The Difference Between Big Data And Deep Data

Big data has become an important topic for nearly every industry. The ability to study and analyze large sections of information to find patterns and trends is an invaluable tool in medicine, business and everything in between. Employing analytics, the root of big data, in your business can lead to advances and discoveries that you might not see otherwise.

When it comes down to it, though, big data isn’t really a new concept. It’s simply taking data already available and looking at it in a different way. Deep data, on the other hand, may be the real tool that you need to change the world, or at least your industry.

Big data is an amalgamation of all of the data collected by a business. The specifics will vary by industry, but generally, its information like customer or client names and contact information and other data collected over a business day. Depending on the side of the business, this can be mind-boggling amounts of information, much more than it would be possible for a regular human to go through.

Businesses can employ predictive analytics to help sift through the data to find patterns and trends, but much of the information is often useless or redundant.

Deep data is, in essence, taking the data gathered on a daily basis and pairing it with industry experts who have in-depth knowledge of the area. We’re talking exabytes or petabytes of data — much more than what could fit on a standard computer or external storage drive. Deep data pares down that massive amount of information into useful sections, excluding information that might be redundant or otherwise unusable.

Big data and deep data are inherently similar, in that they both utilize the mass of information that’s collected every single day by businesses around the world.