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Informatica Data Quality (IDQ + CDQ) Online Training

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This course provides hands-on training in building data quality solutions using Informatica IDQ and Cloud Data Quality (CDQ) on IICS. You will learn to profile, cleanse, standardize, match, and monitor data across various sources, both on-premise and cloud.

The program covers real-time business use cases, rule development, address validation, exception handling, and integration with ETL workflows. With practical assignments, interview preparation, and a capstone project, this course is ideal for those looking to start or advance their career as a Data Quality Engineer or IDQ/CDQ Developer

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  • 2 Months
  • 50+ Hours
  • Lifetime Access
  • Cloud Data Quality
  • Oracle Database

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Informatica Data Quality – IDQ & CDQ

Technologies Taught

  • Informatica Data Quality (IDQ)
  • Informatica Developer Tool
  • Informatica Administrator Console
  • Model Repository Service
  • Cloud Data Quality (CDQ)
  • Informatica Intelligent Cloud Services
  • Secure Agent & CDQ Assets
  • Cloud Mapping Designer & Taskflows

Course Unique Features

  • 50+ hrs of Live Interactive Sessions
  • Hands-on implementation with IDQ (on-premise) & CDQ (cloud)
  • Exposure to Informatica Developer Tool & IICS CDQ Components
  • Live doubt-clearing sessions after each module
  • Full real-time project documentation: BRDs, TSDs, Test Plans & Deployment
  • End-to-End Lifecycle Exposure
  • Daily topic-wise interview Q&A
  • Resume building & interview support for IDQ/CDQ roles
  • Resume Building & Interview Prep. Support
  • Real-time address validation using Address Doctor
  • Design of Scorecards & Data Quality Metrics
  • Best practices & optimization techniques for production-ready pipelines

After completion of this course you can apply for roles:

  • ⁠AWS Data Engineer
  • Cloud Data Engineer
  • Big Data Engineer
  • ETL Developer / Engineer
  • Spark Developer / PySpark Engineer
  • Data Platform / Warehouse Engineer
  • ⁠Data Pipeline Engineer

Course Curriculum

Informatica Data Quality (IDQ) Training

1. Introduction to Informatica (IDQ)

  • Overview of Data Quality concepts
  • Role of IDQ in enterprise data management
  • IDQ on-premise architecture
  • Domain and Node structure
  • Services: Model Repository, Data Integration, Profiling
  • Client Tools: Developer Tool, Administrator Console
  • IDQ vs PowerCenter vs Informatica MDM: Positioning and Use Cases

2. Repository & Administration

  • Setting up IDQ Domain and Node
  • Understanding Services and Integration Service Configuration
  • Security: User Roles, Permissions, Repository Access
  • Connectivity setup: Flat Files, RDBMS (Oracle, SQL Server, etc.)
  • Backup and Recovery best practices

3. Developer Tool Basics

  • Connecting to the Repository using Developer Tool
  • Project and Folder creation
  • Overview of objects: Mappings, Mapplets, Profiles, Rules, Scorecards
  • Importing/Exporting objects between environments
  • Version Control and Check-in/Check-out process

4. Data Profiling

  • Column Profiling: Nulls, Distinct values, Patterns
  • Rule Profiling: Apply reusable DQ rules
  • Join Profiling: Discover relationships between datasets
  • Setting thresholds and alerts
  • Interpreting profiling results for DQ insights

5. Scorecards

  • Creating and configuring scorecards
  • Metrics, filters, dimensions
  • Creating trend reports and visualizations
  • Linking rules to scorecards
  • Monitoring ongoing data quality

6. Transformations in IDQ

  • Standard Transformations: Expression, Filter, Router, Aggregator
  • Lookup, Joiner, Union, Sorter
  • Data Quality-specific Transformations: Parser, Labeler, Tokenizer, Identifier Cleanse, Address Validator, Match, Consolidator
  • Creating mappings using Parser/Labeler Using Cleanse and Lookup for standardization

7. Address Validation & Enrichment

  • Integrating external AV engines (e.g., AddressDoctor)
  • Configuring AV transformations
  • Handling multi-country address formats
  • Licensing considerations for AV/Name3

