OLAP Cubes in SPSS
This morning in class we were taught a new technique of data analysis called 'OLAP Cubes'. This tool adds a third dimension, depth to the regular table which consists of just two dimensions- height and width. An OLAP (Online Analytical Processing) cube is the output of a process that uses one or more scale variables along with one or more categorical values to divide the report information into layers for the depth.
What is OLAP ?
OLAP is a buzzword today. The acronym stands for On-Line Analytical Processing. In fact, this term does not correspond very well to the meaning of OLAP tools.OLAP tools allow the user to query, browse, and summarize information in a very efficient, interactive, and dynamic way. OLAP tools represent a vital component of both the business intelligence and data mining technology. They provide an aggregated approach to analyzing large amounts of detailed data.
Why cubes?
OLAP databases are referred often as "cubes" since they have a multidimensional nature. Each result of querying, browsing, and summarizing can be viewed and stored as a separate cube. A cube is a visual representation of a multidimensional table and has just three dimensions: rows, columns and layers.OLAP cubes are very flexible because they allow the user to move information between these three dimensions. OLAP cubes are easy to create and manipulate. Since they provide insight into various aspects of data, these tools also represent data mining technology. Users can have multiple cubes for their business data: one cube for customers, one for sales, one for production, one for geography, etc.
Types of Variables in OLAP Cubes
1. Summary Variables
2. Grouping Variables
Steps in Producing a Three-Dimensional Table
1. Choose File --> Open --> Data and open Cell_Inter.sav
2. Choose Analyze --> Reports --> OLAP Cubes
The Olap cubes dialog box appears, as shown below :
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3. In the list on the left of the OLAP cubes dialog box :
a. Select relevant variables and move it to summary variables panel.
b. Select relevant variables and move it to grouping variables panel.
4. Click on the statistics button.
The OLAP Cubes Statistics dialog box appears where you can decide what calculations you want
SPSS to perform.
5. Click the OK button.
The total layer of the multi-layered table will then appear. Double-clicking the OLAP Cubes table selects it and causes the appearance of pull-down lists as shown below :
By making selections from the lists, you can change the view by changing the table that appears on top.
Few Examples of Different Layers
A. Gender of respondent:
Female
Level of education: Total
Name of current service
provider: Total
|
|
Sum
|
N
|
Mean
|
Std. Deviation
|
% of Total Sum
|
% of Total N
|
|
Monthly
expenditure on phone
|
11240.00
|
30
|
374.6667
|
320.17520
|
15.5%
|
14.6%
|
|
Fixed
component of bill
|
1448.00
|
30
|
48.2667
|
13.22206
|
14.6%
|
14.6%
|
|
Voice
calls bill
|
1210.00
|
30
|
40.3333
|
23.48636
|
12.1%
|
14.6%
|
|
SMS bill
|
703.00
|
30
|
23.4333
|
11.91256
|
12.7%
|
14.6%
|
|
Other
charges
|
200.00
|
30
|
6.6667
|
12.34094
|
17.4%
|
14.6%
|
B. Gender of respondent: Male
Level of education: Total
Name of current service
provider: Total
|
|
Sum
|
N
|
Mean
|
Std. Deviation
|
% of Total Sum
|
% of Total N
|
|
Monthly
expenditure on phone
|
61393.00
|
176
|
348.8239
|
151.16696
|
84.5%
|
85.4%
|
|
Fixed
component of bill
|
8466.00
|
176
|
48.1023
|
20.51733
|
85.4%
|
85.4%
|
|
Voice
calls bill
|
8775.00
|
176
|
49.8580
|
29.47846
|
87.9%
|
85.4%
|
|
SMS bill
|
4816.00
|
176
|
27.3636
|
18.40819
|
87.3%
|
85.4%
|
|
Other
charges
|
947.00
|
176
|
5.3807
|
11.00844
|
82.6%
|
85.4%
|
C. Gender of respondent: Male
Level of education: Total
Name of current service
provider: BSNL
|
|
Sum
|
N
|
Mean
|
Std. Deviation
|
% of Total Sum
|
% of Total N
|
|
Monthly
expenditure on phone
|
6325.00
|
20
|
316.2500
|
95.00963
|
8.7%
|
9.7%
|
|
Fixed
component of bill
|
960.00
|
20
|
48.0000
|
24.02849
|
9.7%
|
9.7%
|
|
Voice
calls bill
|
885.00
|
20
|
44.2500
|
25.04076
|
8.9%
|
9.7%
|
|
SMS bill
|
665.00
|
20
|
33.2500
|
20.98088
|
12.0%
|
9.7%
|
|
Other
charges
|
120.00
|
20
|
6.0000
|
11.87656
|
10.5%
|
9.7%
|
D. Gender of respondent: Male
Level of education: Total
Name of current service
provider: Hutch'
|
|
Sum
|
N
|
Mean
|
Std. Deviation
|
% of Total Sum
|
% of Total N
|
|
Monthly
expenditure on phone
|
22127.00
|
66
|
335.2576
|
123.93042
|
30.5%
|
32.0%
|
|
Fixed
component of bill
|
3114.00
|
66
|
47.1818
|
19.88344
|
31.4%
|
32.0%
|
|
Voice
calls bill
|
3200.00
|
66
|
48.4848
|
24.69771
|
32.0%
|
32.0%
|
|
SMS bill
|
1656.00
|
66
|
25.0909
|
16.90856
|
30.0%
|
32.0%
|
|
Other
charges
|
216.00
|
66
|
3.2727
|
8.26958
|
18.8%
|
32.0%
|
E. Gender of respondent:
Female
Level of education: Total
Name of current service
provider: BSNL
|
|
Sum
|
N
|
Mean
|
Std. Deviation
|
% of Total Sum
|
% of Total N
|
|
Monthly
expenditure on phone
|
1283.00
|
5
|
256.6000
|
104.13117
|
1.8%
|
2.4%
|
|
Fixed
component of bill
|
237.00
|
5
|
47.4000
|
17.85497
|
2.4%
|
2.4%
|
|
Voice
calls bill
|
265.00
|
5
|
53.0000
|
38.01316
|
2.7%
|
2.4%
|
|
SMS bill
|
85.00
|
5
|
17.0000
|
14.83240
|
1.5%
|
2.4%
|
|
Other
charges
|
.00
|
5
|
.0000
|
.00000
|
.0%
|
2.4%
|
F. Gender of respondent:
Female
Level of education: Total
Name of current service
provider: Hutch
|
|
Sum
|
N
|
Mean
|
Std. Deviation
|
% of Total Sum
|
% of Total N
|
|
Monthly
expenditure on phone
|
3502.00
|
9
|
389.1111
|
97.57106
|
4.8%
|
4.4%
|
|
Fixed component
of bill
|
404.00
|
9
|
44.8889
|
8.70983
|
4.1%
|
4.4%
|
|
Voice
calls bill
|
400.00
|
9
|
44.4444
|
22.97341
|
4.0%
|
4.4%
|
|
SMS bill
|
210.00
|
9
|
23.3333
|
11.98958
|
3.8%
|
4.4%
|
|
Other
charges
|
65.00
|
9
|
7.2222
|
10.92906
|
5.7%
|
4.4%
|
By analysing the three dimensions of available data using OLAP Cubes, one can have a multi-faceted view of consumer trends and other patterns.
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