Internship task under Professor Sameer Mathur

1. Companies should pursue a simpler path to uncovering
the insight in their data and making insight-driven
decisions that add value.

6. BI does this by turning an organization’s data into an asset by having the right
data, at the right time and place (mobile, laptop, etc), and displayed in the right
visual form (heat map, charts, etc) for each individual decision-maker, so they
can use it to reach their desired outcome.

7. Data discovery. Data discovery can take place alongside
outcome-specific data projects. Through the use of data
discovery techniques, companies can test and play with
their data to uncover data patterns that aren’t clearly
evident. When more insights and patterns are discovered,
more opportunities to drive value for the business can be
found.

8. Analytics applications- Applications can
simplify advanced analytics as they put the
power of analytics easily and elegantly into
the hands of the business user to make data-
driven business decisions.

9. Machine learning and
cognitive computing-
Machine learning is an
evolution of analytics
that removes much of the
human element from the
data modeling process to
produce predictions of
customer behavior and
enterprise performance.

11. Another main component of
a company’s analytics journey
depends on the company’s
culture itself: is it more
conservative or willing to take
chances? Does it have a
plethora of existing data and
analytics technologies to
work with, or is it just
starting out with its first
analytics project?