OLAP Miner User's Guide


Creating a deviation detection definition

OLAP Miner searches through an area of a cube that you define. The area of the cube that you define is called the subcube. The subcube structure is specified in a deviation detection definition. The deviation detection definition specifies which members from the hierarchy of each dimension that you want OLAP Miner to mine for deviations.

To create the deviation detection definition, you follow these general steps:

  1. Name the deviation detection definition.
  2. Select members from each dimension.
  3. Run the deviation detection definition.
  4. View the mining results.

Naming the deviation detection definition

Specify a name for the deviation detection definition.

  1. From the OLAP Miner main window, select the Demo Basic cube.
  2. Click Actions --> Create deviation detection definition. The Deviation Detection Wizard opens.
  3. In the Name field, type Actual Sales all products 2001.
  4. In the Description field, type Demo Basic: Actual Sales-all products-all markets-2001.
  5. Click Next. The next wizard window opens.

Figure 5. Deviation Detection wizard (1 of 3)

Wizard 1 of 3: Naming the definition

Selecting members from each dimension

In this step, you create a deviation detection definition by defining an area of the OLAP cube (Demo Basic) that you want OLAP Miner to search.

  1. Select Year and click Member and Descendants.
  2. Select Market and click Member and Descendants.
  3. Select Product and click Member and Descendants.
  4. Expand Accounts, select Profit, and click Member Only.
  5. Expand Scenario, select Actual, and click Member Only.
  6. Click Next. The next wizard window opens.

OLAP Miner will search for deviations specifically in actual sales but in the context of the other dimensions.

Figure 6. Deviation Detection wizard (2 of 3)

Wizard 2 of 3: Selecting members to analyze

Running the deviation detection definition

OLAP Miner displays the selections that you made in the deviation detection definition. You can specify how many deviations that you want OLAP Miner to return. Leave the default number at 100.

Review the selections. Then click Save and run now.

Figure 7. Deviation Detection wizard (3 of 3)

Wizard 3 of 3: Running the definition

OLAP Miner displays a Progress Display window to show how the mining run is progressing. Because you are using a relatively small cube in this example, the mining run should take only a few minutes.

Figure 8. Progress window

Progress Display window

Close the Progress Display window.

Viewing the deviations

In this step, you view the mining run results.

  1. From the left pane of the OLAP Miner main window, expand the deviation detection definition called Actual Sales Analysis 2001. A results file (.res) with a time stamp is displayed.
  2. Select the results file. A list of deviations is displayed in the right pane of the main window.

    Figure 9. OLAP Miner main window

    OLAP Miner main window showing a list of deviations

    You can sort the list of deviations by clicking on the heading of a column in the main window.

  3. Review the list of deviations. Notice the different columns: Scenario, Product, Market, Year, Expected, and Magnitude.

    The first five columns represent the dimensions that you selected in the deviation detection definition. The Expected column describes whether the calculated expected value is higher or lower than the actual value of the cell. OLAP Miner uses the difference between the expected value and the actual value to calculate magnitude. As the difference between the expected value and the actual value increases, the magnitude increases. Higher magnitude values show greater disparities in the data.

  4. Select the first deviation (Actual, Television, New_York, Aug, -274, Higher, 7).
  5. Click View --> Display in Context. The Deviation Viewer opens.

    Figure 10. Deviation Viewer, Product by Market view

    Deviation Viewer: Product by Market

    The deviation that you selected is shown in red with a red border. Other deviations in this area of the subcube are highlighted in red.

    Notice that the deviation -274 is significantly different from the other surrounding values. The actual profits in August for televisions in New York is much lower than expected. OLAP Miner calculates the expected value based on all the other values for each dimension that intersects with the cell Television, New York, August, Actual, Profit.

    In this example, OLAP Miner determines that the Product by Market view is the most significant. The tabs under the deviations are shown in order of importance with the most important view shown first.

    For more information about how OLAP Miner calculates expected values and magnitudes, see The OLAP Miner algorithm.

  6. Click each tab on the bottom of the Deviation Viewer to see the values from other dimensions that intersect with the deviation.

    Figure 11. Deviation Viewer, Market by Year view

    Deviation Viewer: shows the Market by Year view

    When you hold the cursor over a red highlighted value, the magnitude and expected values are displayed.

    Figure 12. Deviation Viewer, Product by Year view

    Deviation Viewer: shows the Product by Year view with help text that shows the magnitude and expected value

  7. Click the Product x Market tab.

Viewing the deviations in spreadsheet

If you installed the DB2 OLAP Server spreadsheet add-in:

  1. Click Open Spreadsheet.

    Figure 13. Standard spreadsheet

    Lotus 1-2-3 spreadsheet showing deviations

  2. Click Essbase --> Connect and select the server where Demo Basic is located.
  3. Type your user name and password.
  4. Click OK.
  5. Select Demo Basic from the Application/Database list. You can now use any of the features in the DB2 OLAP Server spreadsheet to investigate or report deviations.


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