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Big Data: A History That Repeats

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In the early 1800s a thick black liquid, known as oil, started to pour out from inside of the earth. At that moment little was known about its different uses and qualities, but rapidly those properties emerged and gave an impulse to the first industrial revolution, that at the beginning was driven by steam engines, and now had a new boost that put it in a new dimension unknown at that time. From oil came kerosene and gasoline (which was considered as waste due to its volatility). With time oil derivatives started to be used in other applications such as plastics and asphalt, shaping the way in how things were manufactured, and transported and the materials of everyday articles.

In many ways, history is repeating itself in the 4th revolution. Several technological advancements have changed traditional industries and, like oil did at the time, have generated resources that at the beginning had unknown real capacities or uses, but with technology development and new analytical processes revealed different and crucial reach. I’m talking about data as the new fuel to re-shape how business is conducted. The potential of Big data is enormous, such as oil back in the day, it is under layers and layers of legacy systems in many organizations, waiting to be extracted and exploited to fuel businesses into new paths.

For example, the insurance industry has managed its data as stand still information where fields in a database work their purpose to conduct specific transactions, but this is a limited form of using the resources available and not a way of utilize the full potential of data to offer a predictive model.

We are far from having a model that when people change their home address, they get a message from the insurance carrier informing that the company has their new location, and their coverage is active under the current policy. Also, the company would confirm any changes in their risk exposure and alterations to their rate. This is a foreseeable future, but we need to start using the essential raw material, data.

As in the early days of oil, it is a matter of how each company structures its data strategy, begins to “drill” through layers of legacy systems, and builds “refineries” of data to process the information that will be needed in the digital revolution. Or they can simply keep relaying in the good old horse instead of the new cars and say that “cars will never replace the horse.”


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