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Big Data Hype (and
Reality)
by Gregory Piatetsky-Shapiro
Big data has been the focus of countless
articles and perhaps too many meetings and
conferences.
Decision-makers want to understand the
patterns in the past and the present in
order to anticipate what is most likely to
happen in the future.
Insight 1
With three years of effort by some of
the world’s best data mining scientists,
the average prediction of how a
viewer would rate a film improved by
less than 0.1 star.
As a company that thrives when people
consume more content, Netflix routinely
serves up personalized recommendations to
customers based on their feedback on films
they’ve already viewed. This is a prediction
challenge;
If predictive analytics drawing on big data
could accurately point to who in particular
was about to jump ship, direct marketing
dollars could be efficiently deployed to
intervene, perhaps by offering those
wavering customers new benefits or
discounts.
Insight 2
Predictions suggest that the
randomness inherent in human
behavior is the limiting factor to
consumer modeling success.
Though how much ever we analyse the
data, it still depends on humans mood
to take a particular decision
That randomness in decision making
make it difficult to take a decision from
data available that will be exactly
correct
Behavioral and targeted advertising have
been able to improve on that significantly,
with researchers reporting up to seven-fold
improvements.
But note that a seven-fold improvement
from 0.2% amounts to 1.4% — meaning that
today’s best targeted advertising is ignored
98.6% of the time.
Predictive analytics can figure out how
to land on Mars, but not who will buy a
Mars bar.
Big data will see its biggest and most
important application in the realm of
artificial intelligence, which Is also
gaining popularity in India
If you’re counting on it to make people
much more predictable, you’re
expecting too much.
Thank you
SUBMITTED FOR DATA ANALYTICS INTERNSHIP
UNDER PROFESSOR SAMEER MATHUR, IIML
BY
S SHESHASAI VENKATESH
VASAVI COLLEGE OF ENGINEERING

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Big data hype (and reality)

  • 1. Big Data Hype (and Reality) by Gregory Piatetsky-Shapiro
  • 2. Big data has been the focus of countless articles and perhaps too many meetings and conferences.
  • 3. Decision-makers want to understand the patterns in the past and the present in order to anticipate what is most likely to happen in the future.
  • 4. Insight 1 With three years of effort by some of the world’s best data mining scientists, the average prediction of how a viewer would rate a film improved by less than 0.1 star.
  • 5. As a company that thrives when people consume more content, Netflix routinely serves up personalized recommendations to customers based on their feedback on films they’ve already viewed. This is a prediction challenge;
  • 6. If predictive analytics drawing on big data could accurately point to who in particular was about to jump ship, direct marketing dollars could be efficiently deployed to intervene, perhaps by offering those wavering customers new benefits or discounts.
  • 7. Insight 2 Predictions suggest that the randomness inherent in human behavior is the limiting factor to consumer modeling success.
  • 8. Though how much ever we analyse the data, it still depends on humans mood to take a particular decision
  • 9. That randomness in decision making make it difficult to take a decision from data available that will be exactly correct
  • 10. Behavioral and targeted advertising have been able to improve on that significantly, with researchers reporting up to seven-fold improvements. But note that a seven-fold improvement from 0.2% amounts to 1.4% — meaning that today’s best targeted advertising is ignored 98.6% of the time.
  • 11. Predictive analytics can figure out how to land on Mars, but not who will buy a Mars bar.
  • 12. Big data will see its biggest and most important application in the realm of artificial intelligence, which Is also gaining popularity in India
  • 13. If you’re counting on it to make people much more predictable, you’re expecting too much.
  • 15. SUBMITTED FOR DATA ANALYTICS INTERNSHIP UNDER PROFESSOR SAMEER MATHUR, IIML BY S SHESHASAI VENKATESH VASAVI COLLEGE OF ENGINEERING