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Informatica Data Quality (IDQ) Foundation for Developers 10.5x

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4 Days
Classroom Training, Online Training
Informatica Training

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Course Description


IDQ Foundation Bootcamp for Developers course provides an excellent overview of the Informatica Data Quality Developer tool using real use cases as exercises to enhance the learning experience.



  • Work with both the Analyst and Developer tools in all its aspects
  • Collaboration with Business Analysts who use primarily the Analyst tool.
  • Profile data in both the Developer and Analyst: Columns, Joins, Rules, Multi object and Mid-Stream Transformation profiling.
  • Create and manage reference tables in the Analyst Tool
  • Highlight and compare the Lookup transformation to reference tables in IDQ
  • Design and create mapplets for reusability purposes in IDQ mappings.
  • Design and create mappings to standardize, cleanse and parse data.
  • Validate addresses and develop accelerators using various techniques.
  • Create mappings to associate and consolidate matched records.
  • Identify duplicate records and de-dupe them.
  • Move IDQ mappings to PowerCenter and run them under the Workflow Manager
  • Attendees will learn how to apply various strategies to cleanse and improve data quality.


  • Developers with no Informatica experience




1. Data Quality Overview 2. Developer Tool: Physical & Logical Data Objects
  • Overview
  • Create a Physical Data Object
i. Relational ii. Customized iii. Flat File
  • Create a Logical Data Object
Exercise #1 Creating Connections & Import Data source 3. Data Profiling with Developer
  • Profiling
  • Creating Profiling Rules
  • Creating and running scorecards
Exercise #2 Column Profiling in Developer 4. Developing Data Quality Projects
  • Overview
  • Objects
5. Working with Mappings
  • Mappings
  • Sources
  • Targets
  • Linking and Running
6. Working with Transformations
  • Transformations
  • Ports
  • Expressions
  • Testing
7. Data Integration Transformations Part 1:
  • Expression
  • Filter
  • Aggregator
  • Sorter
8. Data Integration Transformations Part 2:
  • Joiner
  • Lookup
  • Router
  • Union
9. Working with Mapplets & Rules:
  • Overview
  • Creating
  • Mapplet Rules
10. Using Reference Data:
  • Overview
  • User Reference Table
  • Content sets
11. Data Standardization:
  • Cleanse and standardize the data set using Standardization transformation:
i. Case Converter ii. Merger iii. Labeler iv. Standardizer Exercise #3 Data Standardization 12. Data Parsing:
  • Parser the data set using one of the following methods:
i. Token Parser ii. Pattern Parser iii. NER/Probabilistic Model
  • Decision
Exercise #4 Parsing using Pattern Based Parsing 13. Address Validation
  • Overview
  • Reference Data
  • Work with Address Validation mappings
14. Data Matching
  • Introducing Matching Concepts
  • Data Grouping
  • Matching Analysis
  • Matching Transformation
Exercise #5 Apply Matching Techniques - Classic Matching 15. Identity Match Option
  • IMO vs Classic Matching
  • Overview
  • IMO configuration
Exercise #6 Apply Matching Techniques - Identity Matching 16. Automatic Consolidation
  • Consolidation transformation
  • Automatically consolidate matched records
Exercise #7 Multi Criteria Matching, Association and Consolidation 17. Working with Workflows:
  • Build a workflow that handle Exception and duplicate records.
  • Human Task
  • Other Tasks
  • Deployment
Exercise #8 Informatica Data Quality Workflow Using Human Task 18. Analyst for the Exception records:
  • Update and modify the exception/duplicate records through the Analyst tool.
19. Other Transformations:
  • Comparison
  • Weighted Average
20. Power Center Integration:
  • Exporting to PC
  • Importing from PC
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