Data Analytics using AI part 2 Overview of AI-Enabled Analytics

Data Analytics Using AI part 2

1. BAI3399
Data Analytics Using AI
Overview of AI enabled Analytics
Islam Ali

2. Learning Objectives
•Understand the Meaning of AI
•Learning the difference between AI and ML
•Knowing what is involved in ML Projects
•Comprehending the difference between Analysis and Analytics
•Avoiding Bias with the use of AI
•ROI of AI

3. Analytics VS Analysis
•Analysisfocusesoninvestigating
thepast,interpretingdatato
understandwhyanevent
occurredandidentifyingpast
trends.Analyticsisabroader
fieldthatencompassesusing
datatomakefuture-oriented
decisionsbyapplyinganalysis,
statisticalmethods, and
advancedtechniquestopredict
outcomesandguideactions

4. Analytics VS Analysis
analysis provides
insightsintowhat
happened, while
analyticsusesthose
insightstodetermine
whattodonext

5. Insights
•knownsaboutthebusiness
andwhenknownshould
affectdecisions.
•Insightsarederivedfrom
analyticsthatapplies
mathematicstodata.

7. Analytics
Can help you make unbiased data-
driven business decisions

8. Analysis
•Generates Information
Analytics
•Generates insight

9. BI AND DATA
VISUALIZATION
VS. ANALYTICS

10. BI
•Descriptive Analytics
•Enables multidimensional reporting
•You build cubes to respond to
predefined business questions
•Data Visualization and Dashboards

11. Dashboards
Can be misleading

12. BIASED VS.
UNBIASED

13. Humans are known to make
biased decision
Data driven decisions are likely
to be unbiased

14. AI ROI

15. Nucleus found analytics enabled improved visibility in three areas
Revenues. The more managers knew about what customers where
(sic) buying and why, the better able they were to accelerate sales
cycles, cross sell, and maximize pricing
Gross margin. Analytics can help decision makers identify the highest
margin products so that they could push the right products and
increase gross profit.
Expenses. The more managers … learned [from] analytics … the better
able they were to reduce or eliminate expenditures that were
unnecessary or generated low returns

16. All sounds
positive
But we still need to
measure AI’s
contribution to
business
performance.

17. AI and ROI
•Research typically pegs the ROI on analytics at a minimum of 10X

18. Conclusion

19. Conclusion
Almost all businesses today realize that AI and analytics
must be incorporated.
Some know what AI-enabled analytics is
only a few know how to incorporate AI, and then only on a
limited basis.
The goal is to empower all leaders with vision and clarity
about how to implement a culture of analytics for data-
driven decisions and to provide a Roadmap to get there.

20. Thank You