Have you ever get overwhelmed with the buzzwords like Business Intelligence, Big Data, Business Analytics, Data Warehouse, Data Mining, Data Visualization, Decision Support Systems, and Expert Systems? This presentation gives you a brief enlightening introduction and outlines how these technologies can help organizations earn competitive advantage. Furthermore, the presentation explains the some important BI tools' adoption and return on investment considerations.

1. Pouria Ghaternabi 7050754
A presentation for
Electronic Business Strategies

3. What is Business Intelligence?
Raw data

4. What is Business Intelligence?
Meaningful and useful information

5. What is Business Intelligence?
To make better decisions

6. Who Make the Decisions?

7. Data = Right Decision?
• What about if you have too much data?

8. Will you be able to find the right
answer

9. For questions such as
• How are my sales?
• How much will I sell next year?
• Are my customer satisfied with my services?
• Which other products are my customers
interested in?
• Which parts of the business are not profitable?

10. How About Those Bad Decisions?

11. How About Those Bad Decisions?
In 2000
$50 million
= $900
million

12. How About Those Bad Decisions?
In 1986
$5 Million

13. How About Those Bad Decisions?
20 years later
$7.4 Billion

14. How About Those Bad Decisions?
Steven Sasson
1975

15. How to Make the Right Decisions?
• You need an insight into the data

16. Business Intelligence 1.0
1980s

17. Business Intelligence/ Data
Warehouse/ Data Mining

18. Business Intelligence 2.0

19. What is Decision Support System?
• Interactive computer-based information
system that supports decision-making
activities.
• It is a an application of BI

20. What is Expert Systems?
• A computer program that simulates the judgment
and behavior of a human or an organization that has
expert knowledge and experience in a particular field

21. Data Visualization?
Goal is to communicate information clearly and
efficiently to users via the information graphics
selected, such as tables and charts

22. Data Visualization?

23. Business Intelligence 3.0

24. Big Data?

25. Big Data
“Big data can be
defined as datasets
that are beyond the
ability of common
databases softwares
to store, manage,
capture and analyze”
Ref: Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H., 2011

30. wikibon.org/bigdata

31. Big Data creates value in several ways
• Making data more readily accessible to relevant stakeholders at the
right time creates enormous value of data

32. • Enabales experimentaion

33. • Improve decision making, minimize risk and unearth valuable insights

34. • Segment the population in order to customize products and services
to meet the segment needs

35. • Innovate new business models, products and services to not only
satisfy customers but to capture new opportunities and create new
markets.

36. Use of Big data as competitive advantage
• Find hidden patterns
• Identify new growth opportunities
• Precise prediction of consumer behavior
• Increases productivity
• New sources of value
• Catalyst for trend shifting in industries

37. Crunch of Big Data
“We’ve never had greater, better analyzed, more
pervasive, or increasingly connected computing power
and information at a cheaper price in the history of the
world”
Ref: McKinsey & Company

68. Insight and Recommendation

69. “Managers are making bad decisions because of
bad data”
Professor Nour El-Kadri
Telfer School of Management
Is BI and Big Data Analytics are the Solution for Bad Decision Making?

70. Let’s Challenge This Idea!

71. What Might Be Wrong?
Causation Bias

72. Boston Street Bump

73. Accelerometer

75. Does Good Data Guarantee Good Decisions?

77. People
who make the decisions
Processes
of decision making

78. Why BI May not Enhance Decision Making?
High Concentration
of Analytics Skills
Shifting BI from
Conventional Uses
to More Critical
Applications
Low Strategic
Priority of Data
Accessibility Issues

79. Analytic Skills are Concentrated on Too Few Employees

80. eBusiness Executives Don’t Manage Data as Good as
They Manage Talent, Capital, and Brand

82. Thank
You
Very
Much!

83. References
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