Test Data Management a Managed Service for Software Quality Assurance
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The document outlines the significance of test data management (TDM) in enhancing software quality assurance through better analysis, development, testing, and maintenance of test data. It highlights the lifecycle of TDM, including profiling, planning, provisioning, and population, while addressing challenges such as data privacy, compliance, and synchronization among teams. The content also suggests that effective TDM can lead to improved data quality, reduced costs, and faster time-to-market.
Test Data Management a Managed Service for Software Quality Assurance
- 1. Test Data Management MANAGED SERVICE FOR SOFTWARE QUALITY ASSURANCE
- 2. Introduction • Management & Streamlining Of Test Data Important • Test Data Management • Analysis • Development • Testing • Maintenance
- 3. The Importance of Managing Test Data • Relevant Test Data Improves • Reliability & Quality Of Software Quality Testing • Frequent Changes Require A Re-look • Constant Refreshes • Versions
- 4. TDM – The Growing Importance Generates test Data Setup for new apps Synchronizes Test Data Across Apps Brings Agility to Test Data Management •Revises Test Data for Ugrades •Maintains & Supports all Data Needs Streamlines Feedback Management to Make Data Better
- 5. Challenges for Test Data Management • Improper Analysis • Frequent Changes • Unexpected Test Data Requirements • Ensuring Data Privacy & Confidentiality • Adhering To Regulatory Compliances • Keeping Version Control Mechanisms • Provisioning Back-ups • Preventing Test Data Redundancy • Synchronization Between Teams • Application Development • Testing & QA • Infrastructure • Database Facilitators
- 6. The TDM Lifecycle Test Data Profiling • Comprehend Data Sources • Understand Requirements of Test Data Test Data Planning • Devise Test Data Strategy • Identify Tools for Test Data Management Test Data Provisioning • Create Sub data sets • Mask Test Data Test Data Population Populate Test Data Continuous Refresh for Test Data Devise Backup Schedules
- 7. Test Data Profiling • Enterprise Business • Mapped To Data Structures • Test Data Requirements Be Identified Based On These • Test Data Profiling • Ensures A Sync
- 8. Test Data Planning • Understand The Intricacies Of The Production Scenario • Evaluate Test Cases
- 10. Sub-setting Data from multiple sources • Identifies Realistic Data • Encompassing As Many Scenarios & Combinations • Small And Allow Quick Testing • Enforces Boundary Conditions & Error Possibilities
- 11. Keeping the Data private • Data Masking • Hides Actual Data • Brings Anonymity
- 13. Automated Test Data Generation & Comparison Keeping Check On Anomalies & Inconsistencies Of Test Data Increases The Speed & Efficiencies
- 14. Periodic Refresh of Test Data • Monitoring Test Data • Get Away With Any Divergences • Ensure Optimal Testing Environments
- 15. Rules of Thumb Manage the Test Data Environment As Similar As Possible To The End User Environment Address Practical Needs Explore Practical Platforms Virtualization Or Cloud Environment Easily Configurable
- 16. Yes or No for Test Data Management NO •Inadequate testing means a low quality solution •More time-to-market •Rising costs because of random test data with no strategies •Non-compliance with regulatory norms for data privacy Yes •Reduced cost in test processes •Improved data quality resulting in better systems •Timely data delivery, with faster test executions reducing the time-to-market •Methodical adherence to regulatory norms on data confidentiality
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