Lynn Cope, an Advanced Business User of a GO Americas subsidiary, needs to analyze which product lines result in the greatest number of returns so that the GO Americas management can focus on these product lines to decrease the number of returns.
Lynn knows that there is one chart inside the IBM Cognos workspace of the Great Outdoors company that already displays the return quantity by product lines. So, Lynn decides to use this existing report as a base for her analysis. To make this possible and easy, the IBM Cognos interface provides a seamless integration between the IBM Cognos Business Insight and IBM Cognos Business Insight Advanced products.
Using this integrated approach, Lynn follows these steps:
Business Insight and Business Insight Advanced integration: Modifying an existing report
After Lynn clicks Do more, the IBM Cognos Business Insight Advanced interface replaces the IBM Cognos Business Insight interface and shows the selected report.
With the IBM Cognos Business Insight Advanced interface opens, Lynn makes improvements to the report to meet her needs. First, she changes the sorting configuration for the chart to allow her to see the product lines in the chart sorted by the return quantity of their products. To execute this task:
Selecting the chart area
Advanced Layout Sorting option: Set Sorting window
GO Data Warehouse package tree: Expanding Returned items folder
After the Return quantity member has been added
After executing these steps, Lynn determines that Outdoors Protection is the product line that has the worst performance in terms of the return quantity of all Great Outdoors subsidiaries,
Report after sorting has been performed
To meet her business needs, Lynn needs to filter the report to display only GO Americas and 2007 (current year) totals.
Using Context filters
Because Lynn is working with a dimensional data model, she can easily filter her data using the Context filter feature by following these steps:
Adding a Context filter
After performing these steps, Lynn notices that, in fact, the performance of the Outdoors Protection product line and the performance of the Camping Equipment product line in terms of return quantity are extremely close,
Report after GO Americas Context filter is applied
The current report shows the total of Return Items for all of the years (2004, 2005, 2006, and 2007). To have the best insight about the return quantity for the current scenario, Lynn needs to filter the report to show only the data for the current year (2007). To achieve this result, she follows the same steps to apply another Context filter for 2007
Report after 2007 Context filter is applied
Now, Lynn can determine that, in fact, only one product line, the Camping Equipment product line, has an extremely high number of returns.
If we think about the business problem, a Product line with a high number of returns for its products does not necessarily mean a large percentage of returns based on the number of products sold for the product line. To find more meaningful information, Lynn needs to calculate the percentage of returns against the number of products sold.
Lynn can create this calculation easily by using the Query Calculation object in the Insert Objects pane, following steps:
Measures: To create this calculation, use the following measures:
Do not set the Measure Dimension.
Creating a query calculation
Inserting a member from the Data items tab into Expression Definition
Inserting operator into Expression Definition
Inserting [Quantity] item into Expression Definition
Starting Expression Definition validation
After these changes, Lynn determines that the Camping Equipment product line has 1.8% of its items returned
Report with the new percent of Returned items metric
After performing these steps, Lynn realizes that the sorting is not working as expected. To solve this issue, she follows these steps:
Members window after the Return quantity member has been removed
After performing these steps, the chart shows the bars in the correct order
Report after sorting change to percent of Returned items
Set the right level of detail for the analysis To complete her analysis, now Lynn needs to discover which brands have the highest percentage of returned items. She uses the drill-down and drill-up features as follows:
Drill down on the product line
Drill down on the product type
Set Sorting properties for percent of Returned items
After performing these steps, Lynn has a report that shows the products that have a higher percentage of returned items
Report after drilling down, ordered by percent of Returned items
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Ibm Cognos Tutorial
Introduction To Ibm Cognos Business Intelligence
Overview Of The Ibm Cognos Business Intelligence Architecture
Business Scenario And Personas Used In This
Create Reporting Packages With Ibm Cognos Framework Manager
Business Intelligence Simplified: An Overview
Individual And Collaborative User Experience
Self Service Interface For Business Users
Actionable Analytics Everywhere
Enterprise Ready Performance And Scalability
Ibm Cognos System Administration
Integrating Ibm Cognos Bi With Ibm Cognos Business Analytics Solutions
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