1. Subject Areas for Transactional Business Intelligence
  2. Subject Areas Overview

Subject Areas Overview

This guide provides a list of all the prebuilt subject areas with the following detail:

  • Description of the subject area.

  • Business questions that can be answered by data in the subject area, with a link to more detailed information about each business question.

  • Job roles and duty roles that can be used to secure access to the subject area, with a link to more detailed information about each job role and duty role.

  • Primary navigation to the work area that is represented by the subject area.

  • Time reporting considerations in using the subject area, such as whether the subject area reports historical data or only the current data. Historical reporting refers to reporting on historical transactional data in a subject area. With a few exceptions, all dimensional data are current as of the primary transaction dates or system date.

  • The lowest grain of transactional data in a subject area. The lowest transactional data grain determines how data are joined in a report.

  • Special considerations, tips, and things to look out for in using the subject area to create analyses and reports.

Scheduled ESS Processes

Some subject area dimensions have scheduled processes to refresh the data. If your analytic doesn’t have the correct or updated data, you might need to run an ESS scheduled process update. For a list of subject areas that contain dimensions that have ESS scheduled processes, and general detail on scheduling ESS processes see, Scheduled Processes for Analytics

Choosing the Right Subject Area

You can use the prebuilt subject areas to build your own analytics. or you can build your own subject areas and use them for building or editing analytics. Most importantly, the focus of a subject area is to provide a way for you to gain access to key insights about your organization.

We provide a wide variety of subject areas that give insight on a lot of different business activities. So how do you know which subject area is right for you? It starts with the names of the subject areas. Let's say you're building your own analytic because you want to know something about your pipeline. The area of interest to you in this case would be pipeline, and would make sense to choose a pipeline subject area for starters. Take a look at the subject areas in the guide. You might notice that the Sales — CRM Historical Pipeline has questions like “ How are product revenues trending month to month?” Or “What are the higher value deals that have been pushed out?” There are lots of business questions that can guide you to the right subject area and help you get the insights you’re looking for.

Now let’s assume you know your subject area. But wait, there could be a prebuilt analytic that uses this subject area. You might take a look at the prebuilt analytics spreadsheet. But if none of those prebuilt analytics work for you, go to BI and click New > Analysis and choose the Sales — CRM Historical Pipeline subject area. You can see the available columns of information you can use to build your analytic. You can add any columns and facts you want, and at any time click the “Results” tab and see how it looks. .

Exploring Subject Area Components

This guide doesn’t detail the dimensions, columns, and facts that make up a subject area. But no problem. You can explore the components right in your application. Here’s how:

  1. From the Home page of your application go to Navigator.

  2. Go to Tools > Reports and Analytics. This brings you to the Reports and Analytics page where your sales team see analytic detail specific to their role. Let's go BI where we can access all the details and tools related to subject areas.

  3. Now let’s go to BI. Click Browse Catalog.

  4. In BI let’s take steps as if we are building a new analytic. Go to New and then Analysis.

  5. Choose the subject area you are interested in exploring. Let’s pick Sales — CRM Pipeline as an example.

  6. Expand some of the folders. The top level folders are called Dimensions. They hold the columns a related to that dimension. You will also see Fact folders. Let’s look more closely at the Fact folders.

What are Facts?

Facts are a little tricky. This first thing to understand is that facts and dimensions work together as a pair for reporting. Think of the fact as the verb or the action in an analytic, and the dimensions as the nouns, or a bunch of related nouns —things grouped together in context. You can have a collection of things, but without doing something with them, they are just there to look at. Same with dimensions, sure you can go into the subject area editor, and expand all the folders and look at the columns. You can drag a column onto the editor and view row after row of data. But, if you want to analyze the data, you need a way to measure it. You need to count it, compare it, sum it up, average it over time or perform any other statistical operation.

So keep in mind that all dimensions need a fact, at least one fact. Facts give meaning and purpose to your analysis. Don’t build analytics without a fact, especially if you have more than one dimension because this leads to unpredictable results.