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How to Prevent Data Black Holes from Swallowing your Organization Whole

In this special guest feature, Tolga Tarhan, Chief Technology Officer at Onica, points out that as data accumulates in an environment, applications and services that rely on that data will naturally be pulled into the same environment, creating a data black hole. As CTO, Tolga leads the technology vision, driving innovation, and strategy for product and service offerings. With two decades of experience leading product and engineering teams and as a hands-on technologist at heart, he brings unique insights to customers undertaking the journey to the cloud. Prior to Onica, Tolga served as an executive technology leader in the SaaS, IoT, and medical device industries. Tolga holds an M.B.A. from the Graziadio Business School at Pepperdine University.

Enterprise data is growing at a rate of 63% per month — companies are generating and storing more data than ever before. This is good news, since data can be an enterprises’ best asset if used effectively.

But as this massive volume of information accumulates in organizations, it’s easy for data to disappear, creating data black holes. Whether they’re caused by disparate systems, siloed organization structures or a lack of proper technical infrastructure, data black holes represent missed opportunities to use and organize data appropriately. This creates problems with user experience, speed, digital transformation and more — and the problems only get worse as data masses grow larger.

With that in mind, there are several causes of data black holes to look for:

Three causes of data black holes

1. You can’t find the data. The first cause of data black holes is broad, but common — put simply, you don’t know where your enterprise’s data is located. Business leaders frequently learn they have this issue when embarking on machine learning projects to utilize their data, only to find they don’t even know where to start. Right out of the gate, you need to determine where your data comes from and where is it stored.

Understanding how your data is backed up is also critical. Is it all stored off-site? Is data in the cloud or on-premise? If you can’t answer these simple questions, you have a data black hole on your hands. 

2. You don’t know who controls the data. Maybe you have a sense of what data your organization is storing, but do you know who to work with to actually access that data?

Given that tech-related decision making now spans various departments and is not solely the responsibility of IT, data silos easily emerge due to increasing SaaS technology options. Maybe the marketing team uses one piece of software, while the operations teams use another. Add factors like employee turnover and manual or unreliable movement of data between systems and you can see how a lack of understanding around data access and controls becomes incredibly complicated.

3. You don’t know what your data can tell you. The point of data capture is to access powerful, potentially transformative insights about your business. Although you obviously don’t know what these insights are before you start mining them, you should at least know what you’re looking for and why. If you don’t understand what data your organization has collected and what you could learn from it, you’re probably dealing with a data black hole.

Solving the data black hole dilemma: Start with a data lake

A data black hole isn’t as apocalyptic as it sounds, if you take the right steps. And the first step is to invest in a data lake.

It might be tempting to try to make sense of the data you have and start analyzing from there, but this wastes valuable time, money and effort. Fortunately, a data lake doesn’t require structured data, so you don’t have to worry about sorting it or organizing it. Parking your data in a data lake ensures you’re not adding to the volume of the black hole while you attempt to analyze data.

Next, commit to investments in data scientists. While the data warehouse approach allows stakeholders without much technical expertise to access data, these insights are often shallow. Data scientists who can actually parse meaningful findings from the data will ultimately drive your business to success.

Leveraging big data properly is a significant competitive advantage for any enterprise. Any time wasted in data black holes is time that’s difficult to make up — so adjust your approach, create a data lake and start making the most of your data now.

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