One of the critical ways Tableau classifies fields is as dimensions and measures. Learn what makes these classifications different and how you can use them to speed up your analyses.
Hi, this is Ryan with Playfair Data TV. And in this video, I’m going to be explaining a major way that Tableau classifies all of the fields that you are using in your dataset and that is as a measure or a dimension.
First, the definitions from Tableau’s own Knowledge Base. By default, Tableau will classify any quantitative field as a measure, so anything that is numeric, by default, that gets classified as a measure, Tableau’s going to assume that is a measure. Measures are dependant because they don’t tell us much on their own. Let me give you an example.
The bar chart that you’re looking at on the screen I happen to know is the SUM of Sales from the Sample – Superstore dataset. But unless I know all of the parameters surrounding that value, it really has no context.
I like to use the joke that if that’s my retirement account, I’m probably feeling pretty good about it right now. But if my sales last quarter were $8 million, I’m feeling pretty bad about that number. I just don’t know. Measures are dependent on the context that comes on the other side of this coin, which are dimensions. Again, the definition from Tableau’s own Knowledge Base, by default, anything that is qualitative so anything with a data type of String or text if you think about it that way, by default, Tableau will classify that as a dimension.
Dimensions are considered independent because they do come with some inherent information. They do tell us something on their own. On the bar chart we’re looking at now, we’ve got a measure of Sales, and it’s being broken down by a dimension called Category from the Sample – Superstore dataset. Well, that Category dimension has three things in it– Furniture, Office Supplies, and Technology. And by the way those three things in the Category dimension, the proper term for those things is ‘dimension members’. So the Category dimension has three dimension members.
The reason those dimension members are considered independent is they mean something. At some point in the business, somebody had to come along and say these are the products that belong in the Furniture category, these are the products that belong in the Office Supplies category, and so on. So they tell us something on their own, but these two things work best when they are combined together.
We had the measure SUM of Sales. We’ve now broken SUM of Sales down by a Category dimension, and only now am I able to start to glean some insight from those two fields. I can see some things like Technology is leading the way. Furniture and Office Supplies are kind of neck and neck, but Furniture is second and Office Supplies is third.
I’ve got a few major rules of thumb here on the Fundamentals learning path at Playfair Data TV. It is not a coincidence that this is my first rule of thumb. This is truly the cornerstone of how I approach every chart that I build in Tableau, so it’ll be very helpful for you to keep this in mind as you make your way through all of our videos. And that is, in general, measures are the numbers, so those are the quantitative fields that we are analyzing. And the dimensions are what we slice and dice those numbers by in order to glean insight.
This has been Ryan with Playfair Data TV – thanks for watching!