608, 'text': 'Now to design the mapping we need to launch another product of Informatica Power Center that is the Informatica Power Center Designer.', 'start': 1357.581, 'duration': 7.027}, {'end': 1371.92, 'text': 'To do that, all you need to do is click on the D icon present here and automatically the Informatica Power Center designer will be launched.', 'start': 1365.336, 'duration': 6.584}], 'summary': 'Use informatica to create work folders and launch power center designer.', 'duration': 41.799, 'max_score': 1330.121, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1330121.jpg'}, {'end': 1414.218, 'src': 'embed', 'start': 1388.872, 'weight': 2, 'content': [{'end': 1394.896, 'text': 'my tables are present in a common database, so let me go ahead and show you how you can load the sources from a database.', 'start': 1388.872, 'duration': 6.024}, {'end': 1402.393, 'text': 'To do that make sure you are in the source analyzer workspace, click on the sources tab and select import from database option.', 'start': 1395.831, 'duration': 6.562}, {'end': 1407.055, 'text': 'Here you need to select the connection object to your database.', 'start': 1403.914, 'duration': 3.141}, {'end': 1414.218, 'text': 'Now if you have not configured the connection object, click on the dots and here you can go ahead and add the connection object.', 'start': 1407.475, 'duration': 6.743}], 'summary': 'Demonstrating how to load sources from a common database in the source analyzer workspace.', 'duration': 25.346, 'max_score': 1388.872, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1388872.jpg'}, {'end': 1540.015, 'src': 'embed', 'start': 1513.999, 'weight': 4, 'content': [{'end': 1520.068, 'text': "So as you can see, for each of the source definitions, there's a corresponding source qualified transformation that was automatically created.", 'start': 1513.999, 'duration': 6.069}, {'end': 1522.34, 'text': 'Now, I had mentioned to you earlier,', 'start': 1520.498, 'duration': 1.842}, {'end': 1529.726, 'text': 'the main objective of a source qualified transformation is to help you convert the source data type to the data type supported by Informatica.', 'start': 1522.34, 'duration': 7.386}, {'end': 1535.491, 'text': 'So if you see the source definition, we are making use of a number which has a precision and a scale set.', 'start': 1530.106, 'duration': 5.385}, {'end': 1540.015, 'text': 'But when it comes to an Informatica data type, it is being converted to a decimal value.', 'start': 1535.871, 'duration': 4.144}], 'summary': 'Automatically created source qualified transformation converts source data to informatica supported data type.', 'duration': 26.016, 'max_score': 1513.999, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1513999.jpg'}, {'end': 1612.455, 'src': 'embed', 'start': 1584.54, 'weight': 5, 'content': [{'end': 1590.364, 'text': 'One. you can manually create a target definition where you have to define each column, its data type and its precision,', 'start': 1584.54, 'duration': 5.824}, {'end': 1594.046, 'text': 'or you can model a target table on the basis of a transformation.', 'start': 1590.364, 'duration': 3.682}, {'end': 1600.03, 'text': "So here what I'm going to do is that I'm going to create a target definition on the basis of the source qualified transformation.", 'start': 1594.507, 'duration': 5.523}, {'end': 1606.693, 'text': 'To do that all you need to do is right click the source qualified transformation and click on the create and add target option.', 'start': 1600.21, 'duration': 6.483}, {'end': 1612.455, 'text': 'So you can see we have just created a target definition that is same as the source qualified transformation.', 'start': 1606.993, 'duration': 5.462}], 'summary': 'Target definition created based on source qualified transformation.', 'duration': 27.915, 'max_score': 1584.54, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1584540.jpg'}, {'end': 1745.01, 'src': 'embed', 'start': 1718.022, 'weight': 6, 'content': [{'end': 1724.89, 'text': "there has to be two department IDs present in the source qualifier because we're gonna use these two department IDs and join the two sources.", 'start': 1718.022, 'duration': 6.868}, {'end': 1726.331, 'text': "I'll show you how it's done.", 'start': 1725.43, 'duration': 0.901}, {'end': 1729.254, 'text': 'So just double click on the source qualifier transformation.', 'start': 1726.972, 'duration': 2.282}, {'end': 1734.403, 'text': "Now here, you need to specify the condition through which you're gonna join the department IDs.", 'start': 1729.98, 'duration': 4.423}, {'end': 1740.447, 'text': 'So go to the properties tab, and here inside the user defined join, just click on the arrow mark that is present.', 'start': 1734.663, 'duration': 5.784}, {'end': 1745.01, 'text': 'Now as you can see, we have two department IDs from the different tables.', 'start': 1741.267, 'duration': 3.743}], 'summary': 'Use two department ids to join sources in source qualifier transformation.', 'duration': 26.988, 'max_score': 1718.022, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1718022.jpg'}, {'end': 1896.504, 'src': 'embed', 'start': 1871.161, 'weight': 7, 'content': [{'end': 1878.107, 'text': 'Now a key feature that Informatica provides us is to validate if the SQL query that you have written is correct or not.', 'start': 1871.161, 'duration': 6.946}, {'end': 1881.21, 'text': 'You can compare this SQL query to your source data.', 'start': 1878.408, 'duration': 2.802}, {'end': 1886.094, 'text': 'To do that, what you need to do is select the corresponding source object,', 'start': 1881.65, 'duration': 4.444}, {'end': 1890.659, 'text': 'specify the username and password for the database and then click on Validate option.', 'start': 1886.094, 'duration': 4.565}, {'end': 1896.504, 'text': "So what you're doing is that you're executing the SQL query on the source data here.", 'start': 1891.659, 'duration': 4.845}], 'summary': 'Informatica validates sql queries by comparing them to source data.', 'duration': 25.343, 'max_score': 1871.161, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1871161.jpg'}, {'end': 1981.402, 'src': 'embed', 'start': 1956.319, 'weight': 8, 'content': [{'end': 1962.986, 'text': 'You can either manually create a workflow or you can create a workflow automatically using the generate workflow option present.', 'start': 1956.319, 'duration': 6.667}, {'end': 1972.74, 'text': "Now, in case, if you wish to make use of multiple mappings in your workflow, then it's suggested that you manually create this workflow Else,", 'start': 1963.967, 'duration': 8.773}, {'end': 1978.141, 'text': 'if you wish to create a workflow for a simple mapping, you can go ahead and create the automatic workflow.', 'start': 1972.74, 'duration': 5.401}, {'end': 1981.402, 'text': 'So right click on the workspace and select generate workflow option.', 'start': 1978.501, 'duration': 2.901}], 'summary': 'Workflow can be created manually or automatically, with multiple mappings done manually and simple mappings done automatically.', 'duration': 25.083, 'max_score': 1956.319, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1956319.jpg'}, {'end': 2046.287, 'src': 'embed', 'start': 2018.428, 'weight': 9, 'content': [{'end': 2022.629, 'text': 'At present we have just defined how the target table should be, so we need to create a target table.', 'start': 2018.428, 'duration': 4.201}, {'end': 2024.99, 'text': 'So go back to the target designer workspace.', 'start': 2023.169, 'duration': 1.821}, {'end': 2029.871, 'text': 'Here in the targets tab you can find the last option generate execute SQL.', 'start': 2025.61, 'duration': 4.261}, {'end': 2032.461, 'text': "So click on it and you'll get a new tab.", 'start': 2030.56, 'duration': 1.901}, {'end': 2037.743, 'text': 'Here, since you are gonna be creating a new table, make sure the create table option is checked.', 'start': 2032.901, 'duration': 4.842}, {'end': 2041.285, 'text': "Once you've set that, just click on generate and execute SQL.", 'start': 2038.083, 'duration': 3.202}, {'end': 2046.287, 'text': "Now you'll be prompted asking to select the connection object to your target database.", 'start': 2041.445, 'duration': 4.842}], 'summary': 'Create a target table by generating and executing sql in target designer workspace.', 'duration': 27.859, 'max_score': 2018.428, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o2018428.jpg'}, {'end': 2228.898, 'src': 'embed', 'start': 2200.516, 'weight': 10, 'content': [{'end': 2202.377, 'text': 'as you can see in the output, it is valid.', 'start': 2200.516, 'duration': 1.861}, {'end': 2208.874, 'text': 'So at times what