Is your test data management strategy driving your organization forward, or holding it back?
For enterprises striving to meet the demands of DevOps, inadequate test data processes pose challenges like delays, quality issues, compliance risks, and inflated costs. Test data so often becomes a roadblock at the worst possible moment.
Discover What’s Holding Your Organization Back
Tired of delays and inefficiencies in your DevOps workflows?
Learn exactly how speed, quality, compliance, and cost are impacted by ineffective test data management — and explore how the right approach can address these challenges.
This guide offers:
- A comparison of 4 types of test data management: Understand the benefits, uses, and limitations of shared production data, subsetting, synthetic data, and standalone masking — and how they measure up to a modern approach that combines virtualization + masking.
- A breakdown of the 4 key areas test data management will make or break: Development speed, application quality, data compliance, and cost & efficiency. Learn the common practices that hold teams back in these areas, and what your organization should be doing differently.
- Checklists to evaluate test data management at your organization: Is data delivery automated with APIs? Can developers and testers bookmark their data environments? Is masking algorithm-driven? Learn what questions to ask as you evaluate your strategy’s test data processes.
- Two test data management success stories: Learn how a healthcare and a retirement services company transformed their approach to test data — quadrupling the number of non-production environments available to their teams and reducing their monthly data provisioning hours by 70%.
Take Control of Your Test Data Strategy
Don’t allow inefficiency, risk, or outdated methods to hold your organization back. Complete the form to get 10+ pages of insights on building scalable test data management processes that drive innovation and success.