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All right.

Next up we have the incredibly important topic of daks measures.

Now by definition measures are daks formulas that are used to generate new calculated values.

So couple important things to note about measurers like calculated columns.

They reference entire tables or columns.

So again no A-one style or grid references like you would use in Excel but unlike calculated columns

the measure values aren't actually visible in your tables.

In fact you can only see measured values within a visualisation like a chart or a matrix.

So for those of you with Excel backgrounds think of measures the same way you'd think about a calculated

field in an Excel pivot that calculated field doesn't exist anywhere else.

You can't see it in tables you only see it within that Excel pivot table itself.

Now measures and power be-I operate the same way you can only see them when you drag them into the values

field of a visualization.

So well-calculated calculated columns are evaluated based on row context measures are evaluated based

on filter context.

It's a little bit of a tricky concept to wrap your head around but what I mean by that is that these

measures the values they take constantly recalculate whenever the fields are filter's around them change.

So if you drag a new field or dimension into the row or column labels of a matrix or if you apply new

filters to your report in each of those cases you're changing the filter context and you're changing

the value that that measure should return.

So to summarize as a rule of thumb you're going to use measures not calculated columns when a single

row isn't going to be able to give you an answer.

In other words when you need to aggregate and protip for remembering this.

Remember that measures are used to create numerical calculated values.

You can analyze in the values field of your report visuals.

So if we actually look at the report pain in our adventure works file you'll see that we've actually

already been using measures.

We just didn't know we were using them quite yet.

And the way we used measures was simply by dragging those fields into the values pane here.

And you'll note that this little arrow tells us that we're looking at the sum of this particular numerical

field order quantity and what we've done is actually create an implicit measure by doing that.

So we're going to talk about implicit versus explicit measures in a bit but check it out.

You've already got a head start on understanding how measures work so that we've done our intro to measures

we've done our intro to calculated columns.

Let's take a minute to compare the two side by side and then move on and get a little bit deeper into

how daks really works.