happens is after you have created a workflow you may go back to your mapping and perform certain changes.', 'start': 2203.513, 'duration': 5.361}, {'end': 2212.735, 'text': 'So in that cases you may find an error with respect to the session properties.', 'start': 2209.214, 'duration': 3.521}, {'end': 2217.196, 'text': 'So you need to make sure you have saved it every time before you go ahead and execute the workflow.', 'start': 2213.255, 'duration': 3.941}, {'end': 2220.597, 'text': 'Now going ahead to execute the workflow there are two options.', 'start': 2217.656, 'duration': 2.941}, {'end': 2225.358, 'text': 'You can either go to the workflow tab and select start workflow option from here,', 'start': 2220.977, 'duration': 4.381}, {'end': 2228.898, 'text': 'or you can right click on the workspace and select start workflow option.', 'start': 2225.358, 'duration': 3.54}], 'summary': 'Ensure to save changes before executing workflow; two options to start workflow.', 'duration': 28.382, 'max_score': 2200.516, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o2200516.jpg'}, {'end': 2265.328, 'src': 'embed', 'start': 2235.825, 'weight': 11, 'content': [{'end': 2240.39, 'text': 'Now the workflow monitor helps you understand the progress of the workflow that you have designed.', 'start': 2235.825, 'duration': 4.565}, {'end': 2244.816, 'text': 'So you can see the corresponding workflow, its session, and its progress.', 'start': 2240.751, 'duration': 4.065}, {'end': 2253.624, 'text': 'Now if you wish to understand better how the workflow has been executed, just double click on the session icon, and you will get the run properties.', 'start': 2246.017, 'duration': 7.607}, {'end': 2258.786, 'text': 'Now here, if you wish to understand how many rows has been transferred from the source or the target,', 'start': 2254.305, 'duration': 4.481}, {'end': 2265.328, 'text': 'or if you wish to get a statistics with respect to source and target, just go to the source target statistics and here you can see the details.', 'start': 2258.786, 'duration': 6.542}], 'summary': 'Workflow monitor provides progress details including row transfer statistics.', 'duration': 29.503, 'max_score': 2235.825, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o2235825.jpg'}], 'start': 1252.927, 'title': 'Informatica power center processes', 'summary': 'Covers utilizing source qualifier transformation, mapping and target definition creation, and informatica processes, including creating workflows, validating sql queries, and executing workflows.', 'chapters': [{'end': 1490.077, 'start': 1252.927, 'title': 'Utilizing source qualifier transformation', 'summary': 'Discusses the process of creating a new work folder, connecting to the informatica power center repository manager, importing sources from a database, and designing a mapping using the informatica power center designer.', 'duration': 237.15, 'highlights': ['The process begins with creating a new work folder to store sources, targets, mapping, and workflow, aiding in managing various processes using Informatica. Creating a new work folder allows for organizing and storing all the sources, targets, mapping, and workflow in a single place, facilitating management of various processes using Informatica.', 'Connecting to the Informatica Power Center Repository Manager involves selecting the configured repository and specifying the username and password to connect. Connecting to the Informatica Power Center Repository Manager requires selecting the configured repository and providing the username and password to connect.', 'Importing sources from the database involves selecting the connection object, specifying the username and password, and loading the desired tables and views. Importing sources from the database includes selecting the connection object, specifying the username and password, and loading the desired tables and views from the database.', 'Designing a mapping using the Informatica Power Center Designer includes loading the sources, creating the mapping, and using the connection object to connect to the database. Designing a mapping using the Informatica Power Center Designer involves loading the sources, creating the mapping, and utilizing the connection object to connect to the database.']}, {'end': 1870.574, 'start': 1490.777, 'title': 'Mapping and target definition creation', 'summary': 'Covers the creation of source qualified transformations and target definitions, including the automatic creation of a source qualifier for each source, the conversion of data types, the deletion and selection of columns for a source qualifier, and the creation and editing of a target definition based on a source qualified transformation, with the additional explanation of joining tables and generating sql queries.', 'duration': 379.797, 'highlights': ['The source qualified transformation automatically creates a corresponding source qualifier for each source, aiding in the conversion of data types. The source qualified transformation automatically creates a corresponding source qualifier for each source, aiding in the conversion of data types to the data type supported by Informatica.', 'Explanation of the process of deleting the source qualifier for a specific table and selecting columns for a source qualifier. The process of deleting the source qualifier for a specific table and selecting columns for a source qualifier is explained, ensuring only the required columns are included in the source qualifier.', 'Demonstration of creating a target definition based on a source qualified transformation and the subsequent editing of the target definition. Demonstration of creating a target definition based on a source qualified transformation and the subsequent editing of the target definition to remove duplicate columns and apply naming conventions.', 'Process of joining tables using source qualifier transformations and generating SQL queries for the join condition. The process of joining tables using source qualifier transformations and generating SQL queries for the join condition is explained to illustrate the use of multiple department IDs for joining tables.']}, {'end': 2253.624, 'start': 1871.161, 'title': 'Informatica: validating sql query and creating workflows', 'summary': 'Discusses the process of validating sql queries against source data, setting up workflows, creating target tables, and executing workflows in informatica power center.', 'duration': 382.463, 'highlights': ["Informatica provides a feature to validate SQL queries against source data by specifying the source object, username, and password, and clicking on the 'Validate' option. This feature allows users to ensure the correctness of SQL queries by comparing them with source data, ensuring accuracy and data integrity.", 'Creating workflows in Informatica can be done manually or automatically, based on the complexity of mappings and the need for reusable sessions. Users can choose between manual and automatic workflow creation, considering the complexity of mappings and the requirement for reusable sessions, providing flexibility in workflow design.', 'Creating target tables involves specifying the table details, generating and executing SQL commands, and ensuring the correct connection object is used for reading and writing. The process of creating target tables includes specifying table details, executing SQL commands to create tables, and ensuring the correct connection objects are used for reading and writing, ensuring data consistency and accuracy.', 'Informatica checks the validity of workflows and alerts users about any errors or discrepancies in session properties before executing the workflow. Informatica automatically validates workflows, alerting users about any errors or discrepancies in session properties before execution, ensuring the smooth execution of workflows and minimizing errors.', 'The Informatica Power Center workflow monitor allows users to track the progress of workflows and understand the execution details by providing run properties. The workflow monitor in Informatica Power Center enables users to track the progress of workflows and gain insight into the execution details, facilitating effective workflow management and monitoring.']