What is TDM (test data management)? Test Data Management (TDM) refers to the supervision and administration of enterprise architectures, methods and policies to successfully manage the value of the data and information lifecycle in-house or from outside vendor sources. TDM makes use of data sets produced to mimic actual data that is used by systems and applications developers to perform valid and rigorous system tests. True production data cannot be used for testing due to security and regulatory concerns, but the data utilized for testing needs to be as identical as possible to the original data to prevent issues when it finally goes into production. Data masking techniques are used to obfuscate personal identifiable information but in a way that still maintains the data formatting and other data properties so it doesn’t affect testing results. Prior to TDM, application teams would have to manufacture data for testing and development in an unstructured, siloed fashion.
Test Data Management is important to PeerSpot users who are tasked with managing data across an entire organization. Standard Operating Procedures (SOPs) are put in place in order for Test Data Management to be consistent with guidelines and procedures developed for the daily functioning of a company. IT managers and DevOps are looking for robust test automation that is flexible, dynamic and able to be efficiently deployed. In order to adhere to company directives, IT managers and DevOps use various key software on-premises, in the cloud, the hybrid cloud and across mobile devices. Test Data Management should deliver data security and copying speed, and increase virtual and automation efficiency. The strategy for developing and facilitating TDM implementation should address variables of data verification, data confidentiality, disk space and prolonged test duration.
IT managers and DevOps align with critical data compliance and confidentiality. Because integrated, sensitive data, business classification and policy-driven data masking are integral to security, PeerSpot users look for a safe and secure environment in which to test data and prefer that Test Data Management ensures that each test begins with a consistent data state, important in maintaining predictable data at the end of testing. Overseeing visible test results and the effects on a database is vital and would be almost impossible to achieve manually. IT and DevOps need to effectively monitor data in order to serve Enterprise needs and outcomes, therefore Test Data Management deployment is the best solution for maintaining protocol and serving the professionals involved.
TDM is necessary for organizations because it allows them to perform business-critical processing of sensitive data. With test data management, organizations can protect highly sensitive data and customer information that could otherwise cause extreme damage if exposed, especially for industries where breaches are more common, such as healthcare. In addition, test data management allows companies to create higher quality software that can perform reliably on deployment and ensures the prevention of rollbacks and bug fixes. Beyond that, TDM minimizes an organization’s security and compliance risks.
With respect to data, organizations need to have test data management strategies in place to minimize the degree of some of the most common challenges that can occur. Below are a few test data management strategies:
Test data management life cycle refers to the different stages data goes through before reaching its end or before starting a recurring life cycle. During its lifecycle, test data goes through the following phases:
When trying to provision and manage test data, pitfalls and challenges are common. Below are some challenges you may experience:
A test data management tool is a tool primarily used to organize and integrate data in all phases of production. The main goal of a TDM tool is to provide high-quality data for systems and application developers to use during testing.
When researching which TDM tool will be best for your specific organization, it is worth considering the following features:
Some of the key benefits gained from leveraging TDM systems are:
Other notable benefits include reduced data refresh cycle, traceability of test data to test cases to business requirements, gaining a more cost-efficient software deployment process, and obtaining customized test data for different kinds of testing such as functional, integration, performance, security, etc.
TDM is necessary for organizations because it allows them to perform business-critical processing of sensitive data. With test data management, organizations can protect highly sensitive data and customer information that could otherwise cause extreme damage if exposed, especially for industries where breaches are more common, such as healthcare. In addition, test data management allows companies to create higher quality software that can perform reliably on deployment and ensures the prevention of rollbacks and bug fixes. Beyond that, TDM minimizes an organization’s security and compliance risks.
With respect to data, organizations need to have test data management strategies in place to minimize the degree of some of the most common challenges that can occur. Below are a few test data management strategies:
Test data management life cycle refers to the different stages data goes through before reaching its end or before starting a recurring life cycle. During its lifecycle, test data goes through the following phases:
When trying to provision and manage test data, pitfalls and challenges are common. Below are some challenges you may experience:
A test data management tool is a tool primarily used to organize and integrate data in all phases of production. The main goal of a TDM tool is to provide high-quality data for systems and application developers to use during testing.
When researching which TDM tool will be best for your specific organization, it is worth considering the following features:
Some of the key benefits gained from leveraging TDM systems are:
Other notable benefits include reduced data refresh cycle, traceability of test data to test cases to business requirements, gaining a more cost-efficient software deployment process, and obtaining customized test data for different kinds of testing such as functional, integration, performance, security, etc.