Master Big Data Testing Training to validate large-scale data systems using modern tools. Get practical experience, improve data quality skills, and unlock high-demand career opportunities
Level
Advanced
Duration
8 weeks



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Big Data Testing Training is designed to help professionals validate and manage large-scale data systems used in modern businesses. This course covers key concepts like data validation, ETL testing, and testing techniques for distributed data processing using tools such as Hadoop and Spark. You will learn how to ensure data accuracy, consistency, and performance across complex big data environments.
The training focuses on real-time scenarios, including testing of data pipelines, data warehousing, and analytics platforms. It also introduces automation strategies to improve testing efficiency and handle high-volume data effectively. With hands-on projects, you gain practical experience in identifying data issues and maintaining quality in enterprise systems.
As organizations increasingly rely on data-driven decisions, skilled professionals in big data testing are in high demand. This training prepares you for roles like Big Data Tester, QA Analyst, and Data Engineer, helping you build a strong and future-ready career in the data domain.
Working professional who is carrying more then 10 years of industry experience.
Access to updated presentation decks shared during live training sessions.
E-book provided by TechPratham. All rights reserved.
Module-wise assignments and MCQs provided for practice.
Daily Session would be recorded and shared to the candidate.
Live projects will be provided for hands-on practice.
Expert-guided resume building with industry-focused content support.
Comprehensive interview preparation with real-time scenario practice.
Module 1: Introduction to Big Data & Testing
Understand fundamentals of big data, its architecture, and testing challenges. Learn how big data environments handle large datasets and why data validation is critical in modern analytics systems.
Module 2: Hadoop & Distributed Systems
Learn Hadoop framework and distributed data processing. Understand how large datasets are stored and processed across clusters in real-world big data environments.
Module 3: ETL Testing Fundamentals
Master ETL testing concepts including data extraction, transformation, and loading. Learn how to validate data accuracy and ensure quality in data pipelines.
Module 4: Spark & Data Processing
Learn Apache Spark for fast data processing. Understand how Spark is used in big data systems for analytics and real-time data handling.
Module 5: Data Warehousing & Testing
Understand data warehousing concepts and how testing ensures data integrity. Learn how analytics platforms rely on accurate data storage.
Module 6: Automation in Big Data Testing
Learn automation techniques to handle large-scale data testing. Improve efficiency and accuracy using automation tools and scripts.
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Scenario: Test large-scale ETL pipelines processing financial data at Infosys Bengaluru. Validate data accuracy, transformation rules, and ensure consistency across Hadoop and cloud systems.
Scenario: Work on telecom data testing at TCS Hyderabad using Hadoop. Verify large data sets, check data processing logic, and ensure system handles high-volume streaming data efficiently.
Scenario: Test retail data warehouse systems at Wipro Pune. Ensure correct data loading, validate reporting accuracy, and check integration between multiple big data sources.
Scenario: Perform big data testing on Spark-based systems at HCLTech Chennai. Validate real-time data processing, ensure performance, and check large dataset handling in distributed systems.

Additional Support We Provide
24/7 Support
LinkedIn Profile
Resume Writing
Alumni Sessions
Interview Preparation
Live Projects
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