}], 'duration': 1000.697, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o1252927.jpg', 'highlights': ['Creating a new work folder to store sources, targets, mapping, and workflow for managing various processes using Informatica.', 'Connecting to the Informatica Power Center Repository Manager by selecting the configured repository and providing the username and password.', 'Importing sources from the database by selecting the connection object, specifying the username and password, and loading desired tables and views.', 'Designing a mapping using the Informatica Power Center Designer by loading sources, creating the mapping, and using the connection object to connect to the database.', 'Source qualified transformation automatically creates a corresponding source qualifier for each source, aiding in the conversion of data types to the data type supported by Informatica.', 'Demonstration of creating a target definition based on a source qualified transformation and subsequent editing of the target definition to remove duplicate columns and apply naming conventions.', 'Process of joining tables using source qualifier transformations and generating SQL queries for the join condition.', "Informatica provides a feature to validate SQL queries against source data by specifying the source object, username, and password, and clicking on the 'Validate' option.", 'Creating workflows in Informatica can be done manually or automatically, based on the complexity of mappings and the need for reusable sessions.', 'Creating target tables involves specifying the table details, generating and executing SQL commands, and ensuring the correct connection object is used for reading and writing.', 'Informatica checks the validity of workflows and alerts users about any errors or discrepancies in session properties before executing the workflow.', 'The Informatica Power Center workflow monitor allows users to track the progress of workflows and understand the execution details by providing run properties.']}, {'end': 3022.753, 'segs': [{'end': 2311.257, 'src': 'embed', 'start': 2270.549, 'weight': 0, 'content': [{'end': 2278.152, 'text': 'Now I have 106 rows present in my source on which all the 106 rows have been affected by the transformation.', 'start': 2270.549, 'duration': 7.603}, {'end': 2281.888, 'text': 'These rows then have gone to be stored in the target definition.', 'start': 2278.352, 'duration': 3.536}, {'end': 2284.711, 'text': 'So let me show you how these tables look in the target database.', 'start': 2282.169, 'duration': 2.542}, {'end': 2289.416, 'text': "So just launch the database application that you're using and check the tables.", 'start': 2285.232, 'duration': 4.184}, {'end': 2295.742, 'text': 'So here you can see, apart from the employee details that was already present,', 'start': 2291.237, 'duration': 4.505}, {'end': 2298.985, 'text': 'there are new columns that are the department name as well as the location ID.', 'start': 2295.742, 'duration': 3.243}, {'end': 2301.327, 'text': 'Let me also show you how the source table looks like.', 'start': 2299.445, 'duration': 1.882}, {'end': 2309.076, 'text': 'Now as you can see, when comparison to the source table, we have two new columns present in our target tables.', 'start': 2303.151, 'duration': 5.925}, {'end': 2311.257, 'text': 'That is the department name and the location ID.', 'start': 2309.336, 'duration': 1.921}], 'summary': '106 rows affected by transformation, new columns in target and source tables.', 'duration': 40.708, 'max_score': 2270.549, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o2270549.jpg'}, {'end': 2377.146, 'src': 'embed', 'start': 2349.784, 'weight': 1, 'content': [{'end': 2358.278, 'text': 'Any questions with respect to source qualifier transformation? So Janice says no, Ajay says no, Dave says no, Sandeep says no, all right.', 'start': 2349.784, 'duration': 8.494}, {'end': 2362.64, 'text': 'Now using the source qualifier, we have joined two tables that are present in the same database.', 'start': 2358.458, 'duration': 4.182}, {'end': 2370.103, 'text': "Let me show you how you can join two sources present in two different file formats, and you're gonna do this using the joiner transformation.", 'start': 2363.04, 'duration': 7.063}, {'end': 2377.146, 'text': 'Now in the joiner transformation, you can join only two sources, but they need to have at least one matching column present between them.', 'start': 2370.203, 'duration': 6.943}], 'summary': 'Demonstrated joining two tables from the same database and explained how to join sources in different file formats using the joiner transformation.', 'duration': 27.362, 'max_score': 2349.784, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o2349784.jpg'}, {'end': 2508.781, 'src': 'embed', 'start': 2481.701, 'weight': 4, 'content': [{'end': 2486.525, 'text': 'So using the joiner transformations, there are four types of join that we can process.', 'start': 2481.701, 'duration': 4.824}, {'end': 2488.806, 'text': 'Now the first type is a normal join.', 'start': 2487.045, 'duration': 1.761}, {'end': 2495.831, 'text': "So here what we're doing is that we're just selecting the common details that are present between the master source as well as the detail source.", 'start': 2489.206, 'duration': 6.625}, {'end': 2502.916, 'text': "So once you've specified the condition through which it is joined, only those rows that match this condition would be selected.", 'start': 2496.352, 'duration': 6.564}, {'end': 2508.781, 'text': "However, if you're using the master outer join, all the rows present in the detail source will be selected,", 'start': 2503.417, 'duration': 5.364}], 'summary': 'Using joiner transformations, four types of joins can be processed, including normal join and master outer join.', 'duration': 27.08, 'max_score': 2481.701, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o2481701.jpg'}, {'end': 2604.828, 'src': 'embed', 'start': 2575.622, 'weight': 2, 'content': [{'end': 2579.104, 'text': 'But now you wish to understand the complete details of the transaction.', 'start': 2575.622, 'duration': 3.482}, {'end': 2583.888, 'text': 'That is you wish to have the details of the customer and the complete details of the product that they have purchased.', 'start': 2579.244, 'duration': 4.644}, {'end': 2590.233, 'text': "So using a joiner transformation, we're going to join the details of the customer with the details of the product.", 'start': 2584.707, 'duration': 5.526}, {'end': 2591.274, 'text': "Let me show you how it's done.", 'start': 2590.313, 'duration': 0.961}, {'end': 2593.796, 'text': "Let's go back to the Informatica Power Center designer.", 'start': 2591.534, 'duration': 2.262}, {'end': 2596.059, 'text': "Here let's begin by creating a new mapping.", 'start': 2594.137, 'duration': 1.922}, {'end': 2598.942, 'text': 'So select on the mapping tab and click on create.', 'start': 2596.239, 'duration': 2.703}, {'end': 2604.828, 'text': "Now once you've created a new mapping, it's time we load our sources.", 'start': 2601.804, 'duration': 3.024}], 'summary': 'Using joiner transformation to merge customer and product details in informatica power center.', 'duration': 29.206, 'max_score': 2575.622, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o2575622.jpg'}], 'start': 2254.305, 'title': 'Data integration transformations', 'summary': 'Covers the use of source qualifier and joiner transformations in informatica, demonstrating joining tables from the same and different databases, affecting 106 rows and adding new columns to the target table. it also explains the four types of join in informatica using the joiner transformation, along with a use case example and detailed mapping creation steps.', 'chapters': [{'end': 2481.501, 'start': 2254.305, 'title': 'Transformations in data integration', 'summary': 'Discusses the use of source qualifier and joiner transformations in informatica, showcasing how to join tables from the same and different databases, with 106 rows affected by the transformation and new columns added to the target table.', 'duration': 227.196, 'highlights': ['The source table has 106 rows affected by the transformation, all of which have been stored in the target definition. 106 rows present in the source were affected by the transformation and transferred to the target definition.', "New columns 'department name' and 'location ID' have been added to the target table, in addition to the existing employee details. Apart from the existing employee details, new columns 'department name' and 'location ID' were added to the target table.", 'The joiner transformation allows for joining two sources with at least one matching column present between them, specifying the join condition to obtain the join result. The joiner transformation enables the joining of two sources with at least one matching column, specifying the join condition to obtain the join result.', 'Clarification provided on the requirement for at least one column to be common between tables, with the same name, data type, and precision. Clarification provided on the requirement for at least one column to be common between tables, with the same name, data type, and precision.', 'Demonstration of joining tables from two different sources, such as databases and files, using the joiner transformation. Demonstration of joining tables from two different sources using the joiner transformation, including tables from databases and files.']