Course Syllabus

Module 1: Data Quality & Data Warehousing Fundamentals (4 hrs)

• Understand data quality dimensions, ETL basics, the role of cleansing, profiling, and match/merge in enterprise data environments

Module 2: Environment Setup & Tool Introduction (4 hrs)

• Install and configure IDQ and Developer tool; explore the UI, project collaboration, repository, content sets, and Analyst vs Developer roles

Module 3: Data Profiling & Scorecards (6 hrs)

• Perform column-, multi-, join-, and mid-stream profiling; generate scorecards to assess data completeness, accuracy, and consistency

Module 4: Data Standardization & Parsing (6 hrs)

• Use parser, labeler, standardizer transformations, manage dictionaries; validate postal addresses and apply reference data approaches

Module 5: Data Matching & Deduplication (6 hrs)

• Configure matching strategies (exact/fuzzy), cluster analysis, identity matching, match rules, and grouping; handle duplicated records

Module 6: Consolidation & Exception Handling (4 hrs)

• Consolidate matched data via consolidation/association mapplets; design workflows for exception record review and stewardship handling

Module 7: Mapplets, Workflows & PowerCenter Integration (4 hrs)

• Build reusable mapplets, integrate DQ mappings into Informatica PowerCenter, design human task workflows and triggers

Module 8: Data Quality Cloud (IDMC) Essentials (4 hrs)

• Use IDMC Cloud Data Quality: cloud agent setup, mappings, standardization, dedupe, verification, scorecards in cloud environment

Module 9: Monitoring, Administration & Performance (4 hrs)

• Implement logging, error handling, performance tuning, change data management, SCDs; monitor workflows via Analyst and Developer tools

Module 10: Capstone Project & Certification Preparation (2 hrs)

• Deliver end-to-end IDQ solution: from profiling to deployment and stewardship; review Developer certification exam domains

• Key Features

  • 70%+ hands-on labs: including profiling, parsing, deduplication, mapping, and cloud DQ jobs.
  • Dual platform teaching: on-premise Developer tool and Informatica Data Quality Cloud (IDMC) workflows.
  • Reusable mapplets: learn to design modular, maintainable data quality components.
  • Tool integration: mapplets in ETL pipelines via PowerCenter; cloud agent and monitoring pipelines.
  • Real-world datasets: address, customer, and product cleansing with postal validation and custom rules.
  • Expert-led guidance: interactive labs, peer-sharing, Q&A sessions and performance tuning support.
  • Capstone implementation: end-to-end data quality system from ingestion to exception management.
  • Certification support: mock tests aligned with IDQ Developer certification paths.
  • Rich resource materials: session recordings, sample mappings, rule libraries, community discussion access.