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Finance BI Pilot UM Analytics - Navigate to Central Developed Dashboards

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Key Terms

Here are some key terms will be helpful as you work within the UM Analytics environment.

• Analysis – Think of an analysis as simply a query or collection of data fields that provide answers to various business related questions. For example, a Sponsored Award Deficit analysis is a query that provides a list of Sponsored Awards that are in deficit.

• Dimensions – Dimensions are data fields that correlate to chartfields that are used in the transaction system. Dimensions can be best described as the building blocks for the analysis. For example, the account dimension would be equivalent to the account chartfield. Members – Members refer to the actual values that are contained within a data field/dimension. The account dimension would contain account member values of 700000, 700100, 700102, etc.

• Attributes – Attributes are data fields that provide additional information about a dimension. The account dimension may have attributes that provide the account description, account type, etc..

• Hierarchies – Hierarchies are used to display the trees that exist in the financial system. Within OBIEE the hierarchies are flattened in a way which allows the customer to report on various levels within the tree without having to create multiple joins to other tables. An example of the hierarchy in the UM Analytics environment is the ‘UM Account CYFWD’, which is used to depict the financial UM_ACCOUNT_CYFWD.

• Objects – Objects are graphical representations of functions within the UM Analytics toolset. The ‘save’ object , provides the ability to save your work.

• Analysis – Query or collection of data which provides answers to business questions.

• Dashboard – Collection of queries presented in graphical and/or tabular form to answer business question(s).

• Dashboard Prompt – Function used to reduce results of dashboard to focus on business question(s).

• Filter – Function used to limit results of an analysis.

The following steps can be used as a blueprint for creating an analysis.



1. Open Browser - Internet Explorer and Mozilla Firefox are supported browsers for the University of Minnesota



2. In the address field of the browser, type in or copy the following address for the UM Analytics Pilot production environment: http://bipltprd.oit.umn.edu/analytics/saw.dll?BIEEHome&startPage=1



3. Type in your login information a. Userid = Internet ID b. Password = Internet ID Password



4. Upon logging into the UM Analytics environment, you will either be presented with a personal dashboard or the standard 'Home' page. The Home page is a task-oriented, centralized workspace combined with the University of Minnesota header, allowing access to various OBIEE objects, the related editors, help documentation, etc.



5. The items below depict some of the more commonly used objects (functions) within UM Analytics a. Analysis – Query or collection of data which provides answers to business questions. b. Dashboard – Collection of queries presented in graphical and/or tabular form to answer business question(s). c. Dashboard Prompt – Function used to reduce results of dashboard to focus on business question(s). d. Filter – Function used to limit results of an analysis.

All 'Central' developed Dashboards will exist in the FMS Shared folder in UM Analytics. To find this folder, please click 'Dashboards' menu option next to the 'Catalog' menu option.



6. You should see a list of options beginning with 'My Dashboard'. Position your cursor next to the plus sign that corresponds to 'FMS Reports'.

7. Expand the FMS Report folder by clicking on the plus sign.

*Note that the FMS: General Ledger dashboard is a delivered Oracle dashboard that may or may not work during the course of the Pilot based on the underlying source data that exists.



8. Select the 'PI Dashboard'



9. The PI Dashboard should appear in the new screen. You should notice that parts of the dashboard will display a 'processing status', which indicates the application is attempting to run the associated analysis. If the dashboard does not find any data that matching the underlying analysis and selected prompt, your screen should resemble the screenshot below:



10. Dashboard Prompts As stated earlier in this document, dashboard prompts are use to filter data within a dashboard. Most dashboards will have prompts which allows for multiple user types to utilize the dashboard. Dashboard prompts also help to reduce the amount of development needed. Rather than create one dashboard for each department, one dashboard can be created that filters on department value. The PI Dashboards are built primarily for PIs. However, because the analysis for the dashboard are based partially on the 'Internet to Chartfield Mapping' page, non-PIs can also use these dashboards.



11. For this example you can select an internet id from the drop down list for internet id. In example below, J-KOEN was selected for the 'Internet ID'. Notice that the Name field is limited based on the value in the 'Internet ID' field. This is a best practice when using fields related to a person. We would want to make sure the Internet ID and Name field retained their integrity.



12. After selecting a valid internet id click the 'apply' button. The dashboard will process based on the dashboard prompt values (in this case, Internet ID). You should see a message or messages within the dashboard with a clock stating, 'Searching...To cancel, click here.'



13. Results should appear in your dashboard based on the internet id entered.

Date post:	27-Mar-2018
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