}, {'end': 3022.753, 'start': 2481.701, 'title': 'Joiner transformation in informatica', 'summary': 'Explains the four types of join in informatica using the joiner transformation, including normal join, master outer join, detail outer join, and full outer join, with a use case example and detailed steps for creating a mapping and specifying conditions for join.', 'duration': 541.052, 'highlights': ['The chapter explains the four types of join in Informatica: normal join, master outer join, detail outer join, and full outer join. The transcript explains the four types of join available in Informatica using the joiner transformation, including normal join, master outer join, detail outer join, and full outer join.', 'A use case example of joining customer details with product details in a retail organization is provided. The transcript provides a use case example of joining customer details with product details in a retail organization to understand the complete details of the transaction.', 'Step-by-step instructions for creating a new mapping, loading sources, and creating a joiner transformation are detailed. The transcript provides step-by-step instructions for creating a new mapping, loading sources, and creating a joiner transformation in Informatica Power Center designer.']}], 'duration': 768.448, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o2254305.jpg', 'highlights': ["New columns 'department name' and 'location ID' added to the target table, in addition to existing employee details.", 'Demonstration of joining tables from two different sources using the joiner transformation, including tables from databases and files.', 'Step-by-step instructions for creating a new mapping, loading sources, and creating a joiner transformation in Informatica Power Center designer.', 'The source table has 106 rows affected by the transformation, all of which have been stored in the target definition.', 'The chapter explains the four types of join in Informatica: normal join, master outer join, detail outer join, and full outer join.']}, {'end': 3454.857, 'segs': [{'end': 3102.286, 'src': 'embed', 'start': 3079.571, 'weight': 4, 'content': [{'end': 3086.934, 'text': 'Now the master table is cached for easier operations, so usually it is recommended that you use a table with less number of rows,', 'start': 3079.571, 'duration': 7.363}, {'end': 3088.115, 'text': "but again it's your choice.", 'start': 3086.934, 'duration': 1.181}, {'end': 3092.457, 'text': 'If you wish to set any table as master, you can change it by selecting it as master port.', 'start': 3088.175, 'duration': 4.282}, {'end': 3100.045, 'text': "Are you clear Sandeep? All right, so now let's move ahead and specify the condition through which we're gonna join these two tables.", 'start': 3093.338, 'duration': 6.707}, {'end': 3102.286, 'text': 'To do that, go to the condition tab.', 'start': 3100.525, 'duration': 1.761}], 'summary': 'Cache master table for easier operations, specify join condition in condition tab.', 'duration': 22.715, 'max_score': 3079.571, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o3079571.jpg'}, {'end': 3211.005, 'src': 'embed', 'start': 3172.104, 'weight': 0, 'content': [{'end': 3177.567, 'text': "but it's mainly used to translate the data from the original source type to Informatica data types.", 'start': 3172.104, 'duration': 5.463}, {'end': 3184.831, 'text': "The joiner transformation helps you join the data present in either the same database or, if it's present in different database,", 'start': 3178.666, 'duration': 6.165}, {'end': 3190.415, 'text': "if it's present in different files, if you have one in a source, if you have one in a file and the second in a database.", 'start': 3184.831, 'duration': 5.584}, {'end': 3193.258, 'text': 'So using a joiner transformation, you can join these two sources.', 'start': 3190.736, 'duration': 2.522}, {'end': 3196.821, 'text': 'Are you clear, Dave? All right.', 'start': 3194.499, 'duration': 2.322}, {'end': 3204.282, 'text': 'So, Dave, the difference between a source qualifier and a joiner transformation is that using a source qualifier transformations,', 'start': 3197.6, 'duration': 6.682}, {'end': 3211.005, 'text': 'you can join two tables that are present in the same source, but you need to make sure they have a relationship present between these two sources.', 'start': 3204.282, 'duration': 6.723}], 'summary': 'Informatica translates data types; joiner joins data from same or different sources.', 'duration': 38.901, 'max_score': 3172.104, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o3172104.jpg'}, {'end': 3403.372, 'src': 'embed', 'start': 3381.247, 'weight': 3, 'content': [{'end': 3390.111, 'text': 'one change that you need to make if your customer table is not present in the default directory is that you need to specify the file directory in which the customer file is present.', 'start': 3381.247, 'duration': 8.864}, {'end': 3396.405, 'text': "So make sure you specify the right path, because if you've not, Informatica cannot load the details from this file.", 'start': 3390.919, 'duration': 5.486}, {'end': 3403.372, 'text': 'Similarly, if you are creating a flat file as an output, in the target properties, there are two things that you have to change.', 'start': 3397.145, 'duration': 6.227}], 'summary': 'Specify correct file directory for customer table. adjust target properties for flat file output.', 'duration': 22.125, 'max_score': 3381.247, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o3381247.jpg'}, {'end': 3469.607, 'src': 'embed', 'start': 3437.429, 'weight': 2, 'content': [{'end': 3440.21, 'text': 'Right click on the workspace and select start workflow option.', 'start': 3437.429, 'duration': 2.781}, {'end': 3447.572, 'text': 'So here you can see the workflow has been successfully executed and if you go into the run properties of the session icon,', 'start': 3440.888, 'duration': 6.684}, {'end': 3454.857, 'text': 'you can see we had 500 rows present in our customer table and then we had 150 present in our products table.', 'start': 3447.572, 'duration': 7.285}, {'end': 3461.822, 'text': 'In our final table we have only 500 where we have all the details of the customer along with the corresponding details of the product.', 'start': 3455.478, 'duration': 6.344}, {'end': 3464.023, 'text': 'Let me show you how the product file looks like.', 'start': 3462.242, 'duration': 1.781}, {'end': 3469.607, 'text': 'Now again Informatica by default creates the target file in the target files directory present inside.', 'start': 3464.664, 'duration': 4.943}], 'summary': 'Workflow executed successfully, 500 customer rows, 150 product rows, resulting in 500 combined rows.', 'duration': 32.178, 'max_score': 3437.429, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o3437429.jpg'}], 'start': 3023.055, 'title': 'Joiner transformation in informatica and creating workflow', 'summary': 'Explains the use of master and detailed ports in a joiner transformation, specifying conditions for joining tables, and the difference between joiner and source qualifier transformations in informatica. it also covers the process of creating a workflow in informatica, including specifying conditions for joining tables, generating workflow, setting file paths, and executing the workflow, with a demonstration of 500 rows in the customer table and 150 rows in the products table.', 'chapters': [{'end': 3230.511, 'start': 3023.055, 'title': 'Joiner transformation in informatica', 'summary': 'Explains the use of master and detailed ports in a joiner transformation, specifying conditions for joining tables, and the difference between joiner and source qualifier transformations in informatica.', 'duration': 207.456, 'highlights': ['The master port denotes that the table from which this port is coming is the master table, cached for easier operations, recommended for use with a table with less number of rows. The master port is used to indicate the master table and is recommended for tables with fewer rows for easier operations.', 'Conditions for joining tables can be specified in the joiner transformation, allowing the use of multiple conditions to extract specific data, ensuring corresponding matching columns in both tables. Joiner transformation allows specifying conditions for joining tables and using multiple conditions to extract specific data with corresponding matching columns.', 'Source qualifier transformation is used to join two tables present in the same database and translate original source type to Informatica data types, while joiner transformation is used to join data present in either the same or different databases and files. Source qualifier transformation is used to join tables in the same database and translate source types, while joiner transformation joins data from different databases and files.']