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

1. AN OVERVIEW
BIG DATA-
POWERED AI:
KEY CHALLENGES FOR MONETIZING

2. 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.

3. 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.

4. CHALLENGES
Here's an overview of the aforementioned
challenges:

5. #1. CONFRONTING COMPLEXITY
Trying 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.”

6. #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.

7. #3. CONSTRUCTING CONTINUITY
Until 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.

8. 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.

9. THANK YOU!
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