Analytics is all about Data so when the form, flavor and ferocity of Data change- Analytics goes into a make-over too

For decades databases have ruled the backyards of IT. Businesses have collected, processed and stored data in conventional and jaded ways for long. Seldom did they know that all this data lying sleepy in these boxes is capable of so much power. When Analytics hit the pavement, an explosive turning point happened. With new tools, data architectures and dashboards in their hands, enterprises could unleash endless insights and decision-enablers from this data. Analytics truly became a datassaince for businesses- catapulting them into a new information revolution.

Understandably, Analytics has become a common denominator for many businesses. There is nothing new, exciting or game-changing about it- we all know how to unpack data with the wide array of solutions at our disposal now. Or is it that unexciting now? Has Analytics turned into a staple and boring factor?

Well, not exactly. There are a lot of undercurrents emerging all around us that are going to redefine Analytics as we know it. If you thought your business and IT teams have dug into all possibilities with Data Analytics, it would come as a surprise to learn that you may have barely scratched the surface of a beautiful iceberg.

Here are some new kids on the block that will underline Analytics with new powers, opportunities and imperatives. Be ready for:

IoT: 

When sensors and edge device spread all across the perimeter of a business and touch even far-flung nooks of a factory or a refinery or an office- then the very definition of cold data gets flipped on its head. Now every IoT pulled-data can be the source of a new hot data repository. This also means that you would need apt visualization and decision tools to make the most of this real-time data streaming in from all corners.

Should we use AI or not:

So far data was data that came in or what you made of it. But with the advent of AI and ML, the width and depth of data expands- multifold. It assumes exponential proportions – thanks to all the modelling and churning that happens inside an AI algorithm or machine. Enterprises will have to learn how to tap this data, how to translate it effectively and how to avert dangers like bias, Black boxes and inconsistencies.

Conversational and Predictive Analytics:

As NLP and unstructured data expand their realms, we are going to observe a new face of Analytics. It will become less machine and more human-like- thus, inching us closer to decisions that entail human nuances and context. The days of flat analytics and prescriptive tools would fade as organizations tap the explosive power of Analytics that talks to you, thinks like you and helps you see ‘tomorrow’ before it happens. It would mean a lot of ease and power- but it would bring some compelling caution areas on data fatigue, data
accuracy, and consequences of actions taken.

Synthetic Data:

Despite the vast amounts of data being fed in machine models and AI engines, there is still an AI appetite for more data. This is being served with the conception of synthetic data- made solely for the purpose of a model, and spun up using existing data patterns. However, a lot of responsibility and regulatory mandates would come in as businesses tap this new form of data. IP, data violation, privacy, discrimination, ethical use – these are just some initial problems that have begun to surface.

New Compliance mandates:

This year we saw DPDP in India along with some stringent moves made in the ambit of GDPR in Europe. All this reaffirms the need for an innate and full-proof awareness that data security, privacy and fair use are no more foot-note choices for businesses-but a big imperative.

Do not get swayed by the power that is unleashed with these new forces. But do not get intimidated either. Be ready with the right data strategy and tools- to emerge as a smart digital business that knows how to tame the genie called data.