What Is Data Management and Why Is It Important?

Digitalization is happening at an even faster pace these days. This means there’s more data than ever before. Organizations can capture all this data to optimize their businesses. In theory, every business can capture data. For example, a hospital captures data about its patients and their diseases, treatments, and much more. A pharmacy can collect sales data and customer data. Any type of data collection is possible!

If your organization doesn’t manage data properly, then the collected data will be scattered and hard to analyze. These problems can be especially tricky if you’re trying to DevOps your data.

To prevent disorganized, inaccurate data, it’s important to learn about data management and its importance. We’ll also discuss common data problems and how to solve them.

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What Is Test Data Management Strategy? A Complete Explanation

chess game with pawns knocked over

As systems become more isolated and autonomous, teams diverge from having shared, centrally managed test data. Legacy test data, which many teams use, can cause problems when it changes without team members’ knowledge. You may get lots of advantages using these more independent systems, but you now have to deal with the pain when your older test data management strategy doesn’t hold up. You need a new way to manage our test data and to make your problems visible.

In this post, you’ll learn how to strategize to conquer test data, just as a general strategizes to conquer a territory. You’ll find out the key elements to a test data management strategy, including what tools to use and how to measure success. We’ll also cover some tactics you can apply to ensure a  strong strategy. Consider this an Art of War for test data management.

I hope this post gives you the confidence to implement your own strategy successfully. Let’s get started!

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A place dedicated to helping people learn more about DataOps. DataOps is the combination of people, process, and products that enable consistent, automated, and secure management of data. Its goal is to improve enterprise IT delivery outcomes by bringing together those that consume the data with those that provision the data.