}, {'end': 3454.857, 'start': 3232.472, 'title': 'Creating workflow in informatica', 'summary': 'Covers the process of creating a workflow in informatica, including specifying conditions for joining tables, generating workflow, setting file paths, and executing the workflow, with a demonstration of 500 rows in the customer table and 150 rows in the products table.', 'duration': 222.385, 'highlights': ['The chapter covers the process of creating a workflow in Informatica, including specifying conditions for joining tables, generating workflow, setting file paths, and executing the workflow.', 'The workflow execution demonstrated 500 rows present in the customer table and 150 rows present in the products table.', 'Instructions are provided for specifying file paths for both source and target files, ensuring that the correct path is specified to enable Informatica to load the required details.']}], 'duration': 431.802, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o3023055.jpg', 'highlights': ['Joiner transformation specifies conditions for joining tables and using multiple conditions to extract specific data with corresponding matching columns.', 'Source qualifier transformation is used to join tables in the same database and translate source types, while joiner transformation joins data from different databases and files.', 'The workflow execution demonstrated 500 rows present in the customer table and 150 rows present in the products table.', 'Instructions are provided for specifying file paths for both source and target files, ensuring that the correct path is specified to enable Informatica to load the required details.', 'The master port denotes that the table from which this port is coming is the master table, cached for easier operations, recommended for use with a table with less number of rows.']}, {'end': 4511.703, 'segs': [{'end': 3481.512, 'src': 'embed', 'start': 3455.478, 'weight': 0, 'content': [{'end': 3461.822, 'text': 'In our final table we have only 500 where we have all the details of the customer along with the corresponding details of the product.', 'start': 3455.478, 'duration': 6.344}, {'end': 3464.023, 'text': 'Let me show you how the product file looks like.', 'start': 3462.242, 'duration': 1.781}, {'end': 3469.607, 'text': 'Now again Informatica by default creates the target file in the target files directory present inside.', 'start': 3464.664, 'duration': 4.943}, {'end': 3473.208, 'text': 'So here once you go inside, you can see the target file is present here.', 'start': 3470.066, 'duration': 3.142}, {'end': 3481.512, 'text': 'So you can see, here we have the details of the customer and then we have the corresponding product that they have purchased, the name of the product,', 'start': 3474.068, 'duration': 7.444}], 'summary': 'The final table contains 500 customer details and corresponding product information.', 'duration': 26.034, 'max_score': 3455.478, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o3455478.jpg'}, {'end': 4127.929, 'src': 'embed', 'start': 4102.943, 'weight': 5, 'content': [{'end': 4108.224, 'text': 'Now the final step of completing the mapping is the linking of union transformation to the target definition.', 'start': 4102.943, 'duration': 5.281}, {'end': 4112.005, 'text': 'So just right click on the workspace and select auto link option.', 'start': 4108.644, 'duration': 3.361}, {'end': 4115.486, 'text': 'Here you can see we have multiple transformations.', 'start': 4112.685, 'duration': 2.801}, {'end': 4119.227, 'text': 'So inside the union transformation, make sure you have selected the output folder.', 'start': 4115.746, 'duration': 3.481}, {'end': 4124.328, 'text': "So once you've selected that, click on apply, click on okay, and save the mapping.", 'start': 4119.727, 'duration': 4.601}, {'end': 4126.828, 'text': "So let's create a workflow for this.", 'start': 4125.328, 'duration': 1.5}, {'end': 4127.929, 'text': 'Right click on the mapping.', 'start': 4126.948, 'duration': 0.981}], 'summary': 'Complete the mapping by linking union transformation to target definition and creating a workflow.', 'duration': 24.986, 'max_score': 4102.943, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o4102943.jpg'}, {'end': 4238.743, 'src': 'embed', 'start': 4209.418, 'weight': 3, 'content': [{'end': 4212.5, 'text': 'So coming back, all right.', 'start': 4209.418, 'duration': 3.082}, {'end': 4218.377, 'text': 'Now to summarize, using the union transformations, we have just seen how you can join multiple sources,', 'start': 4213.015, 'duration': 5.362}, {'end': 4222.738, 'text': 'but they need to have the matching ports with the same data type and corresponding precision.', 'start': 4218.377, 'duration': 4.361}, {'end': 4225.559, 'text': 'Also, it does not remove duplicate rows.', 'start': 4223.618, 'duration': 1.941}, {'end': 4231.341, 'text': 'So, if you wish, you can check if there is any duplicate rows present in it, but if you wish to remove it,', 'start': 4225.819, 'duration': 5.522}, {'end': 4234.001, 'text': 'you need to add another transformation which will remove it for you.', 'start': 4231.341, 'duration': 2.66}, {'end': 4238.743, 'text': 'And finally, you can create multiple input groups, but you have only one output group.', 'start': 4234.522, 'duration': 4.221}], 'summary': 'Union transformation joins multiple sources with matching ports, data type, and precision, does not remove duplicate rows, requires additional transformation for removal, and allows multiple input groups but only one output group.', 'duration': 29.325, 'max_score': 4209.418, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o4209418.jpg'}, {'end': 4302.56, 'src': 'embed', 'start': 4269.991, 'weight': 4, 'content': [{'end': 4271.772, 'text': 'This is the expression transformation.', 'start': 4269.991, 'duration': 1.781}, {'end': 4279.361, 'text': "Now, as I've said, you use expression to perform row wise calculation and compute certain expression formulas.", 'start': 4273.615, 'duration': 5.746}, {'end': 4286.327, 'text': 'So one thing to be kept in mind is that the overall number of rows that pass through the expression transformation is the same,', 'start': 4280.242, 'duration': 6.085}, {'end': 4287.868, 'text': 'but the number of columns may vary.', 'start': 4286.327, 'duration': 1.541}, {'end': 4295.614, 'text': "So here, if you look at the image to your right, what we're trying to do here is that we're concatenating the first name and the last name,", 'start': 4288.369, 'duration': 7.245}, {'end': 4302.56, 'text': "and then we're creating a new column in which these two have been concatenated and we have single field for the employee name.", 'start': 4295.614, 'duration': 6.946}], 'summary': 'Expression transformation concatenates first and last names to create a new column for employee names.', 'duration': 32.569, 'max_score': 4269.991, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o4269991.jpg'}], 'start': 3455.478, 'title': 'Joining customer and product details and union and expression transformations in informatica', 'summary': 'Demonstrates successful joining of 500 customer and product records in informatica, resulting in a target file. it covers joiner, union, and expression transformations, and provides a step-by-step guide for creating a mapping using union transformation.', 'chapters': [{'end': 3490.797, 'start': 3455.478, 'title': 'Joining customer and product details', 'summary': 'Demonstrates the successful joining of customer details with corresponding product details in a final table, containing 500 records, through informatica, resulting in a target file created in the target files directory.', 'duration': 35.319, 'highlights': ['The chapter demonstrates the successful joining of customer details with corresponding product details in a final table, containing 500 records, through Informatica, resulting in a target file created in the target files directory.', 'The final table contains 500 records with all the customer details and corresponding product details, including the name of the product, product company, and other product details.', 'Informatica creates the target file in the target files directory by default, containing the joined details of the customer and the product they have purchased.']