Overview

The SAS BI Dashboard indicator data object associates a data source with an indicator. The core object is the indicator, and a dashboard is just a collection of indicators. An indicator never has more than one set of indicator data (and is rarely used without indicator data). Access to four types of data sources is supplied with the SAS BI Dashboard:
  • SQL queries, which can access relational data
  • information maps, which can access relational data and OLAP cubes
  • tables, which can access data in a SAS data set that is registered in SAS metadata
  • stored processes, which can access various types of data
Note: The SAS BI Dashboard administrator can add access to other data sources.
Before you create a dashboard, you must understand how to create indicator data. Understanding the data flow in the SAS BI Dashboard is the key to building enterprise dashboards that operate efficiently within your organization’s business intelligence system.
Unlike the flow of data in a report (which is usually relatively simple), the flow of data in a dashboard can be very different. Consider the dashboard in your car. Although you see a single representation of the state of the car, the state is actually a collection of different types of data received by the dashboard. The fuel gauge receives data from the fuel tank, the speedometer receives data from the wheels, the battery gauge receives data from the battery, and so on. Like your car’s dashboard, a SAS BI Dashboard can have disparate data sources.
Whereas a report created with SAS Web Report Studio might fill several screens with data from a single information map, a dashboard might render data in a small display that is the result of SQL and JDBC queries and information maps. A dashboard can also render the output of stored processes that produce static images.
By using information maps and SQL queries to retrieve data, you are unconstrained with how the data is laid out at the data set level. For example, you can use computed columns and grouping in the indicator data. After you have the data configured, the lack of constraints helps you to get initial dashboards set up quickly. But this same simplicity means that data structure is not enforced.