What is ETL Testing?
ETL Testing refers to the process of validating the data that is extracted, transformed, and loaded (ETL) from various sources into a target data warehouse or database. The main goal of ETL testing is to ensure that the data is accurate, consistent, and reliable after the ETL process. This involves checking the data at various stages of the ETL pipeline, including:
- Extraction: Verifying that the data extracted from source systems is complete and correct.
- Transformation: Ensuring that data transformations are applied correctly and that business rules are followed.
- Loading: Validating that the data is accurately loaded into the target system and is available for analysis.
Benefits of ETL Testing:
- Data Accuracy: Ensures that the data is accurate and matches the source data, reducing the risk of errors in reporting and analysis.
- Data Consistency: Validates that the data remains consistent across different systems and formats, which is crucial for maintaining data integrity.
- Identifying Data Quality Issues: Helps identify issues related to data quality, such as duplicates, missing values, or incorrect formats, before they affect business decisions.
- Business Rule Compliance: Confirms that the data transformations adhere to defined business rules, ensuring that the resulting data meets business requirements.
- Improved Performance: Optimizes ETL processes by identifying bottlenecks or inefficiencies, leading to faster data processing and better performance.
Why Choose Ignitesofttech?
- Real-Time Training from Experienced Professionals
- Daily Recorded Sessions
- Ongoing Technical Support After Course Completion
- Hands-On Project Implementation
- 100% Real-World Projects and Use Cases
- Curriculum Reflecting the Latest Industry Trends
Course Curriculum
• Data Warehouse Architecture
• Data Mart
• Data Warehouse Schemas: Star Schema and Snowflake Schema
• Key Objects in Data Warehousing: Dimension Tables and Fact Tables
• Slowly Changing Dimensions (SCD): Types 1, 2, and 3
• Differences Between OLTP and OLAP
• Software Development Life Cycle (SDLC) and Software Testing Life Cycle (STLC)
• Agile Methodologies
• Waterfall Model
• Team Architecture
• Role & Responsibility of Testing Team
• Environments in software industry
• Software Development Life Cycle(SDLC)
• Software Testing Life Cycle(STLC)
• Defect Life Cycle
• Scrum Events
• Testing Methods
• Types of Testing
• Severity & Priority
• Testcase design, Testcase creations and Test Plan
Data Definition Language (DDL)
Data Manipulation Language (DML)
Data Control Language(DCL)
Transactional Control Language (TCL)
Data Sorting
SQL Operators
Date Expressions
Order by clause
Distinct by clause
SQL Functions
NVL(Null Value Functions)
SQL Constraints
SQL Joins
SQL Special Joins
SQL aggregate Functions
SQL Set Operators
OLAP Features
SQL Stored Procedure
SQL Index etc., . .
• Structure Validation
• Count Validation
• Transformation Logic Check
• Data Validation
• MINUS Query Check
• Duplicate Check
• Error Logic Check
• Referential Integrity Constraint (RI) Validation
• Scenario Testing
• Derived Value Checks
• Default Value Checks
• Data Integrity Checks
• Basic Checks at ETL Phases
• Data Migration Testing
• Sample Testing and Scenario Testing
• Batch Job Testing
• Inbound Testing
• Outbound Testing
• ETL Testing Tasks
• Test Case Design
• Preparation of ETL Test Scripts
• Environment Setup
• Test Execution
• Peer Review of QA Deliverables
• ETL Testing Validations
• Extraction Phase Testing
• Transformation Phase Testing
• Loading Phase Testing
• SCD Type 1 Testing
• SCD Type 1 Testing
• SCD Type 2 Testing
• SCD Type 3 Testing
• SCD Type 4 Testing
• SCD Type 5 Testing
• SCD Type 6 Testing
• Basics of ETL Development Tool
• Mappings in ETL development Tool
• Running jobs in ETL development Tool
• Project -1
• Project-2