Management & streamlining of test data is more than important and test data management remains a critical component in the testing life cycle for software & apps. Test data management or TDM, facilitates test data during various phases of a software development life cycle. The data consumed, tested & modified is constantly put to use during the complete software cycle. The evolution of Test Data Management into a comprehensive service ensures that the need for relevant data during various phases of the software life cycles are taken care of pushing faster go-market times. Get More Insight at: http://softwaretestingsolution.com/blog/test-data-management-managed-service-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

9. Test Data Provisioning

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

12. Test Data Population

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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