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.
The course is appropriate for both Novice and Experienced Software Engineers under the following category:
Quality Assurance Specialists
Project / Test Managers
Project / Test Leads
Participants are expected to have basic knowledge on software Testing.
After the completion of the course, the participants would be able to:
Review the fundamental concepts of data warehousing and its place in an information management environment.
Learn about the role of the testing process as part of software development and as part of data warehouse development.
Learn about test strategies, test plans and test cases – what they are and how to develop them, specifically for data warehouses and decision support systems
Create effective test cases and scenarios based on business and user requirements for the data warehouse
Plan and coordinate usability testing for data warehousing
Conduct reviews and inspections for validation and verification
Participate in the change management process and document relevant changes to decision support requirements
Topic Area 01: Introduction to Class Participants | Familiarization with course material | Familiarization with the protocols and timings | Expectation setting and clarifications
Topic Area 02: 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
Topic Area 03: Introduction and Key Principles in Testing Testing Concepts- Verification & Validation | SDLC and STLC | Test Design Methods and Testing Levels
Topic Area 04: Project Management Overview Basic Project Management Concepts | Project Management in Software Development and Data Warehousing | Roles and Responsibilities – Enterprise DWH Project
Topic Area 05: 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
Topic Area 06: 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
Topic Area 07: 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
Topic Area 08: 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
Topic Area 09: Acceptance Testing for Data Warehouses Identify Scenarios, Environment , Business Users | Scheduling and Execution | Issue Resolution and QA Support | Iterative testing for data warehouse projects
Topic Area 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
Topic Area 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
Topic Area 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
Topic Area 13: ETL TOOLS Introduction to ETL TOOLS | A Sample Case Study for AN ENTERPRISE DATAWARE HOUSE PROCESS
Topic Area 14: Case Study, Evaluation Test and Hands on Sessions