“The world’s most valuable resource is no longer oil, but data.” What seemed like a bold statement by The Economist (in a story they published in 2017) is now anything but. Kiran Bhageshpur, a columnist at Forbes, put it best when he claimed that the phrase, “Data is the new oil” has become a refrain in conversation. In our first ever Data Analytics session, our facilitator described the digital representation of nearly every facet of the human experience as the creation of an alternate world. This was, by no means, a revelation to me, I had just never thought about the intentionality behind this creation process.
Sitting in class and listening as the multi-disciplinary instructor linked statistics and the history of the terms ‘state’ and ‘country’ to the treaty of Westphalia, I wondered, “What fuel could be mined and used to create an alternate world?”. The answer was simple, data.
Data is a precious thing and will last longer than the systems themselves.Tim Berners-Lee, inventor of the world wide web
The statement by The Economist might as well have been prophesy. This is because over the three years that followed, about 90% of the world’s data was created at a staggering rate of 1.7 megabytes a second (per human being). Data regarded in these large volumes and implications are referred to as big data. The cardinal features of big data are its 5 V’s. They are:
- Volume: The sheer colossal size of data. This represents the amount of data produced. Traditional means of processing data and information are severely challenged by ‘data explosion’. Thanks, in no small part, to the roles of digital and social media.
- Velocity: This refers to the increasingly rapid speed of data creation, multiplication and consumption. In business, the ability to interpret data to solve real-time problems can be a distinguishing weapon in the arsenal.
- Variety: Often classified as structured, semi-structured or unstructured, big data can be presented in diverse forms (almost 80% of the time, unstructured). It bestows on the able businessperson to identify and classify the data accordingly.
- Value: In my opinion, it all comes down to value addition. Of what merit is the data to the decision-making process of your business? Big data must be seen to have value.
- Validity: Big data can get messy, challenging to control and it can be untrustworthy. This is usually as a result of its multiple variances and sources. You must be able to assess the credibility of big data before you harness it’s “powers”. It can do serious damage otherwise.
Surely, these large amounts of data aren’t neatly stored in a safe at some Swiss bank. As much as it can be coherent and credible, data can be disarticulated, non-homogenous and chaotic. The process of refining these chaotic materials, identifying patterns and extracting meaning from them is what I have come to know as Data Analytics.
In closing, it may still be too soon to declare data king of the world’s resources but if the architects, analysts and designers of the alternate world have anything to do with it, it won’t be a pre-mature statement for much longer. After all, man’s digital footprint can’t simply be wiped away by a 10km asteroid.