In the
technology world, there are a lot of buzzwords that you might be hearing about
but might not understand. Today, we’re going to take a look at test data
management (TDM).
TDM is the process of creating
production-like environments for testing purposes. This includes masking
sensitive data so that it can be used by teams without risk.
What is TDM?
Test data management is a set of processes
that ensure high-quality test data for use in testing applications and systems.
It also ensures that test data is accurate and reflects real-world behavior,
which improves application quality and reduces software errors during
deployment. It’s critical to have test data that accurately represents
production data in order for automated tests to produce reliable results.
Managing large volumes of test data
requires a significant amount of time and resources for the organization to
prepare, maintain, and distribute. This can lead to delays in the software
development process, which can have a negative impact on application quality
and cost. Test data management can help alleviate these issues by reducing the
amount of time spent on preparing test data, providing better access to
realistic test data, and improving the overall quality of test data.
In addition to increasing the
quality of test data, TDM also enables organizations to create more effective
and efficient testing environments. For example, TDM can help organizations
create non-production environments with a smaller storage footprint by
optimizing the amount of space required to store the data libraries. This
reduces costs while still providing a fast retrieval speed for the test data.
TDM Requirements
Testing applications with real-world
data increases realism and helps teams better understand user behavior. But
locating the right test data for each test environment can be challenging. It
requires identifying the different types of data and the locations where it is
stored. Also, ensuring that the data can be easily version-controlled to track
precise changes made during testing.
The best TDM processes ensure that
the data is timely, valid and realistic. This is especially important because
it can impact major functionalities and overall app performance. Poor TDM can
lead to errors during production that result in crashes and slowdowns. This
could damage customer trust and lead to a decline in customer retention.
TDM also helps organizations lower
costs and increase the speed of software deployments and updates. It also
improves the quality and accuracy of the data used in software testing. In
addition, it can reduce security risks by limiting access to sensitive data and
preventing the unauthorized use of information.
TDM Implementation
The key to successful TDM is
implementing well-defined processes that allow testing teams to achieve high
quality test data in an efficient manner. This creates a more cost-efficient
software deployment process, lowers compliance and security risks, reduces
false defects in production, and helps the organization to improve its bottom
line.
TDM requires a variety of tools to
meet the steep demands of modern software projects. The tools must be able to
provision a spectrum of test data to address functional and performance testing
needs. This can be achieved through synthetic data creation, production
extraction and masking, or sourcing from lookup tables. A modern TDM solution
must be able to reduce the number of duplicate copies across environments,
allow for the sharing of common data blocks to minimize storage costs, and
provide workflow automation to eliminate manual processes.
In addition to these benefits, a TDM
approach also ensures that the most up-to-date data is available for testing.
This reduces time spent on data preparation and makes it easier to fulfill
ticketed requests for test data. It also increases the number of test cases
that can be run, which results in more comprehensive coverage and improved
testing effectiveness. It also helps the team avoid costly errors in production
that would otherwise have been discovered by testing and resolved through a bug
fix cycle.
TDM Tools
The best test data management tools provide
a variety of capabilities that help teams address the challenges of managing
large amounts of data and provisioning the right data for each testing type.
These tools offer the ability to automate data subsetting and masking, extract
and load data at the business object level, preserving database and application
relationships, as well as create synthetic or augmented test data. They also
have the ability to store, share and reuse data sets across different projects.
As enterprises shift to DevOps, the
demand for high-quality test data has increased significantly. This new
approach to software development accelerates the time it takes for IT teams to
deliver high-quality applications to market. However, it can lead to a tangled
web of data sources and challenges with meeting compliance and privacy
regulations.
The best test data management tools
enable teams to meet these requirements by providing a single system where all
the relevant and required test data is stored and accessed, making it easy for
testing teams to locate and retrieve it. They can also support multiple test
environments, enabling teams to easily roll back the results of previous tests.
Comments
Post a Comment