TDM is the formation of data sets that are a reliable imitation of actual data in the production of an organization’s data. This replication is created to help application developers and testers to perform rigorous and valid systems tests, to test applications with real data to check the efficiency and effectiveness of application being developed. Test Data Management software allow the software quality and testing team to have control over the data, files, rules, and policies produced during the entire software-testing life cycle. It is widely adopted by the organizations across the globe for improving testing effectiveness, reducing time and cost, and providing high quality and safe test data through a coordinated and easy-to-manage process. Test data plays an important role in assuring the quality of the application, hence the management and streamlining of test data plays an equally important role in quality assurance of any application that should be released to the customers.

Top 10 Test Data Management software in 2020:

1. BROADCOM LIMITED
2. INFORMATICA
3. IBM
4. SOLIX TECHNOLOGIES
5. SAP
6. IRI
7. DELPHIX
8. HPE
9. CIGNITI
10. INFOSYS

Top free Test Data Management Software

1. TestRail
2. PractiTest
3. Zephyr
4. Tricentis qTest
5. QMetry Test Management
6. SpiraTest
7. Test Collab
8. TestCaseLab
9. Meliora Testlab
10. Eyes

Top Applications of Test Data Management Software

Test management tools help teams in development organise, monitor, and maintain software test results.  Developers are using test management approaches to keep test scenarios results in an archive-like framework, which are then transformed into actionable reports. Some of the applications are:

1. Data subsetting
2. Data masking
3. Data profiling and analysis
4. Data compliance and security
5. Synthetic test data generation
6. Data provisioning
7. Data monitoring

Top features of Test Data Management Software

Management of research data becomes very important during the life cycle of the study. The amount of data that is generated to test the application is enormous. Reporting the results minimizes the time spent on data processing and reporting contributes significantly to the efficiency of a product as a whole. Some of the features are:

1. Identify common test data elements
2. Aging, masking and archiving
3. Prioritization and allocation
4. Report generation and dashboards
5. Creating and implementing business rules
6. Automation suite for master data
7. Masking, archiving and versioning

The MicroQuadrant matrix provides information about the major players offering Test Data Management software and services, and outlines the findings and analysis on how well each market vendor performs within the predefined criteria. The MicroQuadrant matrix highlights the top vendors in the TDM market. Vendor evaluations are based on 2 broad categories: strength of product portfolio and business strategy excellence. Each category carries various criteria, based on which the vendors have been evaluated. The evaluation criteria considered under strength of product portfolio include breadth and depth of product offering, product feature and functionality, product differentiation and impact on customer value, and product quality and reliability. The evaluation criteria considered under business strategy excellence include geographic footprint, channel strategy and fit, vision alignment, and effectiveness of growth strategy.

CA Technologies, Informatica, IBM, IRI, and Solix are the leading players in the TDM market and are recognized as the visionary leaders. They have a strong portfolio of Test Data Management software and associated services. These vendors are marking their market presence by offering solutions that are required by most of the organizations. These vendors have robust business strategies to achieve continued growth in the market.

Capgemini, Cigniti, Cognizant, Doble, HPE, Infosys, SAP, SQS, and Wipro are recognized as the dynamic differentiators. These companies have strong business strategies with extensive channel network and market reach. Over the years, the dynamic vendors have been consistently generating positive revenue growth in the TDM market with their product offerings. Moreover, their market position is enhanced by the organic and inorganic strategies undertaken by them over the period.

DATPROF, Delphix, and MENTIS are recognized as the innovators in the TDM market. They have a wide portfolio of Test Data Management software and services, and have the potential to build strong business strategies to be at par with the visionary leaders. These vendors have been providing TDM offerings as per the customers’ demands. Innovators have been at the forefront in deploying their solutions for the niche and custom requirements of the clients.

Actifio, Compuware, GenRocket, Original Software, TechArcis, TestingXperts, Ekobit, and Zephyr are recognized as the emerging players in the TDM market. The emerging companies specialize in offering highly niche and tailor-made solutions and services to their clients. These companies help enterprises not only build and manage the content-driven processes but also support new ways of working to drive the business results.

Test Data Management softwares serve the applications, such as data subsetting, data masking, data profiling and analysis, data compliance and security, synthetic data generation, and others (data provisioning and data monitoring). The replication of the exact data used in the production system in the testing environment is crucial for the successful operation of certain applications. A system contains data in various formats and types. Various rules need to be applied to various types of data to ensure the correct flow of data. TDM applications extract the subset of the data from the collected data and masks the sensitive data. Then, it compares the accuracy of the data carried out by the application.

DATA SUBSETTING

Data subsetting is the process of sampling a part of the production database and replicating it to the test environment. Data subsetting reduces storage costs, data refresh time, and infrastructure costs. The primary goal of the data subsetting solution vendors is to provide simple and effective ways to slice the data from a large production data. Data subsetting accelerates the test process and development cycles, thereby creating the right-sized test systems. A scalable data subset from heterogeneous applications supports a wide variety of databases and applications. Data subsetting creates smaller, targeted databases from large, complex databases.

DATA MASKING

Data masking is a process of creating similar, but inauthentic versions of the organization’s production data, which can be used for data testing. Data masking is used to protect the actual data while keeping the functional behaviour intact for the testing purpose. Most organizations have strict security controls to protect the production data in their databases. To maintain the regulatory compliances, real data exposure to IT vendors is impossible, and therefore alteration of the original data becomes a mandate. However, the format of the data remains the same. The original data may be altered in a number of ways, including encryption, character shuffling, and word substitution.

DATA PROFILING AND ANALYSIS

Data profiling is a process of examining the data from the existing databases and collecting useful information from the data. Data profiling helps in improving the ability of the search data, assigns it to a particular category, checks the pattern of data, examines the risks associated with the data, discovers the functional dependencies of the data and analyses the challenge to the data-sensitive process. Data profiling assists in clarifying the data structure and its relationship with the overall business requirements. Data profiling uses minimum, maximum, mean, median, mode, percentile, and other such calculations to discover any anomalies and varying values. Data profiling also improves the data quality, shortens the implementation cycle and improves data understanding. The analysis of data in the production systems helps get a clear picture of the data consistency in an enterprise application. The analysis of data in the production system for each category and format is segregated in the test data to set up rules for data routing for each type of data in the software application. Data analysis enhances a better understanding of the data characteristics at each stage of data processing in the application.

DATA COMPLIANCE AND SECURITY

The amount of data managed in an organization’s database is tremendous and will only multiply in the future. Moreover, IT environments are becoming increasingly complex and require more data for testing. To define and classify the sensitive data and understand the flow of application data across the other applications and databases, the data compliance and security application is essential in an information-sensitive environment or industry. The data compliance and security application prevent private and sensitive data from being breached. Every industry and department needs to adhere to various compliances and secure data at each level of hierarchy in an organization, for the data flow of an application.