ETL Testing: Manual + Automation with Python – Live Training
(Learn ETL basics, SQL, Data validation, Python automation, Frameworks, Cloud ETL testing, Performance checks, and Real-world projects with hands-on training to build job-ready skills.)
This ETL Automation Testing course is designed to help you master both manual and automated ETL testing. You’ll start with the fundamentals of data, SQL, and ETL processes, then move on to advanced concepts using Python for automation. The course covers data validation, transformation testing, and building reusable automation frameworks. You’ll also gain exposure to cloud ETL tools like Snowflake and Databricks, along with CI/CD integration. By the end, you’ll complete a real-world project and be well-prepared for interviews and industry roles.
About the Instructor:
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Divya is a highly experienced Cloud Data Engineer and Corporate Trainer with over 7 years of professional expertise in the IT and services industry. She has extensive hands-on knowledge in ETL, Data Warehousing, and Cloud Technologies, and has delivered impactful solutions using tools like Informatica PowerCenter, IICS, MS SQL Server, Python 3.X, SnapLogic, and Google Cloud Services (BigQuery, CloudSQL, Composer/Airflow, etc.). Alongside her corporate experience, Divya is deeply passionate about teaching and mentoring. She has conducted multiple training sessions for professionals and students, enabling them to gain practical skills in Data Engineering and Cloud technologies. She specializes in simplifying complex concepts with real-world examples, ensuring learners not only understand the theory but also gain the hands-on expertise required in today’s industry. |
Live Sessions Price:
Offer price after discount is 200 USD 159 89 USD Or USD19000 INR 99000 INR 6900 Rupees.
OR
Free Demo Session:
24th September @ 9 PM – 10 PM (IST) (Indian Timings)
24th September @ 11:30 AM – 12:30 PM (EST) (U.S Timings)
24th September @ 4:30 PM – 5:30 PM (BST) (UK Timings)
Class Schedule:
For Participants in India: Monday to Friday @ 9 PM – 10 PM (IST)
For Participants in the US: Monday to Friday @ 11:30 AM – 12:30 PM (EST)
For Participants in the UK: Monday to Friday @ 4:30 PM – 5:30 PM (BST)
What student’s have to say about Trainer :
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👨This course gave me complete confidence in ETL automation. – Arush Patro 👩I loved how the trainer explained SQL and ETL testing basics. The automation part with Python was a game changer for me.– Greeshma Gaikward 👨The course covered everything from ETL fundamentals to advanced automation. The real-time scenarios and projects gave me confidence to apply my skills at work. Truly industry-relevant training. – Meghansh 👩I liked the step-by-step approach, starting from basics and gradually moving to automation frameworks. The trainer also helped with interview preparation, which added a lot of value to the course.– Abdul 👨Clear explanations, hands-on practice, and excellent support throughout. Highly recommend for anyone starting ETL testing. – Justin |
What will I learn by the end of this course?
- Understand ETL concepts and data flow clearly.
- Write SQL queries for ETL testing.
- Perform manual ETL testing and validations.
- Automate ETL testing using Python.
- Build a mini automation framework.
- Work with real-world ETL projects and cloud tools.
- Prepare for interviews and job roles in ETL testing.
Who can enroll for this course?
- Beginners who want to start a career in ETL Testing.
- Manual testers looking to move into ETL Automation.
- SQL learners who want to apply their skills in testing.
- Data engineers or analysts who wish to learn ETL validation.
- Professionals aiming to upskill in automation with Python.
- Freshers preparing for ETL testing job opportunities.
Salient Features:
- 40 Hours of Live Training along with recorded videos
- Lifetime access to the recorded videos
- Course Completion Certificate
Course syllabus:
Week 1: Basics of Data & ETL Foundations
⮚ What is Data? Types of data (Structured, Semi-structured, Unstructured)
⮚ Introduction to Databases and Tables
⮚ OLTP vs OLAP with real-life examples
⮚ Why do we need Data Warehousing?
