Author: DataOpsZone

As information systems advance, data generation increases. There was a time humans owned and generated data. But for the past few years, the technology trends have been changing. With these changes, the definition of data has broadened. For instance, it’s not necessary for data to have a structure, like having the same data type or organization pattern. In other words, the data may contain different data types that are randomly arranged. Machines can generate information as well. Data can also exist outside the corporate boundaries. Data is growing as time goes by. We’re using the term “big data” to describe this portfolio of data. So, while thinking about how this data can be managed for better reporting, you may wonder, how does big data come into the picture?

In this post, we’ll discuss how big data has improved the audit process. But before that, we’ll get to know what big data is.

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Testers have quite a lot of responsibilities. Often, when a tester thinks that they’ve covered all the test case scenarios, a regression defect appears. Usually, it appears at a late testing phase or when some new code changes are pushed in the application—the worst case being when the tester from the client side catches these defects in the production environment. Problems like this arise when a proper test data management (TDM) strategy isn’t in place. Managing data is, in fact, the hardest part of the software development life cycle (SDLC).

In this post, we’re going to learn about TDM in detail. We’ll get to know what test data and test data management are. Also, we’ll check out why TDM is important and the challenges that come along with it. Let’s dive into the details.

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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.

Continue reading “What Is Data Management and Why Is It Important?”