AN OVERVIEW

BIG DATA- POWERED AI:

KEY CHALLENGES FOR MONETIZING

Your big data is just a big waste of money and server storage space. 

No matter how much of it you collect, no matter how many analytics programs

you run, no matter how many data scientists you have pouring over the bits and

bytes -- big data is not boosting the bottom line or making your business

smarter.

YOU’RE NOT THE ONLY ONE FACING THIS PROBLEM

according to recent articles in the

Harvard Business Review and McKinsey.

But don’t blame big data for that. It’s all your fault.

CHALLENGES

Here's an overview of the aforementioned

challenges:

#1. CONFRONTING COMPLEXITYTrying to get value out of vast amounts of complex data is a serious challenge

facing businesses. A recent big data survey by NewVantage Partners cited “ability

to develop greater insights into their business and customers” as the primary

driver behind their big data initiatives as well as “faster time-to-answer, faster

time-to-decision and faster speed-to-market.” 

#2. CREATING CONSUMERIZATION

Organizations want to extract intelligence from their big data as quickly and easily

as consumers get the information they need from the apps on their smartphones.

In other words, businesses want “consumerized” data. How can businesses work

with their big data in the same fashion? Analytics firms need to consumerize the

data, providing businesses with the information they need right now, in a

consumable format for effective decision making.

#3. CONSTRUCTING CONTINUITYUntil now, organizations mainly relied on analytics to understand the drivers of past

performance or the root cause of a problem, but organizations are increasingly

demanding insights from analytics that enable them to predict their future.

Predictive and prescriptive insights are big data’s real value.

But as anyone who has seen a time travel movie or studied quantum physics

knows, the predictable future is not set in stone. If something shifts, the whole

scenario changes.

CONCLUSION

While meeting all three

challenges is critical to extracting

the most value from your big data,

continuity is in many ways the

most important, as it underpins

the self-learning architecture of

the analytics that are ushering in

the era of sophisticated AI,

machine learning and deep

learning.

THANK YOU!Stay tunned for more such presentations! 

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