Data masking and tokenization both protect sensitive data by replacing it with something safer to handle. They solve different problems, though, and choosing the wrong one adds cost or leaves a gap. This post defines each clearly, sets them side by side on the criteria that drive the decision, and gives you a framework for […]
In July 2024, a single software update affected roughly 8.5 million Windows devices. CrowdStrike’s preliminary post-incident report found that a flaw in the company’s Content Validator let a faulty update pass integrity checks it should have failed. That is a pattern behind many go-live failures. A verification step gets skipped, compressed, or trusted when it […]
For years, CA Test Data Manager was one of the default answers in the test data management category. That context changed when Broadcom acquired CA Technologies in 2018, a deal Broadcom valued at roughly $18.9 billion in equity and one that CA’s own legal counsel described as the largest sale of an enterprise software company […]
Every release carries risk. A team can test in staging, review the code, and run the deployment pipeline successfully, yet still introduce a regression, broken integration, or unexpected performance issue in production. When that happens, the team needs a reliable way to restore service. A deployment rollback returns an application or service to a previously […]
Why Test Data Just Became an AI Governance Problem In late August, Thoughtworks published a lengthy field guide on what it takes to make enterprise data ready for agentic AI. Its central claim is simple: a human analyst who runs into a number that looks wrong pauses and double checks it, while an autonomous agent […]