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    You are at:Home » Main Steps of Test Data Management and Implementation Challenges
    Technology

    Main Steps of Test Data Management and Implementation Challenges

    Amir KhanBy Amir KhanAugust 16, 2021Updated:March 1, 2023No Comments5 Mins Read
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    Last Updated on March 1, 2023 by Awais Aftab

    Before deploying software, it is tested aggressively to ensure performance and efficiency under challenging environment.  It is important to provide high-quality data so that all possible scenarios including exceptional circumstances can be tested. Test data management (TDM) process aims at providing test data for software testing purposes. Since test data is responsible for ensuring quality and performance in a software, therefore this process holds a significant importance. Through TDM process sufficient amount and formats of test data are created, and are made available for testing whenever there is need.

    This article elaborates various steps involved in Test Data Management and different challenges technicians encounter while implementing this process.

    1. Data creation

    The process of Test data Management begins with actual data generation. There are a number of tools and strategies available for acquiring data. While data can be cloned i-e copied from real data, it can also be generated synthetically. The generation of synthetic data is done to meet the requirements of test data, and it is very much similar to the real data.

    2. Data obfuscation

    If you have decided to use real data then it is important that the TDM takes care of sensitive data such as passwords, identity information, financial information, token and so on. The obfuscation of data is the second step of Test Data Management, and various techniques such as data masking and data anonymization are used to protect sensitive information from leaking.

    3. Data sub-setting

    In the next step, TDM accesses a required chunk of data during production cloning. This process is also known as data slicing. For effective testing, you need to access some data. In the testing phase, you might not require all the data, therefore only a data sub-set is accessed because it reduces the storage need and infrastructure costs of accessing the whole set of test data.

    4. Data Delivery

    In the next phase, the data subset is prepared to be used in test environments. It is the responsibility of the Test Data Management to ensure that the test data is made available at the right times and in the required format.

    5. Integrations

    In the stage of integration, the test data delivery is automated and integrated with the existing tool-chain, which is then made included into the CI/CD pipeline.

    6. Versioning

    An effective Test Data Management process performs versioning of the test data repositories. This stage offers a variety of benefits. It ensures effective and efficient test iterations, scenarios, test cases, and various changes made to the data.

    The objective of Test Data Management is to make the testing phase easy and convenient. However, this process itself comes with its own share of baggage and challenges. Some challenges encountered during the implementation of TDM are listed below.

    1. Increased Cost of Thorough testing:

    If instead of data slicing, discussed in step 2, you decide to perform complete data testing, then that can increase the cost of testing significantly.

    2. Invalid Test data

    If you have decided to use real data which is obsolete or which is no longer required, it is quite possible that the data set is outdated or invalid. It does not suffice the testing requirement and can lead to ineffective testing or poor results.

    3. Test data corruption

    Many times, the identical test data is used by various testing teams. The usage of same data can result in data corruption, compromising the effectiveness of testing.

    4. Data Protection and compliance

    As required by the regulatory authorities, the real data has to be protected to avoid data leakage. Compliance to data protection regulations can raise the cost of test data management.

    5. Storage and infrastructure costs

    In order to keep test data stored, the organization has to incur high storage and infrastructure costs. It is often quite expensive to store and maintain huge amount of test data which can be provided in the hour of need

    Final Words

    Having an experience of more than a decade in the IT industry, GenRocket is fully aware of the requirements and challenges involved in efficient Test data Management. Get the expertise of professionals for testing your software’s, at affordable costs by GenRocket. We are strict adherents of Data Protection Regulations and make sure that we remain compliant to it during the testing phase of software.

    Read more: Test Preparation Market Overview, Industry Top Manufactures, Market Size, Opportunities and Forecast by 2021-2026

    Which of the following is the greatest challenge in using test data?

    The use of test data is an essential aspect of software development and quality assurance. However, there are several challenges associated with using test data that can affect the accuracy and reliability of the testing process. Of these challenges, the greatest one is the ability to create test data that accurately represent real-world scenarios.

    One of the primary purposes of testing is to identify and fix defects in software. To do this, test data must be designed to accurately represent the various scenarios that a user may encounter when using the software. This requires a deep understanding of the software’s functionality and the ability to simulate real-world scenarios accurately. Creating test data that accurately represent real-world scenarios can be challenging, as there are often countless variations of user behavior and environmental factors that must be considered.

    Another challenge associated with using test data is the need to keep it up to date. As software changes and evolves, so too must the test data used to test it. Failure to keep test data up to date can result in inaccurate testing results and can make it difficult to identify and fix defects in a timely manner. This challenge can be particularly difficult to overcome in large, complex software projects where there are numerous changes and updates occurring simultaneously.

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