Tolga Tarhan, Onica’s SVP, GM AWS Services, was recently featured in insideBIGDATA’s article discussing data black holes, how to recognize them as well as measures you can take to solve the data black hole dilemma and make your data actionable towards use cases such as machine learning and data analytics.
“How to Prevent Data Black Holes from Swallowing your Organization Whole” takes a dive into the concept of data black holes – situations where pieces of data disappear – a phenomenon more commonly observed today as companies generate and store more data than ever before. “[Data black holes] are caused by disparate systems, siloed organization structures or a lack of proper technical infrastructure” says Tolga Tarhan. Not only does their emergence create issues with user experience, speed, and other aspects of workloads, they only become larger and more problematic as data repositories grow in size and complexity.
The article cites various causes for why data black holes may emerge. One of the primary reasons data black holes exist is that an organization is simply unable to find their data, says Tarhan. “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.” Answering the questions of how data is backed up and if it is stored in the cloud or on-premises is very important to reduce your risk of encountering data black holes.
Tarhan also shares insight on a few more identifiers you can use to recognize the prevalence of data black holes and offers suggestions to how you can go about mitigating such problems. Data lakes, or repositories of unstructured data, allow your organization’s raw data to be stored in the cloud and be utilized towards data analytics, visualization, reporting, and machine learning. “Utilizing these data lakes is simple,” says Tarhan, “they require no sorting or organization, and can help you ensure your data is safe and in one place.” He also discusses the value of data scientists in extracting meaningful value from the data that can be imperative to yield business advantages.
To read the full article, visit insideBIGDATA here.
If you are interested in learning about data lakes as a solution to data black holes and are looking to leverage data analytics to drive informed business decisions, get in touch with our data engineering and analytics experts today.