Session-Level Calculated Member Examples

Example Data

The data that is used in these examples is from a company that sells electronics and outdoor and sporting goods equipment.

Example 1

This example creates the session-level calculated member called avg_price in the sales cube on the Measures dimension. This calculated measure shows the average price:
create session
    member [sales].[measures].[avg_price] as
      '[Measures].[total] / [Measures].[qty]'   
Nothing is returned when you create a session-level calculated member.

Example 2

This example uses the session-level calculated member called “avg_price.” It shows the quantity, total, and average price of goods sold from 1998 through 2000.
SELECT
    {[measures].[qty], [measures].[total],
 [measures].[avg_price]} ON COLUMNS,
    {[time].[all time].children} ON ROWS
 FROM sales
Here is the resulting output:
Query Results
Year
Qty
Total
Average Price
1998
440,852
10,782,352.94
24.4579880322648
1999
539,433
14,080,419.58
26.1022584454418
2000
32,267
859,108.83
26.6249986053863

Example 3

This example uses the session-level calculated member called “avg_price.” It shows the quantity, total, and average price of goods sold in different customer regions.
SELECT
    {[measures].[qty], [measures].[total],
 [measures].[avg_price]} ON COLUMNS,
    {[customer].[all customer].children} ON ROWS
 FROM sales 
Here is the resulting output:
Query Results
Region
Qty
Total
Average Price
Central
157,659
3,942,290.26
25.0051710336866
Mid-Atlantic
79,555
2,011,008.77
25.2782197222048
Midwest
259,759
6,614,999.09
25.4659091311562
Mountains
32,768
838,064.62
25.5757025146485
Northeast
143,934
3,658,452.99
25.4175732627454
South-Central
64,943
1,662,479.79
25.5990605607995
Southeast
122,888
3,134,589.55
25.5076944046611
West
151,046
3,859,996.28
25.5551042728705

Example 4

This example uses the session-level calculated member called “avg_price.” It shows the quantity, total, and average price of goods sold in the different product groups.
 SELECT
    {[measures].[qty], [measures].[total],
 [measures].[avg_price]} On COLUMNS,
    {[product].[all product].children} ON ROWS
 FROM sales
Here is the resulting output:
Query Results
Product
Qty
Total
Average Price
Doing
191,321
4,850,302.26
25.3516459771797
Electronics
330,977
8,426,846.64
25.4605203382712
Health & Fitness
185,909
4,717,790.80
25.3768822380842
Outdoor & Sporting
304,345
7,726,941.65
25.3887583170415