The amount of data in the world keeps growing, making it increasingly easy for important information to slip through the cracks.

Tolga Tarhan, CTO at the cloud provider Onica, said those “data black holes” are only becoming more of a problem as time goes on.

“IT departments aren’t necessary for spinning up new systems anymore,” Tarhan said, “which means it’s easy to lose track of what data is being created and where it’s stored.”

SEE: 10 things companies are keeping in their own data centers (free PDF) (TechRepublic)

Even organizations without a Shadow IT problem face issues of legacy systems that keep data in silos and other disparate systems. With no one able to present a holistic view of organizational data black holes emerge where data should be, but isn’t (even though it may exist).

Black holes lead to poor analytics, which can in turn lead to devastating organizational missteps. In other words, it’s a serious problem in a business age increasingly dominated by well-analyzed data.

Data black hole red flags

Like a black hole in space, it can be tough to spot data black holes until it’s too late. If you’ve noticed any of these three signs at your organization you may already have data black holes—but it isn’t too late.

1: You don’t know where all your data is. Ask yourself two questions: Who in your organization is producing data that could be used in an analysis; and where do they store that data? If you don’t know the answers to either question you may have data black holes.

2: You don’t know who has access to data, or how it’s secured. Data shared casually can end up being damaged. If you don’t know who has access, and how data is kept safe, there’s no way to know if it’s intact or correct.

3: You don’t know how your data is retained and protected from disaster. Is your data kept on-premises or in the cloud? Is it backed up off site? If you’re not sure of either of these, or if you’re unclear as to if all data is being stored in one location, you probably have black holes.

How to eliminate data black holes

Tarhan’s solution for data black holes is simple: Put it all in one big data lake.

Because data lakes are unstructured, none of the data needs to be sorted, organized, transposed, or otherwise changed: Just get it in the lake and worry about what to do with it afterward.

“The most important first step is to get all of your data in one place, regardless of its format. Once you have it all centralized then go look for data scientists to make sense if it all,” Tarhan said.

“Lots of companies don’t realize they have black holes until they start a major analytics project,” Tarhan said. Finding that out during a major project could be a disaster for many organizations.

Before you even decide to undertake a business analytics project start at square one: Find your black holes and get all your data in one central location.

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