Course Overview
About Course
This 40‑hour ETL Testing training enables professionals to confidently validate data across the extract, transform, and load lifecycle. Starting with data warehousing fundamentals—covering schemas, SCD types, and OLAP versus OLTP—participants transition into understanding ETL architecture and how testing differs in data environments. Comprehensive workflow modules teach requirement analysis, test case design, execution strategies, and defect tracking, while also addressing challenges like high volume, varying data formats, and system limitations.
Learners engage deeply with test types: data completeness, transformation, quality, performance, integration, incremental/full-load validation, and user acceptance testing. Tools like Informatica PowerCenter, IBM DataStage, and open-source ETL platforms are explored through hands-on labs that simulate real-world pipelines. Emphasis on source-to-target testing, error handling, recovery mechanisms, and performance tuning equips students to ensure reliability and robustness in data delivery.
Automation plays a key role—practicing shell scripting or Python to schedule ETL validation, generate test reports, and streamline workflows. Case studies in retail, finance, or CRM data reinforce learning, culminating in a capstone where learners architect, implement, and test a complete ETL pipeline. Downloading 75% of class time is practical work. Graduates exit with strong SQL, scripting, and validation skills, a portfolio of tested ETL pipelines, readiness for certification, and the capability to drive quality-assured data integration in enterprise environments.
Course Syllabus
Module 1: Data Warehousing & ETL Concepts (4 hrs)
- Introduce data warehousing fundamentals: OLTP vs OLAP, star/snowflake schemas, facts & dimensions, SCD types
Module 2: ETL Architecture & Testing Overview (4 hrs)
- Understand ETL pipelines, SDLC/STLC in data integration projects, key differences from application testing
Module 3: ETL Testing Workflow & Challenges (6 hrs)
- Step through requirement analysis, test planning, test-case design, execution, defect reporting; address challenges like volume, data variety, job privileges
Module 4: Types of ETL Tests (6 hrs)
- Explore completeness, transformation, data quality, performance, integration, UAT, full/incremental load testing, SQL-driven validation
Module 5: ETL Tools & Components (4 hrs)
- Overview of Informatica, DataStage, Ab Initio; PowerCenter components: Designer, Workflow, Repository, transformations
Module 6: Source & Target Validation (4 hrs)
- Validate flat files, ODS, RDBMS sources and targets; test boundary conditions, duplicate and inconsistent data
Module 7: Error Handling, Logging & Incremental Loads (4 hrs)
- Test ETL error-logging, recovery, rollback; validate incremental and full-load strategies .
Module 8: Performance Testing & Optimization (4 hrs)
- Analyze load performance, benchmarking, tuning SQL, parallel job execution .
Module 9: Automation & Reporting (4 hrs)
- Use scripting (shell, Python), schedule testing with cron/CLI, generate ETL test reports and metrics
Module 10: Real‑World Case Studies & Capstone (4 hrs)
- Hands-on mini-project: build and validate ETL pipeline (source → transform → load), peer review, and closure of test documentation.



