Covering Disruptive Technology Powering Business in The Digital Age

2017 is undeniably in full swing and with the completion of the Chinese New Year celebrations for the year of the Rooster, the transition is complete. Yet transitions for many businesses, government agencies and organisations is yet to come.

The catalyst for these changes is of course Big Data Analytics. It will disrupt most business processes in the coming year, and affect every other type of business in its wake, if they haven’t changed already.

One technology that will be talked about a lot, will be a rejuvenated come back from Artificial Intelligence. Being the corner stone for machine intelligence, machine learning neural networks as well as cognitive data, we can expect progress in leaps and bounds as companies gear themselves to take on the challenges.

Its comeback after decades of absence since the foundations were laid in the 60’s by Ray Solomonoff, can be attributed to the the 3 V’s. Namely Velocity, Volume and Variety. Technological advancements today are able to scale linearly to process the three V’s while providing tremendous cost efficiency of up to 10 – 20 times what traditional platforms could ever offer.

Googles many documentations have shown how better results are achieved through simple algorithms that are executed frequently against large datasets, as compared to other methods using smaller datasets. John Schroeder, executive chairman and founder of MapR Technologies also agrees that AI will easily beat out human intuition and error through its consistency, therefore reducing cost.

Another area is in how easily can data be accessed. Data has to be agile and provide continuous connections between customer and provider. It could be what makes the difference in retaining customers in 2017.

Businesses will want to take action on their incoming real-time data and so this will mean Development Operations will need to step up to the plate. Just having lakes of data doesn’t give the competitive edge any longer. Processing models are now able to support batch analytics, interactive analytics, global messaging, database and file-based models.

So with all this speed and accessibility, governance has to be made mandatory so as not to lose the customers trust. Enterprises are brimming with information about their partners and customers and this will need proper regulatory governance from a body that can track and report data through all transformations right up to its originating source.

In some instances, it will be difficult to make it mandatory especially towards non-regulatory use cases such as customer 360 or offer serving, when a mix of structured and unstructured can offer better and more effective results.

It will definitely be an exciting time in Big Data as people begin to adopt and accept analytics as a way of life. Some may not even have a choice in the matter. Big Data has, in fact, taken up a life of its own. Even though progress has its good and bad in opportunities and downfalls, as we’ve seen throughout our history, it waits for no man.

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