Companies should focus on analyzing important data rather than all data. They can accelerate data using a hybrid data platform for fast insight and outcomes. Next-gen business intelligence and data visualization turn data into an asset for decision-makers. Data discovery finds patterns to uncover opportunities, while analytics applications simplify advanced analytics for business users. Machine learning removes human elements to produce predictions using cognitive computing. Companies can take hypothesis-based or discovery-based approaches depending on if the problem or solution is known. The key is to take action on insights uncovered from data analysis.

1. Right way of Data
Analysis

2. Companies can get stuck trying to
analyse all the data they can get their
hands on, when they should be trying to
recognize what’s important and what
isn’t.

3. What is to be done?

4. 1. Accelerate the data
Liberate and accelerate
data by creating a data
supply chain built on a
hybrid technology
environment — a data
service platform
combined with emerging
big data technologies.
Fast Data
Fast Insight
Fast
Outcomes

5. 2. Next-Gen Business Intelligence (BI) and data
visualization
BI turns organization’s
data into an asset by
having the right data, at
the right time and place,
displayed in the right
visual form for each
individual decision-
maker, so they can use it
to reach their desired
outcome.

6. 3. Data discovery
Through the use of data
discovery techniques,
companies can test and
play with their data to
uncover data patterns
that aren’t clearly
evident to find more
opportunities to drive
value for the business.

7. 4. 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

8. 5. Machine learning and cognitive
computing
Machine learning is an
evolution of analytics that
removes much of the
human element from the
data modelling process to
produce predictions of
customer behaviour and
enterprise performance.

10. Companies can take two approaches
depending on the nature of the business
problem -
Second, for a known
problem area but with an
unknown solution, the
company could take a
discovery-based approach
to look for patterns in the
data to find interesting
correlations that may be
predictive.
First, for a known problem
with a known solution, the
company could take a
hypothesis-based
approach by starting with
the pilot, test the solution
with a control group and
then scale broadly across
the customer base.

11. Once insights are
uncovered, the next
step is for the
business, of course, to
make the data-driven
decisions that place
action behind the
data.