ETL QA for Freshers

Categories: QA
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About Course

ETL QA (Extract, Transform, Load Quality Assurance) is the process of testing ETL workflows to ensure data is extracted, transformed, and loaded correctly into a target system, such as a data warehouse. It ensures data accuracy, integrity, and performance while verifying that business requirements are met.

Why ETL QA Skills Are In Demand 

  1. Explosion of Data-Driven Decision-Making
    • As organizations increasingly rely on data to drive their decisions, data quality and accuracy are paramount.
    • ETL processes (Extract, Transform, Load) are at the heart of how data is handled, and QA teams ensure that data is reliable and error-free.
  1. Growth of ELT (Extract, Load, Transform) Pipelines
    • With the rise of cloud data platforms (like Snowflake, Redshift, BigQuery), ETL is evolving into more complex ELT workflows.
    • QA in these environments is crucial to ensure data transformation logic is validated and integrated across multiple sources.
  1. Data Governance and Compliance
    • Data governance is a big concern for organizations — ensuring data is accurate, consistent, and traceable.
    • QA roles now also cover data integrity checks, audit trails, and data privacy, especially in regulated industries (finance, healthcare, etc.).
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Course Content

ETL QA

  • Introduction to ETL & Data Warehousing
  • Understanding Data
  • Introduction to Data Modelling
  • ETL Testing Fundamentals
  • Types of ETL Testing
  • ETL Testing Process & Lifecycle
  • Test Case Design & Execution
  • Defect Management in ETL Testing
  • SQL for ETL Testing
  • ETL Tools & Hands-on Practice
  • Data Validations
  • Real-Time Projects
  • Validate ETL Pipelines
  • Snowflake Overview
  • Interview Preparation