3. There are also some areas of
disappointment. Experts caution
that big data, like any other, is
only as good as the questions
being asked – and that some
algorithms can make unhelpful
assumptions.
4.
5. • Big data needs a hard outcome metric for
performance, but the most readily available
metrics may not actually be the most important
variables in organizational flourishing.
• while destroying the emotional climate that
sustains the life-blood of any organization.
• A manager – like the demotivating petty tyrant
mentioned above –can force his people to work
hard to meet quarterly targets.
6. There’s a saying in the sciences, “Statistics
means never having to say you are certain.” in
any massive data analysis, for instance, there
will be random c correlations that look
significant but actually are noise, not signal.
STATISTICS
7.
8. Big data needs a hard outcome metric for
performance, but the most readily available
metrics may not actually be the most
important variables in organizations
flourishing.
10. The more we depend on algorithm,
numeric values problems of
employee will not be reduced but
we need to implement more
technologies knowing their pros and
cons.