1. Quiz 2

2. 1. How do we interact with multidimensional data in order to
1. How do we interact with multidimensional data in order to provide us more interesting information?
A. Storing the data for future use
B. Averaging data across different dimensions
C. Slicing and dicing
D. Simplifying the data by ignoring random dimensions
E. None of these
Answer: Slicing and dicing

3. 2. What fundamentals define an online transaction
processing (OLTP) system?
A. It processes a transaction
B. It performs transactions in real time
C. It processes many transactions on a continuous basis
D. All of these
Answer: All of these

4. 3. (True/False) Online analytical processing (OLAP) systems
and online transaction processing (OLTP) systems
perform identical functions.
Answer: False

5. 4. Pivoting and nesting are capabilities of what type of IS
system?
A. OLTP
B. OLAP
C. Disk storage hardware
D. Word processors
E. None of these
Answer: OLAP

6. 5. What is a data warehouse?
A. A collective repository of data
B. The building where computer systems store data
C. The data used by inventory managers
D. Equivalent to a data mart
E. All of these
Answer: A collective repository of data

7. 6. Why do we use data mining?
A. To cleanse the data
B. To reduce data storage space
C. To search through mountains of data for interesting
information
D. To prevent viruses from infecting large computers
E. None of these
Answer: To search through mountains of data
for interesting information

8. 7. Standard casino poker tables typically accommodate up to 10 players
7. Standard casino poker tables typically accommodate up to 10 players. How many players at a time can one video poker machine accommodate?
A. 2
B. 3
C. 4
D. 10
E. None of these
Answer: None of these

9. 8. (True/False) Because of their high capital and energy costs, slot machines are significantly less profitable than table games such as black jack and roulette.
Answer: False, slot machines are the more profitable than table games and dominate casino floor space

10. 9. What is Harrah’s “Total Rewards” program?
A. VIP treatment for high rollers
B. A co-branded credit card with VISA
C. A program providing higher slot returns for frequent gamblers
D. A tiered membership program for all customer levels
E. None of these
Answer: A tiered membership program for
all customer levels

11. 10. Decision analytics enabled Harrah’s to improve which of the following KPIs?
A. Earnings per share rose from $14 to $81
B. Revenue per room rose from $172 to $268
C. EBITDA rose from $513 million to $2 billion
D. Cross-market play rose 18.5%
E. All of these
Answer: All of these

12. Multidimensional Analysis

13. For Next Week Read Pages 113-143 of Business Intelligence
Pages 1-64 of Process Mapping
Quiz 3 next Wednesday covers these readings

14. Bridging the Analysis Gap
How do we go from data to information?
Data > Information > Knowledge > Power
Information is data that has meaning/is useful
Fruit wholesale example
Distributes fruit in four markets
Sells four types of fruit
Sales in multiple quarters

15. Dimensions Distinct categories
Customers, geographic regions, etc.
Time, product and market are the dimensions in the fruit wholesaler example

16. Measures Quantitative expression Measures are analyzed by dimensions
Sales, profitability, etc.
Measures are analyzed by dimensions
Sales by region by salesperson
Sales by region by product

17. Dimensions/Measures Peruvian Doll Sales by Store Sales Week Above Plan1 2 3 4 5
YTD
Lovesick Lake
103
135
116
128
119
Wingtip 76 84
104 89
111 93
Tailspin 66 80 88 91
Contoso 35 74 95
Tkachuk 82 79
Above Plan
At Plan
Below Plan

18. Multidimensional Analysis
Looking at data with single dimensions obscures interesting/useful patterns
Need to view data simultaneously categorized across many dimensions
Often more than three dimensions
Time
Amount
Qtr 1
$16,000
Qtr 2
Total
$32,000
Market
Amount
Atlanta
$8,000
Chicago
Denver
Detroit
Total
$32,000
Product
Amount
Apples
$8,000
Cherries
Grapes
Melons
Total
$32,000

19. Multidimensional Analysis
Atlanta
Chicago
Denver
Detroit
Total
Qtr 1
Apples $-
$2,500
$1,500
$4,000
Cherries
$2,000
Grapes
$1,000
$3,000
Melons
Total Q1
$5,000
$4,500
$3,500
$16,000
Qtr 2
Total Q2

20. The Cube Multidimensional data can be visualized as a cube
Each cell contains a specific value

21. Slicing and Dicing Two techniques used in multidimensional analysis
Slice
Member of a specific dimension
Cherries in the product dimension
Q1 in the time dimension
Dice
Intersection of a slice by another dimension
Sales of cherries by region
Sales in Q1 by product

22. Slicing and Dicing
Sales of cherries by region by time?

23. Slicing and Dicing
Sales in Q1 by product by region?

24. Hierarchy Data is organized in hierarchies
Different levels of organization with a single dimension

25. Roll Up/Drill Down
A hirarchy enables two additional techniques in our multimensional analysis
We can roll up the data
Bottom-up (specific to general)
We can drill down into the data
Top-down (general to specific)

26. Roll Up/Drill Down
Roll up the time dimension

27. Roll Up/Drill Down
Drill down into the time dimension

28. Ad-Hoc Analysis
Slicing, dicing rolling up, etc. enable ad-hoc analysis
Unlike reporting, has no constraints
Any question can be answered quickly
What is our profitability by product and by customer?
What are our sales in January in the Northeast region by sales person?