}, {'end': 4511.703, 'start': 3491.637, 'title': 'Union and expression transformations in informatica', 'summary': 'Covers the joiner transformation, union transformation, and expression transformation in informatica. it discusses how to join multiple sources using joiner and union transformations, and the use of expression transformation for row-wise operations and conditional statements. it also includes a step-by-step guide on creating a mapping using union transformation.', 'duration': 1020.066, 'highlights': ['The union transformation allows joining multiple sources with matching ports having the same data type and precision, without removing duplicate rows, and with only one output group defined by Informatica. The union transformation joins multiple sources with matching ports having the same data type and precision, without removing duplicate rows, and with only one output group defined by Informatica.', 'The expression transformation is used for row-wise operations and conditional statements, with the number of rows remaining constant while the number of columns may vary, and it offers the use of variable ports to store temporary values and simplify complex operations. The expression transformation is used for row-wise operations and conditional statements, with the number of rows remaining constant while the number of columns may vary. It also offers the use of variable ports to store temporary values and simplify complex operations.', 'The step-by-step guide demonstrates creating a mapping using the union transformation, including loading source files, creating a union transformation with corresponding ports, and linking the union transformation to the target definition. The step-by-step guide demonstrates creating a mapping using the union transformation, including loading source files, creating a union transformation with corresponding ports, and linking the union transformation to the target definition.']}], 'duration': 1056.225, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o3455478.jpg', 'highlights': ['The chapter demonstrates the successful joining of customer details with corresponding product details in a final table, containing 500 records, through Informatica, resulting in a target file created in the target files directory.', 'The final table contains 500 records with all the customer details and corresponding product details, including the name of the product, product company, and other product details.', 'Informatica creates the target file in the target files directory by default, containing the joined details of the customer and the product they have purchased.', 'The union transformation allows joining multiple sources with matching ports having the same data type and precision, without removing duplicate rows, and with only one output group defined by Informatica.', 'The expression transformation is used for row-wise operations and conditional statements, with the number of rows remaining constant while the number of columns may vary. It also offers the use of variable ports to store temporary values and simplify complex operations.', 'The step-by-step guide demonstrates creating a mapping using the union transformation, including loading source files, creating a union transformation with corresponding ports, and linking the union transformation to the target definition.']}, {'end': 5123.375, 'segs': [{'end': 4581.021, 'src': 'embed', 'start': 4555.368, 'weight': 3, 'content': [{'end': 4562.57, 'text': 'Now before I go ahead and I show you how you can identify inconsistencies, let me show you a simple use of the expression transformation.', 'start': 4555.368, 'duration': 7.202}, {'end': 4566.231, 'text': "I'll show you how you can concatenate the first name and the last name.", 'start': 4563.27, 'duration': 2.961}, {'end': 4569.071, 'text': 'So first begin by adding a new port.', 'start': 4567.148, 'duration': 1.923}, {'end': 4571.575, 'text': "Let's say name.", 'start': 4570.814, 'duration': 0.761}, {'end': 4578.185, 'text': 'Make sure the precision is greater than the combination of both of them since we are combining them.', 'start': 4573.358, 'duration': 4.827}, {'end': 4581.021, 'text': "I'll set it as 30.", 'start': 4579.187, 'duration': 1.834}], 'summary': 'Demonstrating how to concatenate first and last name in expression transformation.', 'duration': 25.653, 'max_score': 4555.368, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o4555368.jpg'}, {'end': 4690.322, 'src': 'embed', 'start': 4665.666, 'weight': 0, 'content': [{'end': 4672.891, 'text': "All right, so now it's time we create the expression through which we'll identify the inconsistency present in the data.", 'start': 4665.666, 'duration': 7.225}, {'end': 4677.374, 'text': "To do this, let's add a new column and let's call it inconsistency flag.", 'start': 4673.171, 'duration': 4.203}, {'end': 4684.539, 'text': "So here what I'm going to do is that I'm going to create a flag that will help me identify which row has some inconsistencies.", 'start': 4678.074, 'duration': 6.465}, {'end': 4690.322, 'text': "Once I've identified this, I can directly contact my employees and then update the required data.", 'start': 4685.039, 'duration': 5.283}], 'summary': 'Create inconsistency flag to identify data inconsistencies and update employees', 'duration': 24.656, 'max_score': 4665.666, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o4665666.jpg'}, {'end': 5103.474, 'src': 'embed', 'start': 5031.127, 'weight': 1, 'content': [{'end': 5038.989, 'text': "Here if you want you can check the session properties and make sure you're using the correct connection object.", 'start': 5031.127, 'duration': 7.862}, {'end': 5044.27, 'text': "Save the workflow and it's time we execute the workflow.", 'start': 5041.729, 'duration': 2.541}, {'end': 5054.112, 'text': 'So you can see we have successfully executed the workflow.', 'start': 5051.771, 'duration': 2.341}, {'end': 5058.673, 'text': 'Double click on it and you can see we had 107 rows present in the source data.', 'start': 5054.412, 'duration': 4.261}, {'end': 5062.891, 'text': 'and 107 have been transferred to the target table.', 'start': 5060.769, 'duration': 2.122}, {'end': 5069.417, 'text': "So it's time we check whether the concatenation operation and identification of inconsistencies has been done.", 'start': 5063.492, 'duration': 5.925}, {'end': 5076.624, 'text': 'So go into your target database and here check the details stored inside the target table.', 'start': 5069.938, 'duration': 6.686}, {'end': 5100.871, 'text': 'So you can see here the name field has been concatenated, the first name and the last name has been concatenated with the space between them,', 'start': 5093.243, 'duration': 7.628}, {'end': 5103.474, 'text': 'and also an inconsistency flag has been set.', 'start': 5100.871, 'duration': 2.603}], 'summary': 'Successfully executed workflow with 107 rows transferred, and concatenated names with inconsistency flag set.', 'duration': 72.347, 'max_score': 5031.127, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o5031127.jpg'}], 'start': 4512.663, 'title': 'Expression transformations in informatica', 'summary': 'Covers creating expression transformations for data validation, including concatenating names, identifying inconsistencies, and flagging 16 records for updating.', 'chapters': [{'end': 4706.543, 'start': 4512.663, 'title': 'Expression transformation in mapping designer', 'summary': 'Covers creating an expression transformation, including concatenating first name and last name, and identifying inconsistencies in the data by creating a flag for the same.', 'duration': 193.88, 'highlights': ['Creating an expression to concatenate the first name and last name Demonstrates the process of creating an expression to concatenate the first name and last name, ensuring the precision is set to 30 to accommodate the combination, and unchecking the input and output options for the individual names.', 'Creating a flag to identify inconsistencies in the data Details the process of creating an inconsistency flag to identify rows with data inconsistencies, which will facilitate direct communication with employees for necessary data updates and specifies the precision of the flag as five.']