8. Reference Data Management

  • Reference Table object configuration
  • Using lookup and value replacement
  • Maintaining reference data updates
  • Building dynamic rule logic using reference lists

9. Matching and Identity Resolution

  • Match Path and Match Columns setup
  • Match Key Generation Techniques
  • Fuzzy vs Exact Matching: Configuration and Tuning
  • Creating and fine-tuning match rules
  • Consolidation and Survivorship logic (basic)

10. Exception Handling

  • Creating exception tables and handling rejected data
  • Filtering and routing bad records
  • Notifying stakeholders through workflow/email
  • Best practices for exception management

11. Workflow Integration with PowerCenter

  • Exporting IDQ mappings to PowerCenter
  • Parameter file management
  • Using IDQ logic within ETL workflows
  • End-to-end DQ pipeline design (ETL + DQ)

12. Reusability & Modular Design

  • Mapplets for rule encapsulation
  • Parameterization techniques
  • Shared folders and cross-project references
  • Rule/Mapplet versioning and migration

13. Deployment and Promotion

  • Object lifecycle: Dev → QA → Prod
  • Export/Import procedures using XML

14. Auditing, Logs & Monitoring

  • Execution logs: Session log, Transformation log
  • Audit table design
  • Monitoring services via Admin Console
  • Performance tuning tips

15. Real-World Case Studies & Projects

  • Customer Master Standardization
  • Product Attribute Cleansing
  • Lead De-duplication across CRMs
  • Implementing an End-to-End Data
  • Quality Flow: Source Ingestion → Profiling → Standardization → Matching → Exceptions → Export
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Download Full Syllabus in PDF

Upon completing this training

What you’ll learn Upon completing this training

  • Design and build end-to-end data quality pipelines using Informatica IDQ and CDQ.
  • Perform advanced data profiling to assess data health and identify anomalies.
  • Cleanse, standardize, and enrich data using transformations and external engines.
  • Develop & apply data quality rules using rule specifications, dictionaries & mapplets.
  • Implement fuzzy and exact matching logic for deduplication and identity resolution.
  • Handle data exceptions through custom routing, logging, and alert mechanisms.
  • Create scorecards and dashboards to monitor ongoing data quality metrics.
  • Integrate IDQ logic into ETL workflows using PowerCenter or IICS taskflows.
  • Deploy and promote data quality assets across Dev → QA → Prod environments.
  • Operate confidently as a Data Quality Engineer or Informatica IDQ/CDQ Developer.

Course Instructed By:

Mr.Rahul D

A seasoned Data Quality and Integration expert with 10+ years of experience in Informatica IDQ and Cloud Data Quality (CDQ) on IICS. Has led enterprise data quality projects across industries, specializing in profiling, cleansing, matching, and exception handling. Known for practical, real-world training that has mentored hundreds into job-ready IDQ/CDQ developers. Approved trainer by Raj Cloud Technologies.

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Informatica Data Quality – IDQ & CDQ

NEW BATCH STARTED, HURRY UP!

Informatica Data Quality (IDQ)

₹13,999 ₹19,999

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Cloud Data Quality (CDQ)

₹11,999 ₹14,999

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Informatica Data Quality + Cloud Data Quality (IDQ & CDQ)

₹24,999 ₹34,998

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What our students say?

Meghana R
Meghana R
@meghana-r
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I just want to share my experience about Natraj sir training, it is one of the best training I had ever on informatica. I learned lots of real time concepts from Raj sir training and also they are very useful in my job. The training is based on Realtime scenarios so that you will get familiar with the concepts of informatica and Oracle and Unix. Thank you Raj sir for giving us such a nice training and so much of confidence...
Akash Dhus
Akash Dhus
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It's a fantastic course for a beginner also. I could feel the effort that was put into to make sure people understood. Thank you Raj, when I become one the greatest, I will remember this beginning. A wonderful experience . The lecturers are great with a very nice way on interacting and lots of useful material. Thank you for all your cooperation. Hope to see more of you in future. Thank you once again.
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