Optimization Of Test Data Management

Test Data Management

Agile development based on the DevOps approach makes companies more adaptable – at the same time costly software errors and data misuse are prevented. Application development drives business success and benefits the competitive position of companies. It is not for nothing that software availability is referred to as the “third platform” in companies. This stands for multimodal provision and use of environments such as mobile computing, cloud, social networks, big data and analytics.

The third platform is now evolving to include “embedded” environments, “systems of systems” or the “Internet of Things”. New models and approaches for software development are required for successful implementation in the company. These include agility and DevOps for software delivery in complex environments, where frequent, rapid, iterative testing and continuous release management are required. The basis for this is good quality and efficient management of the life cycle of the data, from the application idea to software testing and use. The process extends from using the data for various purposes throughout its lifecycle to making the data available after the application has been retired.

Four Challenges – That Can Influence Software Projects In Companies


Traditional methods of making copies of data for development, user acceptance testing, and quality assurance are sluggish. They slow down the production systems and the processes can take up to three weeks. Typically, teams either need to pull data from backup systems or subject their production systems to large I/O volumes, which impacts live operations and is not a desirable option. All in all, the traditional way is time-consuming and a great burden and challenge for the teams and systems.


Because it is time-consuming and difficult to access large amounts of real, up-to-date data, test and development are often out of sync with the “reality” of operating and production system data and actual levels of complexity. As a result, developments have to be revised, which costs more valuable time.

Maintain Control And Keep An Eye On Costs


Compliance with legal regulations and measures to protect customers requires the obfuscation of sensitive data. In addition, there are security risks if there is no control over the data. Because development and testing teams depend on what data they can get, it is often stored in locations that are most convenient for the user.


Companies often combat typical problems by building large, expensive hardware infrastructure dedicated only to development environments. Here they duplicate complete data copies for multiple teams. However, the data you need may not be available in the required forms for all the teams that need it. Even if hundreds of terabytes are consumed for physical data copies, it still cannot fully meet the needs of some developers, testers, or contractors.

The Following Points Serve As Recommendations For Action For Companies

  • Assess current strategies for your data, development and quality from conception to delivery
  • Initiate the transition to effective data lifecycle development processes and the use of automated tools
  • Establish a combined data and quality lifecycle strategy that evaluates, adapts, and implements test data management automation to achieve application quality, compliance, and customer support benefits
  • Drive toward an effective quality management and data lifecycle strategy to reduce costs, increase business efficiency and agility, and empower your organization to face competitive challenges.

Also Read: Open Source: Digitization Needs Open Standards

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