}, {'end': 5123.375, 'start': 4707.864, 'title': 'Expression transformation for data validation', 'summary': 'Explains the process of creating an expression transformation in informatica to check for null values in specific columns, trim white spaces, concatenate names, and identify inconsistencies, resulting in 16 records with inconsistencies flagged for updating.', 'duration': 415.511, 'highlights': ['Creating an expression using if and is null operators to check for null values in specified columns The process involves using the if operator to check conditions and the is null operator to directly check if the column value is equal to null.', 'Refining the expression to handle white spaces and identifying inconsistencies The transcript explains the process of removing white spaces using ltrim and rtrim operators, then checking if the values are equal to null, to identify inconsistencies in the data.', 'Concatenating first name and last name, and setting an inconsistency flag for records with inconsistencies The explanation involves concatenating the first name and last name, storing it as a single field, and setting an inconsistency flag for records with inconsistencies.', 'Execution and validation of the workflow resulting in 107 rows transferred and 16 records with inconsistencies identified The workflow successfully transfers 107 rows to the target table, with 16 records identified as having inconsistencies, which need to be updated.']}], 'duration': 610.712, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o4512663.jpg', 'highlights': ['Creating a flag to identify inconsistencies in the data Details the process of creating an inconsistency flag to identify rows with data inconsistencies, which will facilitate direct communication with employees for necessary data updates and specifies the precision of the flag as five.', 'Concatenating first name and last name, and setting an inconsistency flag for records with inconsistencies The explanation involves concatenating the first name and last name, storing it as a single field, and setting an inconsistency flag for records with inconsistencies.', 'Execution and validation of the workflow resulting in 107 rows transferred and 16 records with inconsistencies identified The workflow successfully transfers 107 rows to the target table, with 16 records identified as having inconsistencies, which need to be updated', 'Creating an expression to concatenate the first name and last name Demonstrates the process of creating an expression to concatenate the first name and last name, ensuring the precision is set to 30 to accommodate the combination, and unchecking the input and output options for the individual names.']}, {'end': 5918.911, 'segs': [{'end': 5150.316, 'src': 'embed', 'start': 5125.256, 'weight': 2, 'content': [{'end': 5130.279, 'text': "Now to summarize, using the expression transformation, you can perform row level calculations as we've seen.", 'start': 5125.256, 'duration': 5.023}, {'end': 5133.661, 'text': 'You can also modify individual columns that are present in the row.', 'start': 5130.299, 'duration': 3.362}, {'end': 5140.365, 'text': "So I've shown you how you can create a new column that has the name, which is a concatenation of the first name and the last name.", 'start': 5133.961, 'duration': 6.404}, {'end': 5150.316, 'text': 'So any questions with respect to the expression transformation? So Sandeep says no, John says no, Matthew says no, Dave says no.', 'start': 5140.785, 'duration': 9.531}], 'summary': 'Expression transformation allows row-level calculations and column modifications, such as creating a new column with a concatenation of first and last names.', 'duration': 25.06, 'max_score': 5125.256, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o5125256.jpg'}, {'end': 5188.051, 'src': 'embed', 'start': 5158.281, 'weight': 0, 'content': [{'end': 5163.485, 'text': 'Now the normalizer transformation, as the name suggests, helps you in converting the data to a normalized format.', 'start': 5158.281, 'duration': 5.204}, {'end': 5169.229, 'text': 'Now when I say a normalized format, as I had given you an example earlier,', 'start': 5164.946, 'duration': 4.283}, {'end': 5174.012, 'text': "let's say you have a customer details where the customer has given us three addresses,", 'start': 5169.229, 'duration': 4.783}, {'end': 5178.59, 'text': 'so you can create a row with the details of the customer where each address is unique.', 'start': 5174.012, 'duration': 4.578}, {'end': 5180.81, 'text': 'Similarly, if you look at the image here,', 'start': 5179.15, 'duration': 1.66}, {'end': 5188.051, 'text': "we have four occurrences of the weekly sales and we'll have each row with one corresponding value for the weekly sales once you've normalized this.", 'start': 5180.81, 'duration': 7.241}], 'summary': 'Normalizer transformation converts data to a normalized format, e.g., creating unique rows for multiple addresses or values.', 'duration': 29.77, 'max_score': 5158.281, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o5158281.jpg'}, {'end': 5252.571, 'src': 'embed', 'start': 5215.124, 'weight': 1, 'content': [{'end': 5221.868, 'text': 'Now, by default, if a source qualifier is created for a COBOL file, then this is also a normalizer transformation.', 'start': 5215.124, 'duration': 6.744}, {'end': 5227.812, 'text': 'So Informatica automatically creates a normalizer transformation as a source qualifier for a COBOL source file.', 'start': 5222.208, 'duration': 5.604}, {'end': 5231.754, 'text': "So remember that when you're going for an interview, it is something that is oftenly asked.", 'start': 5228.472, 'duration': 3.282}, {'end': 5242.344, 'text': 'So any questions about the normalizer transformation? Matthew says no, Ajay says no, John says no, Dave says clear, all right.', 'start': 5232.415, 'duration': 9.929}, {'end': 5247.928, 'text': "So now let's move ahead and look at an additional feature that is provided to us through the normalizer transformation.", 'start': 5242.984, 'duration': 4.944}, {'end': 5252.571, 'text': 'So this is the normalizer generated key and generated column ID.', 'start': 5248.688, 'duration': 3.883}], 'summary': 'Informatica creates normalizer transformation as source qualifier for cobol file. remembered for interviews. normalizer has generated key and column id.', 'duration': 37.447, 'max_score': 5215.124, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o5215124.jpg'}, {'end': 5301.159, 'src': 'embed', 'start': 5272.025, 'weight': 4, 'content': [{'end': 5279.172, 'text': "So let's say if you restart a workflow the second time, the generated key value will start from 101 instead of 1.", 'start': 5272.025, 'duration': 7.147}, {'end': 5284.136, 'text': 'This also helps us to set that the generated key be a primary key value in the target table.', 'start': 5279.172, 'duration': 4.964}, {'end': 5291.163, 'text': "If there's no primary key already present in the target table, then you can make use of the generated key to be as the primary key for that table.", 'start': 5284.297, 'duration': 6.866}, {'end': 5293.957, 'text': 'After that we have the generated column ID.', 'start': 5292.156, 'duration': 1.801}, {'end': 5301.159, 'text': 'Now the use of the generated column ID is just to help us understand which instance does this belong to of the multiple occurring field.', 'start': 5294.377, 'duration': 6.782}], 'summary': 'Workflow restart generates key starting from 101 and can be used as primary key in absence of one. the generated column id helps identify instances of multiple occurring fields.', 'duration': 29.134, 'max_score': 5272.025, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o5272025.jpg'}, {'end': 5887.158, 'src': 'embed', 'start': 5859.537, 'weight': 5, 'content': [{'end': 5865.261, 'text': 'So to summarize, using the normalizer transformations, we can convert multiple occurring data to single unique data.', 'start': 5859.537, 'duration': 5.724}, {'end': 5870.005, 'text': "Now we've just seen how it's done, and you can use the generated key as a primary key.", 'start': 5865.662, 'duration': 4.343}, {'end': 5875.329, 'text': 'Because this is a unique value that does not repeat, you can set it as a primary key in your target definition.', 'start': 5870.385, 'duration': 4.944}, {'end': 5878.671, 'text': "So with this, we come to a conclusion of today's session.", 'start': 5875.929, 'duration': 2.742}, {'end': 5883.415, 'text': 'If you have any questions with respect to any of the transformations, please do let me know.', 'start': 5879.252, 'duration': 4.163}, {'end': 5887.158, 'text': 'we can clarify it, else make sure you provide the feedback after the session.', 'start': 5883.415, 'duration': 3.743}], 'summary': 'Normalizer transformations convert data to unique values, suitable as primary keys.', 'duration': 27.621, 