Telling Your (Data) Story
Storytellers usually design and select characters who have the right level of depth and complexity needed to further a story. Similar to storytellers, both data scientists and visualization experts interpret data —their "characters" — to help them answer questions and relay the right information.
Before creating your first visualization, you want to identify the questions you need to answer using data. Then, use the data fields in Analytics to find the data — or the "characters" — needed to help you answer those questions.
In Analytics, the characters are called Dimensions and Measures.
About Dimensions and Measures
Dimensions and Measures are types of preexisting data fields used to build visualizations.
- A Dimension can be thought of as a group or bucket of data.
- A Measure is information about that bucket of data.
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In a refrigerator, you see an array of food: fruits, vegetables, and cookies (or biscuits in British English). These food groups can be thought of as Dimensions because they are individual groups of data. Now, let's say you want to know exactly what fruits, vegetables, or cookies there are in this refrigerator. You could ask the following questions:
These questions could be thought of as Measures because you are seeking information about one type of food against itself and/or each other. |
Now, let's take a look at how Dimensions and Measures work in Analytics.
Viewing Dimensions and Measures in an Explore
Let's say that you want to know how many work orders are in different work order statuses. In this scenario:
- the Dimension is the Work Order Status: Open, In Progress, Completed, Invoiced (much like fruits, vegetables, and cookies).
- the Measure is the information you want to know about the work order statuses — in this case, the number of work orders (or Work Order Count). Questions such as "How many work orders are in the Open or In Progress status?" or "How many work orders are not yet Invoiced?" can be answered using this Dimension.
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Example: Selecting Data
Over the next few pages, we will follow an example of building a story using data. We start with a simple scenario and then build in more complexity as we move through the workflow. Follow along with your data, noting that your data will be different from what is shown.
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In this example, we want to see the number of work orders in each status. It will look like this:
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Most visualizations will have at least one Dimension and one Measure. |
Next section: Checking Out the Data
Now that you understand what Dimensions and Measures are and have seen what they look like when selected, let's dig a little deeper into the data.
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