5 Best Practices For Test Data Management

 


Modern application development practices leverage the cloud features and benefits. However, these modern practices add unique hurdles that require certain standardised governance for test data practices.

Cloud functionality has empowered DevOps teams with incredible flexibility in software development. With code infrastructure and automated CI/CD pipelines, your development teams can achieve repeatable software delivery processes for enhanced efficiency in workflows and improved productivity.

However, test data management has failed to evolve with the modern agile techniques of application development. The outdated waterfall test data management approach negatively affects the release speed.

In fact, the modern cloud application development methods increase complexity in outdated data management techniques. 

Get the best professional services for TDM and IT portfolio management to reduce organisational bottlenecks and deliver high-quality applications on time. 

The data management challenges include: 

  • Struggling to maintain test data compliance 
  • Supply unable to meet exponential demands for test environments 
  • Incompetent data management infrastructure and processes unable to account for and maintain diverse data stores and distributed locations. 

So, what’s the solution? With the best test data management practices, you can overcome the data procuring and processing hurdles while staying compliant and accelerating the software delivery velocity.

Also Read: Test Data Management And Automation: Why Is It Necessary?

5 Best Practices For Test Data Management 

Maintain The Pace With Automated CI/CD Workflows 

Even minute delays in data delivery can disrupt the breaks microservices efficiency. Introducing automation for test data management improves timelines for the entire software delivery lifecycle. 

With automation, you can substantially limit the wait states of the prolonged period, such as from weeks, or months, to just a few minutes or just seconds. 

Limit Expenditures With Ephemeral Test Environments 

Implementing a single API call for data provisioning while you set up ephemeral test environments can enhance productivity and reduce the control cloud expenditures. 

Deliver High-Quality Software By Running Tests With Production-Quality Test Data 

Automating data delivery translates into a constant flow of production-quality test data into your relevant test environments. If your team uses outdated or stale data just to accelerate the release train, the software quality will deteriorate. 

Eliminate Compliance Challenges In Test Environment 

Sensitive data classification and masking for use in test environments is a fundamental element of a comprehensive data governance program. API-driven masking approach efficiently de-identify data while maintaining referential data integrity for accurate testing. 

Enabling Data Portability Within And Throughout The Cloud Database 

When you establish data portability, you can easily transport lightweight virtual clones when production and test environments aren’t co-located. Additionally, virtual databases can share similar data blocks to minimise data footprints by 10x. 

Conclusion 

A cloud-based software development approach introduces enhanced speed and agility to your software delivery lifecycle. However, like any advanced concept, cloud architecture also involves new and evolving complexities for efficient data delivery into test environments. 

Introducing modern concepts and eliminating the outdated siloed test data management using the best practices ensures constant access to safe, high-quality data. Additionally, the enhanced speed of the data flow can keep up pace with the accelerated pace of DevOps techniques.

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