The document discusses how we interpret and make meaning from big data. It notes that when analyzing big data, we must consider both black and white factors like correlation and causation, as well as grey areas around humanities, sociology, and ethics for proper context. The language and inferences we use to understand data can impact the decisions we make. We should therefore question both the questions we ask of data and the answers we receive to avoid making bad decisions from incomplete analysis.

1. Do we
know
how to
use BIG
DATA?

2. What do we do with
all this big data?

3. Susan Etlinger
at
TED@IBM

4. Accessing The Grey Areas
1

5. “
We can take data and make it
mean anything. But are we
actually extracting the root
cause or the factor that we
“think” is the root cause.

6. We are the ones creating
meaning out of the big
amount of data at our
disposal.

7. White
 Humanities
 Sociology
 Social sciences
 Rhetoric
 Philosophy
 Ethics
The world isn’t just
Black and White
Black
 Correlation
 Causation
 Economic
Feasibility
 Sequence of events

8. We should take into
consideration the grey areas
as they give us context to
tackle big data and help us
become better critical
thinkers.

9. The language of Data
2

10. We make the
inferences
So even when the we see
that data doesn’t crop up
from its usual sources, we
shouldn’t regard it as
irrelevant. It is upto us to
make sense out of it.

11. We have the potential to
make bad decisions far more
quickly, efficiently, and with
far greater impact than we
did in the past.“

12. What
should
mangers in
India look
forward to?
👨

13. We not only have to find
answers to the questions we
have at hand.
Try questioning the answers
that we get from data
exploration.
“

14. As Susan Etlinger mentions,
Did the data really show us
this, or does the result make
us feel more successful and
more comfortable?

15. Thanks!
-Analysis by Shloka