⮚ Data Warehouse Architecture basics (Source → Staging → DWH → Reporting)
⮚ Fact & Dimension tables explained with daily-life examples
⮚ Star Schema vs Snowflake Schema
⮚ Very simple intro to ETL process (Extract, Transform, Load)
(Goal: Students understand why ETL exists and how data flows.)
Week 2: SQL Basics for ETL Testing
⮚ Introduction to SQL (SELECT, WHERE, ORDER BY)
⮚ Joins explained with examples (INNER, LEFT, RIGHT)
⮚ Group By, Aggregations (SUM, COUNT, AVG)
⮚ Subqueries basics
⮚ Intro to Primary Key & Foreign Key
⮚ Hands-on SQL practice on datasets (sales/orders type examples)
⮚ Why SQL is the core skill for ETL Testing
⮚ Intro to Data Quality dimensions (Accuracy, Completeness, Consistency)
(Goal: Students become comfortable writing queries for validations.)
Week 3: ETL Testing Fundamentals
⮚ What is ETL Testing? Why is it different from normal testing?
⮚ ETL Testing Lifecycle (mapping document → test cases → execution → defect logging)
⮚ ETL Testing vs Manual Testing
⮚ Data validation basics (row counts, duplicate checks, NULL checks)
⮚ Transformation Testing (examples like convert date format, derive new column)
⮚ Writing ETL Test Cases & Test Scenarios
⮚ Defect Life Cycle in ETL Testing (with example)
(Goal: Students learn how to test ETL jobs manually before automation.)
Week 4: Tools & Hands-On Practice
⮚ Overview of ETL tools (Informatica PowerCenter, IICS, Talend — just awareness)
⮚ Basic UNIX commands (ls, cat, grep, wc, shell scripting basics)
⮚ Real manual ETL testing scenarios (data completeness, duplicates, mismatched values)
⮚ Data Profiling basics (checking quality before ETL)
⮚ case study: Validating a source → staging → target load
(Goal: Students do mini hands-on ETL testing manually.)
Week 5: Introduction to Automation with Python
⮚ Why Automation in ETL Testing? (real-world need)
⮚ Python Basics: Variables, Data Types, Loops, If-Else
⮚ Using Python for SQL query execution (pyodbc/sqlalchemy)
⮚ Reading/writing data from CSV & databases
⮚ pandas basics for comparison (df.equals, merge, differences)
⮚ Error handling, logging basics in Python
(Goal: Students see how Python replaces manual SQL checks.)
Week 6: Advanced Automation with Python
⮚ Functions, Modules, File handling in Python
⮚ Writing reusable test scripts (parameterized)
⮚ Automating SQL execution + validation
⮚ Automating reconciliation between source & target tables
⮚ pytest/unittest basics (automation frameworks)
⮚ Config-driven testing (test cases from Excel/JSON)
⮚ Scheduling scripts (cron/Windows Task Scheduler)
(Goal: Students start building a mini framework.)
Week 7: Real-World ETL Automation & Cloud
⮚ Real-time ETL scenarios (Incremental loads, CDC)
⮚ Performance testing of ETL jobs
⮚ Debugging and troubleshooting automation scripts
⮚ Cloud ETL Testing (Snowflake, Databricks, GCP BigQuery)
⮚ Error handling & retry mechanisms
⮚ CI/CD Integration (Jenkins basics, pipeline execution)
(Goal: Students apply automation in real-world ETL pipelines.)
Week 8: Final Project & Career Prep
⮚ End-to-End ETL Automation Project(Source → Staging → DWH → Validation → Automation → Reporting)
⮚ Industry Best Practices & Pitfalls
⮚ Testing security & compliance aspects in ETL processes
⮚ Designing an ETL Automation Framework (mini version)
⮚ Resume Prep + Mock Interviews + Q&A
(Goal: Students complete one full project + interview preparation.)