One of the core concepts that we're going to dive into, and this is directly related to any visualization tool that you play around with is called a dimensions versus measures. You can think of the data fields in your datasets as ingredients that we could potentially cook with to build in bake these beautiful visualizations. A dimension is a field that you can classify, that is an independent variable. Normally I like to think of that as your qualitative or categorical information. If you had your IRS 990, this could be like the name of the charity, their address, anything that's not necessarily mathematical. Whereas your measure is going to be dependent. That's going to be generally quantitative information, so things like revenue metrics, expenses, salaries, counts, sums. That doesn't mean that one particular field can't serve as a potential dimension and the measure. For example, if you add the employer identification number, what would that be? Would that be a dimension or measure? If you said dimension, you're absolutely correct. Just because it's an integer or a number, doesn't necessarily mean it's a measure because that's a qualitative information. That would actually classify itself as a dimension. But if you had the count of all those EIN numbers, you can then treat that dimension as a measure. That count would then be a measure. Question for you that we'll walk through together. Which of the below are measures? Some measures again are those quantitative fields. Which ones can you perform math on? Well, let's take it from top to bottom. Number one phone number, no that is definitely a dimension. You cannot perform math on a phone number. I mean, you could, definitely shouldn't. Employee ID, no, not technically, but again, if you're doing things like counts of employees, you can apply functions on top of your dimensions to treat them as measures. Age, absolutely. You could do average age, you could do min-max. Date of birth, I wouldn't really consider that as a measure. Tenure at work in years, definitely, that's something that would make sense to do math on. Job title, I would not consider that as a measure because again, that's qualitative information. Let's talk a little bit more about one of the chief deliverables of what you're actually going to be producing, which is, lo and behold, the report. The report is a canvas for you to clearly tell whatever message or story about the insights that you've gathered, and tell in a clear and effective and well-laid out manner so that your audience gets it very quickly. Again, think back to the count of five example. You want to immediately look, maybe within the first 10, 15 seconds and hone in on those really key insights that the audience care about. Of course, you can share and collaborate these reports with your peers as you're developing them, and this is an iterative process. Just because you create a beautiful visualization and you launch it out into the world, doesn't necessarily mean that that's never going to change in the future with new data or new feedback from your audience members.
