What Is Data Unification and Why Does It Matter?

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What is data unification? Data unification is the process of bringing data from several different sources together in one centralized location.

In 1871, a collection of small, loosely connected European states came together to form the nation we now know as Germany. That process was known as the Unification of Germany. But it wasn’t easy to unify so many states with slightly different cultures and backgrounds.

In fact, unification is rarely easy, even within the far simpler context of running a business. For example, successful businesses revolve around data. But that data comes from different sources, and it’s a good idea to bring it all together in one location.

That’s the idea behind data unification. But what is data unification, and what makes it so significant? Read on to get an answer to both of those questions.

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What is data unification?
Data unification is the process of gathering data from different sources and bringing it all together in a single location.

Why does unifying data matter?
When your data is spread out across different platforms, formatted differently on each one, it can be very difficult to gain insights from it. You constantly have to jump from one platform to another. Plus, if you want to create a report using multiple types of data from different platforms, you’re out of luck.

Data unification is the answer to that problem. With it, you can pull data from all your different sources and feed it into a single tool. That way, you can easily access it all from one place. Plus, if you want to compare different types of data, you can easily do so within that centralized platform.

Unified data make things far easier and more convenient and it enables you to gain new insights and find new patterns in your data that you’d never have discovered otherwise.

What makes unifying data challenging?
Data unification isn’t always simple — you’re pulling data from all kinds of different platforms, and all those platforms operate in different ways. Because of that, there are several notable challenges that will inevitably crop up when you attempt to unify data. You need to be aware of those challenges before you begin.