While the use of Test data Management (TDM) products is increasing, a majority of companies still do not currently use formal TDM methodologies or tools, and the importance of TDM, or having the right data delivered to the right place, at the right time, for testing purposes is overlooked.

Banks have automated all the ‘low hanging fruit’, leading to the question of how they could automate testing of the end-to-end business processes and make testing more efficient. The absence of proper test data is a major reason why nearly two thirds of business applications reach production without being properly tested.

Following a bad practice on test data management or just using live production data for testing without proper governance is going to result in a major damage on your overall application development and testing lifecycle. Reevaluating the importance of TDM comes with the realization of which are the consequences of weak TDM:

Bugs enter production

Bugs’ escaping during testing and slipping into production is a common outcome when not using test data that matches business requirements in test cases. Even the most efficient testing processes can’t overpass a poor or missing test data.

Applications failing to meet regulatory compliance and privacy rules

In financial services, copying data from production to test applications is a big no due to privacy rules that protect customer information. That means practices of just subsetting or cloning data from production and provisioning it as it is, are not possible for most regulated markets.

Loss of revenue and customers

When not realistic production data is used for product testing, you get bad press and potential revenue loss as incorrect business formulas may slip into production.

Testing and development costs rising

Having to go back in order to fix bugs that got caught later in the delivery process, is definitely time-consuming, expensive and harmful for the customer experience.

Performance and scale issues

A negative impact on performance and scale, like for example an application’s slow performance in production, is an indicator that data does not reflect business or application stress points.

The TDM challenges that Agile teams most often face

Supporting a proper TDM lifecycle within Agile and DevOps is not easy; pressure for speed and absence of an enterprise governance lifecycle process are big obstacles to the way for a healthy continuous test data management life cycle. However, realizing why these obstacles occur can help Agile teams find out which key steps to make next:

DevTest teams lack time to prepare data

Integrating testing into the software development life cycle is already overwhelming for the time schedule of DevTest teams. You need an enterprise test data governance process, supported by small centralized center of excellence (CoE) or an architecture team, for preparing, provisioning and refreshing test data within sprints. Otherwise DevTest teams collapse and fall back on the old processes of no TDM.

DevTest teams can’t wait for test data to be provisioned

In order to avoid days or even weeks of waiting for test data that is ready to use in either manual or automated testing, test data provisioning must be on-demand, self-service and also, several testing cycles must run simultaneously for an application. Each cycle will require a separate test database.

Supporting increasing test automation needs

Agile and continuous integration capabilities accelerate the need for more automated processes and place TDM in the center of application development and testing life cycle. Proper tooling to automate the TDM governance process and support dev teams the fastest the possible.

Deliver projects with secure, compliant and quality data that can be versioned on-demand!

Validata has created ConnectIQ, a new type of cloud-native, Connected, Intelligence DataOps platform, designed to help analysts, data providers and data consumers with a complete, business-model, end-to-end test data management solution allowing banks to shift left testing, eliminate the data wait, reduce data-related defects and fix the ‘Data Gap’ in QA and DevOps. The platform utilizes an integrated data and automation fabric layer, delivering a new approach to creating business value and help clients become data-driven businesses. Test Data Management can no longer be a back-office function. It is a critical business enabler for enterprise agility, security, and efficiency and Continuous Testing Success.