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    ETL Testing

    Certificate Program in ETL Testing

    The Certificate Program in ETL Testing at Veda IT provides specialized training in the verification and validation of ETL (Extract, Transform, Load) processes within data warehouses and business intelligence applications. This course is ideal for aspiring data testers, QA engineers, data analysts, and IT professionals who want to ensure data accuracy, consistency, and reliability across systems.

    Who Should Join ETL Testing Course?

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      Job Switchers
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      Working Professionals
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      Engineering Graduates
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      University Students
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      Entry-Level Candidates

    Keyskills of ETL Testing Developer

    The Certificate Program in ETL Testing equips professionals with essential skills to master the end-to-end data integration process. Key skills include understanding ETL concepts and architecture, proficiency in data extraction, transformation, and loading techniques, and expertise in SQL queries and database management. Participants also gain knowledge in data warehousing, data validation methodologies, and performance tuning of ETL processes.

    Key Features
    • Covers ETL processes, data validation, SQL, and automation.
    • Real-world projects to develop practical ETL testing skills.
    • Learn from experienced data and QA professionals.
    • Offline classes with optional online support.
    • Recognized certificate from Veda IT upon successful course completion.

    What you'll learn

    The Certificate Program in ETL Testing at Veda IT provides specialized training in the verification and validation of ETL (Extract, Transform, Load) processes within data warehouses and business intelligence applications. This course is ideal for aspiring data testers, QA engineers, data analysts, and IT professionals who want to ensure data accuracy, consistency, and reliability across systems. Covering essential concepts of ETL testing, data transformation, SQL, and data quality validation, this program equips students with the skills needed to perform comprehensive testing of data pipelines.

    Throughout the program, students will gain hands-on experience in testing ETL workflows, writing SQL queries for data validation, performing data comparisons, and ensuring compliance with data integrity standards. Key modules include understanding ETL processes, data warehouse architecture, data reconciliation, and automation in ETL testing, preparing students for real-world scenarios in data-driven environments. By working on practical projects and receiving personalized feedback, students will learn industry-standard practices for managing data integrity and optimizing ETL processes.

    Upon completion, graduates will be ready for roles such as ETL Tester, Data Quality Analyst, or QA Engineer, with the skills to maintain and improve the quality of data across complex systems.

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    Modules Covered

    • Overview of Data Warehousing and ETL Architecture
    • Understanding Data Sources, Data Extraction, and Loading Processes
    • Types of ETL Testing: Initial Load, Incremental Load, and Transformation Testing
    • Creating Data Mapping and Data Flow Diagrams
    • Introduction to Data Warehouse Tools and Databases
    • Mini Project: Designing a Basic ETL Process Workflow for a Mock Data Warehouse

    • Writing SQL Queries for Data Verification and Validation
    • Data Comparison Techniques for Source and Target Data
    • Performing Data Aggregation, Joins, and Data Integrity Checks
    • Working with Null Values, Duplicates, and Data Cleansing
    • Advanced SQL for Data Quality Assurance and Troubleshooting
    • Mini Project: SQL-Based Data Validation for ETL Testing in a Data Set

    • Types of ETL Testing: Transformation, Completeness, and Accuracy Checks
    • Handling Missing or Incomplete Data in ETL Processes
    • Data Reconciliation Between Source and Target Systems
    • Error Handling and Reporting for ETL Failures
    • Introduction to ETL Tools like Informatica and Talend for Workflow Management
    • Mini Project: ETL Testing and Data Reconciliation for a Real-World Data Set

    • Introduction to Automation in ETL Testing with Selenium and Python Scripting
    • Setting Up Automated Tests for Data Loading and Transformation
    • Performance and Volume Testing for High-Volume Data Loads
    • Reporting Test Results, Analyzing Data Quality, and Building Reports
    • Final Project: Comprehensive ETL Test Suite for a Simulated Data Pipeline
    • Best Practices for Documentation, Compliance, and Maintenance of ETL Tests

    Learning Path

    Introduction to ETL Processes and Data Warehouse Concepts

    Learn the fundamentals of ETL (Extract, Transform, Load) processes and data warehouse architecture.

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    SQL for ETL Testing and Data Validation

    Master SQL queries to validate data integrity, transformations, and accuracy in ETL pipelines.

    Manual ETL Testing, Data Reconciliation, and Error Handling

    Perform manual ETL testing, reconcile data discrepancies, and manage error handling effectively.

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    ETL Test Automation, Performance Testing, and Final Project

    Automate ETL testing processes, conduct performance testing, and implement your skills in a final project.

    Mini Projects for Hands-On Practice

    Work on small-scale ETL testing projects to gain practical experience and reinforce your knowledge.

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    Final Project and Career Guidance:

    Develop a comprehensive ETL testing solution and receive career coaching to excel in ETL and data testing roles.

    Potential Roles

    • ETL Tester
    • Data Quality Analyst
    • QA Engineer (Data Warehousing)
    • Data Analyst
    • Automation Tester (ETL)
    • Start Date20/05/2025
    • Enrolled100
    • Lectures50
    • Skill LevelBasic
    • LanguageEnglish,Telugu
    • Quizzes10
    • CertificateYes
    • Pass Percentage100%
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    Certificate Program in ETL Testing

    Upon successful completion of the Certificate Program in ETL Testing, you will receive a certificate from Veda IT, validating your skills in ETL testing, SQL-based data validation, and automation for data quality assurance.