'max_score': 5859.537, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o5859537.jpg'}], 'start': 5125.256, 'title': 'Normalizer transformation and use cases', 'summary': 'Covers expression and normalizer transformation for row-level calculations, column modifications, and data normalization with cobol files. it also discusses the use of the normalizer transformation, including key and column id generation, presenting a use case with doubled rows in the target table.', 'chapters': [{'end': 5231.754, 'start': 5125.256, 'title': 'Expression and normalizer transformation', 'summary': 'Covers the expression transformation for row-level calculations and column modifications, followed by the normalizer transformation for converting data to a normalized format, addressing the maximum number of occurring instances and its use with cobol files.', 'duration': 106.498, 'highlights': ['The normalizer transformation helps in converting the data to a normalized format, such as creating unique rows for multiple occurrences of data, like customer addresses or weekly sales. The normalizer transformation converts data to a normalized format, creating unique rows for multiple occurrences of data, such as customer addresses or weekly sales.', 'Informatica automatically creates a normalizer transformation as a source qualifier for a COBOL source file, which is a commonly asked topic in interviews. Informatica automatically creates a normalizer transformation as a source qualifier for a COBOL source file, a commonly asked topic in interviews.', 'Expression transformation allows for row-level calculations and modifying individual columns, demonstrated by creating a new column through concatenation of first and last names. Expression transformation allows for row-level calculations and modifying individual columns, demonstrated by creating a new column through concatenation of first and last names.']}, {'end': 5918.911, 'start': 5232.415, 'title': 'Using normalizer transformation', 'summary': 'Discusses the use of the normalizer transformation, including the generation of key and column id, and demonstrates a use case involving the transformation to convert multiple occurring data to single unique data, with the generated key doubling the rows in the target table.', 'duration': 686.496, 'highlights': ['The normalizer transformation provides features for generating key and column ID, with the generated key being a unique sequence number updated for each row, and the generated column ID helping identify the instance of multiple occurring fields. The normalizer transformation provides a generated key, a unique sequence number updated for each row, and a generated column ID to identify the instance of multiple occurring fields.', 'The generated key can be used as a primary key in the target table if no primary key is present, and the value restarts from one if the workflow is executed again, while the generated column ID helps in identifying the instance of multiple occurring fields. The generated key can be used as a primary key in the target table, restarting from one if the workflow is executed again, while the generated column ID helps identify the instance of multiple occurring fields.', 'The use case involves using the normalizer transformation to convert multiple occurring data to single unique data, demonstrating how the generated key doubles the rows in the target table. The use case demonstrates using the normalizer transformation to convert multiple occurring data to single unique data, with the generated key doubling the rows in the target table.']}], 'duration': 793.655, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/yw8uJdUc42o/pics/yw8uJdUc42o5125256.jpg', 'highlights': ['The normalizer transformation converts data to a normalized format, creating unique rows for multiple occurrences of data, such as customer addresses or weekly sales.', 'Informatica automatically creates a normalizer transformation as a source qualifier for a COBOL source file, a commonly asked topic in interviews.', 'Expression transformation allows for row-level calculations and modifying individual columns, demonstrated by creating a new column through concatenation of first and last names.', 'The normalizer transformation provides a generated key, a unique sequence number updated for each row, and a generated column ID to identify the instance of multiple occurring fields.', 'The generated key can be used as a primary key in the target table, restarting from one if the workflow is executed again, while the generated column ID helps identify the instance of multiple occurring fields.', 'The use case demonstrates using the normalizer transformation to convert multiple occurring data to single unique data, with the generated key doubling the rows in the target table.']}], 'highlights': ['Informatica offers 33 types of transformations, but the session focuses on five commonly used transformations: source qualified, joiner, union, expression, and normalizer.', 'Data transformation enables conversion of inconsistent and unstructured data to a structured and consistent format, facilitating easier analysis.', 'The source qualified transformation is used to convert data types to Informatica supported data types.', 'Joiner and union transformations assist in combining data from various sources.', 'Expression transformation enables the performance of calculations and expressions on each row of data.', 'The normalizer transformation aids in converting data to a normalized format.', 'Creating a new work folder to store sources, targets, mapping, and workflow for managing various processes using Informatica.', 'Connecting to the Informatica Power Center Repository Manager by selecting the configured repository and providing the username and password.', 'Designing a mapping using the Informatica Power Center Designer by loading sources, creating the mapping, and using the connection object to connect to the database.', 'Creating workflows in Informatica can be done manually or automatically, based on the complexity of mappings and the need for reusable sessions.', "New columns 'department name' and 'location ID' added to the target table, in addition to existing employee details.", 'The chapter explains the four types of join in Informatica: normal join, master outer join, detail outer join, and full outer join.', 'Joiner transformation specifies conditions for joining tables and using multiple conditions to extract specific data with corresponding matching columns.', 'The workflow execution demonstrated 500 rows present in the customer table and 150 rows present in the products table.', 'The final table contains 500 records with all the customer details and corresponding product details, including the name of the product, product company, and other product details.', 'The union transformation allows joining multiple sources with matching ports having the same data type and precision, without removing duplicate rows, and with only one output group defined by Informatica.', 'Creating a flag to identify inconsistencies in the data Details the process of creating an inconsistency flag to identify rows with data inconsistencies, which will facilitate direct communication with employees for necessary data updates and specifies the precision of the flag as five.', 'Execution and validation of the workflow resulting in 107 rows transferred and 16 records with inconsistencies identified The workflow successfully transfers 107 rows to the target table, with 16 records identified as having inconsistencies, which need to be updated', 'The normalizer transformation converts data to a normalized format, creating unique rows for multiple occurrences of data, such as customer addresses or weekly sales.', 'Informatica automatically creates a normalizer transformation as a source qualifier for a COBOL source file, a commonly asked topic in interviews.', 'Expression transformation allows for row-level calculations and modifying individual columns, demonstrated by creating a new column through concatenation of first and last names.', 'The normalizer transformation provides a generated key, a unique sequence number updated for each row, and a generated column ID to identify the instance of multiple occurring fields.', 'The generated key can be used as a primary key in the target table, restarting from one if the workflow is executed again, while the generated column ID helps identify the instance of multiple occurring fields.', 'The use case demonstrates using the normalizer transformation to convert multiple occurring data to single unique data, with the generated key doubling the rows in the target table.']}