Test Data Management System for Stale Data Elimination
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Solution Overview
Problem
Managing large data sets for test environments is challenging due to the time-consuming process of sorting and filtering, which often results in stale data and confusion in transaction data analysis, especially when different environments require different database structures and limitations.
Innovation Solution
A system for test data management that receives test data characteristics, generates secondary copy data from a master copy database, and transmits it to a test environment, allowing for updating and versioning of data to ensure freshness and compatibility with various database structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sorting and filtering large data sets to conform to desired limitations is performed manually, then test data can be retrieved for analysis, but the process becomes time consuming and uses large amounts of computing resources
Solution Approach 1:
The system performs preliminary actions by pre-processing and preparing test data sets in advance based on anticipated test requirements. Data is segmented and stored in a test data repository before actual testing begins, eliminating the need for time-consuming sorting and filtering during test execution.
Solution Approach 2:
The large production data set is segmented into multiple smaller test data sets with different limitations and characteristics. Each segmented data set is pre-prepared and stored separately, allowing quick retrieval without processing the entire large data set during testing.
2Reliability
If data is updated frequently to maintain freshness, then test data remains current, but computing resources and time consumption increase
Solution Approach 1:
The system implements periodic action by updating test data sets at scheduled intervals rather than continuously. The test data repository is refreshed periodically from the production data source, maintaining data freshness while avoiding constant resource consumption associated with real-time updates.
3Adaptability or versatility
If different test environments require different database structures and requirements, then testing can be tailored to specific needs, but data availability is hampered and confusion arises
Solution Approach 1:
The system segments the test data repository into multiple data sets, each tailored to specific test environment requirements. Each segmented data set contains data with limitations and structures appropriate for particular testing scenarios, making it easy to retrieve the right data for each environment without confusion.
Solution Approach 2:
The system creates copies of production data in the test data repository with modifications to match different test environment requirements. These copied and adapted data sets maintain the essential characteristics needed for testing while conforming to specific environment constraints.
Data Source
AI summary
The method for test data management may comprise receiving a test data characteristic; retrieving a master copy data from a master copy database; generating a secondary copy data, wherein the secondary copy data comprises a subset of the master copy data corresponding to the test data characteristic; generating a test copy data, wherein the test copy data is a copy of the secondary copy data; and transmitting the test copy data to a test environment. In this manner, the efficiency and resiliency of the system may be enhanced, and the test copy data may be improved so that the network may function according to approved parameters.