The History of Big Data Analytics

Big data analytics started to become a huge buzzword in 2011. For this reason, one might assume there is very little history on the topic to speak of. This isn’t necessary the case. In fact, it’s possible to find what can be called a rich history when analyzing the two major components behind the trend and stripping them down to the core.

Computers Changed Everything

The origins of big data can be tracked back to the advent of the most basic arithmetic. Man has been counting and measuring volumes since the first modern societies mingled in Egypt and Indus Valley during the 3,000 BC era. But we’ll zoom ahead to the computer age …

From handwritten records to typed documents, information is something we’ve been collecting in massive amounts for ages. However, it was the computer that introduced innovative ways to capture, store, and analyze information. Until mainframes and PCs entered the conversation, data management and analyzing long consisted of traditional bookkeeping using some of the most tedious number crunching methods you could imagine.

Computers gave humans the ability to process information much faster at a scale that compared to traditional means, was almost limitless. As time progressed, these machines evolved with greater speed, storage capacities, and capabilities. When computers hit the mainstream, the library database, criminal files, and medical records stored in cabinets began to find regular housing in digital folders. With all the basics covered, the only thing missing from the puzzle was an effective way to measure this digital information.

Data Mining and the Internet Age

The trend we know as big data analytics began to take form when data mining rose to prominence. Companies started investing in software that allowed them to zip through large volumes of information in search of patterns and correlations that are essential to business performance. With this type of application, a manufacturer could pinpoint the various flaws in production. Or a retailer could identify products that are ideal for upselling and cross-selling to existing customers.

In the internet era, big data analytics has exploded into a multi-billion industry that transcends geographical borders. And because even the smallest business can quickly accumulate a massive amount of information, organizations from virtually every sector are tapping into it to tame and maximize their data infrastructures.

  • Video streaming services use analytics to deliver recommendations to viewers based on viewing history, reviews, and preferences.
  • Social networks make millions in advertising revenue by selling units that allow businesses to target audiences by location, interests, and activity, which they serve up using analytical technology.
  • Suppliers and carriers use big data analytics to map out the safest and most efficient routes for drivers to travel on their deliveries.
  • Automobile makers are increasingly using the same technology to produce models that improve vehicle safety and efficiency for drivers.

Big data analytics hasn’t been around long, but its current position in the digital world has been a long time in the making. Although one could argue that there is still quite a ways to go, what can’t be debated are the opportunities available to those who decide to get in on the action and optimize their informational assets.


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