A data warehouse is a composite and collaborated data model that captures the entire data of an organization. It brings together the Data that is Extracted, Transformed and Loaded (ETL) into one single destination. Software testing is predominantly focused on program code, while data warehouse testing is directed at data and information. As a matter of fact, the key to data warehouse testing is to know the data and what the answers to user queries are supposed to be.

This type of testing is getting more and more critical in the business scenario nowadays. The reasons for this are manifold, the prominent ones being increase in Enterprise Mergers & Acquisitions, Data Center Migrations, Increased compliance regulations etc. In this 2 day workshop will get to understand and apply how data warehouse testing is done in a structured and methodical way.

Module 1 – Introduction to Class
Participants | Familiarization with course material | Familiarization with the protocols and timings | Expectation setting and clarifications | Pre-training test for the resources attending the training
Module 2 – Understanding Data Warehouse and ETL ( Extract, Load and Transform)
Introduction Data Warehousing Industry-Databases to DWH – An Evaluation | Data Warehousing Fundamentals, Architecture & Process | Turning Data Into Information Through DWH | Components of Data Ware House | Need of ETL and Introduction to ETL Process | Data Model | Data Quality | Data Visualization | Dimensional Modeling and Star Schema | Case Study From Business Domain Such as Retail, Finance and SCM
Module 3 – Introduction and Key Principles in Testing
Testing Concepts- Verification & Validation | SDLC and STLC | Test Design Methods and Testing Levels
Module 4 – Project Management Overview
Basic Project Management Concepts | Project Management in Software Development and Data Warehousing | Roles and Responsibilities – Enterprise DWH Project
Module 5 – Introduction to Data Warehouse Testing
DWHLC (Data Warehouse Development Life Cycle) and Testing in Each Stages | QA Strategy for DWH – Distinction Between DB Testing and DWH Testing | Planning For DWH Testing | Planning Testing For Common DWH Issues and Risk Analysis | Source-Target Data Mapping – Explained | Topics For Data Warehouse Test Plan
Module 6 – Data Analysis and Test Case Design
Data Profiling Analysis | Business Rules and Data Rules | Potential Sources For Data Errors | Data Quality and Data Profiling | Primary Key Analysis | Pattern Matching | Multi-Column Value Analysis ( Dependency) | Join Testing | Cross Domain Analysis | Test Design Technology | Test Case Components | Requirement Traceability Matrix
Module 7 – Unit and integration Testing
The Need For Unit,Integration Testing | Focus Areas for Unit Testing During Development and Data Loading | Thought For Automation for Unit Testing | Example For Automation For Unit Testing | Phases For Unit Testing | Testing of Individual and Integrated Stored Procedures and Triggers | Test Reporting and Resolution
Module 8 – System Test (Enterprise Integration Test)For DWH
The Need for System Testing by an Independent QA Team | Test plan for Estimation and Scheduling of Test Efforts | Test Condition, Scenarios and Test Cases for System Testing | Data Completeness | Data Correctness | Data Quality | Data Aggregation | Dimensional Modeling(FACT and Dimension Table) | Data Loading Procedures | Transformation and Mapping Rules | Changing Data | Dirty Data | Test Data Preparation | Test Environment Setup | Defect Reporting, Analysis, Tracking and Resolution
Module 9 – Acceptance Testing for Data Warehouses
Identify Scenarios, Environment , Business Users | Scheduling and Execution | Issue Resolution and QA Support | Iterative testing for data warehouse projects
Module 10 – Regression Test for Data Warehouse Testing
Test Cycles and Regression Test Planning | Common Strategies for Selecting Regression Test Suites | Requirement for ETL Regression Test Plan
Module 11 – Performance Test for Data Warehouse Testing
Identify The Performance Concerns | Identify Performance Goals and Metrics for Performance | Identify specific Scenarios for Performance Testing | Setting Up Environment with Test Data | Identify Performance Test Tools and Execution
Module 12 – Thoughts On Automating Data Warehouse Testing
Common Data Warehouse Test Automation Objectives | Data Warehouse Processes – Targets for Test Automation | Examples for Scenarios Used by Automated ETL Tools | Deciding Which Component to Automate | Automation Challenges | Common Solutions | Advantages for Automation | Recommendations | A Sample for Test Automation Solution
Module 13 – ETL TOOLS