Informatica Data Quality (IDQ) Foundation for Developers

Course Objectives

IDQ Foundation Bootcamp for Developers is hands-on, an introductory-level IDQ course that provides students with a high-level overview of the Informatica Data Quality Developer Desktop as well as sufficient knowledge of all Data Quality functionalities.

NOTE: The Informatica Training Series is independent-format training that can be tuned and adjusted to best meet your needs. Our materials are flexible, comprehensive, and are always instructed by a senior instructor with a deep understanding of Informatica and its most current features, benefits and functionality in a wide array of uses. This is not Official Informatica Training.

Course Prerequisites

This course is geared for ETL developers new to Informatica Analyst / Developer.

Course Agenda

1. Data Quality Overview
    
2. Developer Tool: Physical & Logical Data Objects

• Overview
• Create a Physical Data Object
  • Relational
  • Customized
  • 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 Transformation Part 1:

• Expression
• Filter
• Aggregator
• Sorter
   

8. Data Integration Transformation 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:
  • Case Converter
  • Merger
  • Labeler
  • Standardizer
• Exercise #3 Data Standardization

12. Data Parsing:

• Parser the data set using one of the following methods:
  • Token Parser
  • Pattern Parser
  • 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

Course Materials

Each student will receive a Student Guide with course notes, code samples, software tutorials, diagrams and related reference materials and links (as applicable). Our courses also include step by step hands-on lab instructions and and solutions, clearly illustrated for users to complete hands-on work in class, and to revisit to review or refresh skills at any time. Students will also receive the project files (or code, if applicable) and solutions required for the hands-on work.