This is an Analysis of "Simplify Your Analytics Strategy" by Narendra Mulani

1. Simplify your
analytics Strategy

2. Challenges faced!!
 Companies can get stuck trying to analyze
all that’s possible and all that they could do
through analytics, when they should be
taking that next step of recognizing what’s
important and what they should be doing —
for their customers, stakeholders, and
employees.
 Discovering real business opportunities and
achieving desired outcomes can be elusive.

3. Simplification of data
Acceleration
of data
Delegation of
work to
analytical
technologies

4. Acceleration of data
 Liberation and acceleration of data by
creating a data supply chain can be built on
a hybrid technology environment.
 Such an environment enables businesses to
move, manage, and mobilize the ever-
increasing amount of data across the
organization for consumption faster than
previously possible.
 Real-time delivery of analytics speeds up
the execution velocity and improves the
service quality of an organization.

5. Delegation of work to analytical
technologies
 Uncovering data insights doesn’t have to be
difficult.
Ways to delegate
Next-Gen
Business
Intelligen
ce (BI)
Data
discovery
Machine
learning
and
cognitive
computing
Analytics
application
s.

6. Next-Gen Business Intelligence (BI)
 Bringing data and analytics to life to help companies
improve and optimize their decision-making and
organizational performance.
 It turns an organization’s data into an asset by having
the right data, at the right time and place and
displayed in the right visual form for each individual
decision-maker, so they can use it to reach their
desired outcome.
 Enabling to chase and explore data-driven
opportunities more confidently.

7. Data discovery
 It takes place alongside outcome-specific
data projects. Through the use of data
discovery techniques.
 Helps to test and play with their data to
uncover data patterns that aren’t clearly
evident. Thus, presenting more
opportunities to drive value for the
business.

8. Machine learning and cognitive
computing
 With an influx of big data, and advance in
processing power, data science and
cognitive technology, software intelligence
is helping machines make even better
informed decisions

9. 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.
 They can also be industry-specific,
flexible, and tailored to meet the needs of
the individual users across organizations

10. Solution of business problems
 companies can take two approaches
depending on the nature of the business
problem
Known problem,
known solution
Known problem,
Unknown solution

11.  Determining which problem to address, companies
should first focus on the one that can offer the highest
value, then it can choose a hypothesis-based or
discovery-based approach based on the degree of
institutional knowledge it has to solve that kind of
problem.
 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. It is possible to
uncover the business opportunities in your data and
increase data equity, simply.


12. Thank you…