Data Warehouse and ETL Testing Fundamentals for QuerySurge
Course Summary
This one day course is designed to familiarize business professionals in the Data warehouse and ETL space with the basics of testing and validating. This course focuses on getting professionals the knowledge required in order to successfully test and validate data warehouses and ETL processes.
Intended Audience
- Manual Testers
- Automation Engineers
- Quality Assurance Analysts
- Developers
- Project Managers
- anyone involved with providing software quality for data warehouses
- Course Objectives
- Course Outline
At the end of the course, you will be able to:
- Describe the purpose of a data warehouse and the ETL process
- Determine an appropriate testing strategy
- Understand a source-target mapping document
- Describe an approach to test each business rule
- Recognize the different testing methods
- Determine appropriate sample sizes and data permutations
- Explain the different data error types
- Star Schema
- Snowflake schema
- Galaxy schema
- Have knowledge of the different testing tools
- Understand the importance automated testing
Introduction
- What is big data?
- What is a Database?
- What is a Data Model?
- What is a Data Warehouse?
- What is ETL?
- What is a Data Mart?
- What is Business Intelligence (BI)?
- What are BI tools?
- Transactional vs. analytical databases?
- Data Warehouse table types
- Resources Types Involved
- Main Structures
- Introduction
- Test points and legs
- Single Leg strategy
- Multi leg strategy
- Single Leg vs Multi Leg
Principles of ETL Testing
- Data Mapping Document
- Testing methods
- Visual Compare
- Record Counts
- Minus Queries
- Automation
- Working with flat files
- Excel Files
- Comma delimited files
- Fixed width files
- XML Files
- How much data to test?
- Testing incremental loads
- Multiple Sources
- Selective column and row type
- Translation
- Lookups
- Transpose
- Field Splitting
- Field Merging
- Calculated and Derived
- Table Splitting
- Assess: Test Strategy
- Data Permutations
- Test Data Sampling
- Test Points
- Leveraging Test Tools
- Plan: Test Planning
- Test List
- Resource Estimation
- Prioritizing
- Scheduling
- Defect workflow
- Test Plan
- Design: Test Case authoring
- ETL Manual Test Creation
- Visual Compare
- Record Counts
- Minus Queries
- Home Grown
- ETL Automated Test Creation
- QuerySurge
- BI Report Test Creation
- Execute: Test Case Execution
- Manual Tests
- Automated Tests
- Evaluate and Improve
- Lessons learned
- New Test cases
- Missing Data
- Truncation
- Type Mismatch
- Null Translation
- Misplaced Data
- Extra records
- Logic Issues
- Duplicate Records
- Precision
- Sequence
- Rejected Rows
- Undocumented Requirements
- Simple Issues
Transformation Types
Testing Process
Defect Types
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