This presentation is a part of data analytics internship under Prof. Sameer Mathur, IIM Lucknow

1. Simplify your analytics strategy
By Narendra Amulani

2. Businesses arebeing
challengedby the
complexityand confusion
that analyticscreate.
Companiescan getstuck
trying to analyseall that’s
possibleand allthey could
do through analytics.

3. Discoveringrealbusiness
opportunitiesand achieving
desiredoutputs canbe difficult
to achieve.To overcomethis,
companiesshould pursue a
simpler path to uncoveringthe
insight in their data and
makinginsight-driven
decisionsthat addvalue.

4. Following steps
can betakento
simplify analytics
strategy and
generateinsights
that canlead to
realoutcomes:

5. 1.
Accelerate Data

6. Fast data = Fast insight = Fast outcomes
Data shouldbe accelerated to create a data supply chain
builton ahybridtechnologyenvironment.Suchan
environmentenables businesses to move, manage, and
mobilizethe increasing amount of data. Real-time
delivery of analytics speeds up the execution velocityand
improves the service qualityof an organization.

7. 2.
Next-Gen Business
Intelligence (BI) and
Data Visualization

8. Next-gen businessintelligenceis bringing data and
analytics tolife to helpcompaniesimproveand
optimizetheir decisionmaking and organizational
performance.BI doesthis by turning data into an
asset anddisplaying itin the right visualform.

9. 3.

10. Data Discoverycan take
placealongsideoutcome-
specificdata projects.
Through the use ofdata-
discoverytechniques,
companiescan uncover
insights and patterns and
opportunities to drivevalue
for the business.

11. 4. Analytics Applications

12. Applicationscan simplify advancedanalyticsas they
put the power of analyticseasilyand elegantlyinto
the hands ofthe business user tomakedata-driven
business decisions.

13. 5.

14. Machinelearningis an evolutionof analyticsthat
removesmuch ofthe human elementfrom the data
modellingprocessto producepredictionsof
customerbehaviourand enterpriseperformance.
With an influx of big data,and advancesin
processing power, data scienceandcognitive
technology,software intelligenceis helping
machinesmakeevenbetter-informeddecisions.

15. Managerial Relevance

16. Managersshould embracethe opportunities
that are beinglaid down by bigdata and
analytics.They should acceleratethe data flow
insidethe organizationso that the datacan be
consumedby the organizationand real-time
deliveryof analyticscan takeplace.Managers
should

17. Managersshould identify the key data anduse data
visualizationtoolsso that the customerscan interact
with theresults and querythe databasedon their
needs so that actionscan betakenthat would
benefitthe business.

18. Machinelearningand cognitive computingcan help
the managerthrough a data-drivenapproach.No
matter what combinationof cultureand technology
exists for abusiness, eachpathto analyticsinsight
should be individuallypavedwith an outcome-
drivenmind-set. Once insights areuncoveredthe
companyhas tomakedecisionsthat placeaction
behind the data.

19. By- Jyotsana Manglani
UCER,Allahabad