Although the word DATA has been with us for a long time, only in the recent decades, since Data was computerised, did it grow exponentially and became synonymous with success, no matter if it referred to business, academia, research or any other domain including our private lives.
And as we move from the past to the future, new DATA terms started to appear in order to differentiate how we perceived, processed and consumed DATA in the past and how we go about doing this today. Most of us have heard and hopefully are familiar with terms like Big Data, correlation, analytics and the extensive if not exchaustive vocabulary surrounding the DATA subject.
But there are still people that do not understand the total picture of DATA moving over time and stages. And although the attempt below is of my own device, I am sure it will bring some clarity to the uninitiated.
So lets start with the different periods of DATA, using a mix of globally accepted and own terminology. I would therefore split DATA into the following 4 ages:
1/ Historic (prior to mainstream computer adoption = <1990)
2/ Past (average computer adoption, early stages of internet adoption and mobile = 1985-2005)
3/ Present (catholic adoption of computers, internet and mobile with early stages of IoT = 2000-2020)
4/ Future (Cloud, mobile and IoT have taken over, AI picking up quickly = 2015-?)
You can see how DATA ages overlap, this was done on purpose as the boundaries of ages are always blur.
But what are the additional differentiators of these DATA ages, outside of the ones mentioned above (computer, internet, mobile and IoT adoption)? The following table attempts to clarify the landscape and give some perspective of additional key differences.
One can now see clearly how we have advanced from having limited data and resources to collect, process and share DATA just 20-30 years ago, to where we stand today where DATA is in abundance and we have merely the time or resources to fully exploit it. This exact point, DATA management and usage, has proven to be a key strategic and competitive differentiator between businesses, enterprise and public alike. Believe it or not, there are still companies living in the historic DATA age, relying solely on Excel for their needs.
But I am still optimistic in what the future holds for DATA and believe me when I say that the best is yet to come. We are already taking our first infant steps into this future with the first Machine Learning platforms already crunching data for us (see IBM Watson). These platforms will evolve and eventually reach a state where they will operate without human intervention or manual connection to data sources. It will only take a set of natural language questions and a few seconds of data gatheirng and crunching to get back our results.
I don’t know about you, but I simply cannot wait …
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