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All right.
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Next up we have the incredibly important topic of daks measures.
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Now by definition measures are daks formulas that are used to generate new calculated values.
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So couple important things to note about measurers like calculated columns.
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They reference entire tables or columns.
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So again no A-one style or grid references like you would use in Excel but unlike calculated columns
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the measure values aren't actually visible in your tables.
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In fact you can only see measured values within a visualisation like a chart or a matrix.
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So for those of you with Excel backgrounds think of measures the same way you'd think about a calculated
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field in an Excel pivot that calculated field doesn't exist anywhere else.
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You can't see it in tables you only see it within that Excel pivot table itself.
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Now measures and power be-I operate the same way you can only see them when you drag them into the values
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field of a visualization.
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So well-calculated calculated columns are evaluated based on row context measures are evaluated based
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on filter context.
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It's a little bit of a tricky concept to wrap your head around but what I mean by that is that these
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measures the values they take constantly recalculate whenever the fields are filter's around them change.
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So if you drag a new field or dimension into the row or column labels of a matrix or if you apply new
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filters to your report in each of those cases you're changing the filter context and you're changing
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the value that that measure should return.
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So to summarize as a rule of thumb you're going to use measures not calculated columns when a single
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row isn't going to be able to give you an answer.
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In other words when you need to aggregate and protip for remembering this.
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Remember that measures are used to create numerical calculated values.
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You can analyze in the values field of your report visuals.
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So if we actually look at the report pain in our adventure works file you'll see that we've actually
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already been using measures.
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We just didn't know we were using them quite yet.
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And the way we used measures was simply by dragging those fields into the values pane here.
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And you'll note that this little arrow tells us that we're looking at the sum of this particular numerical
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field order quantity and what we've done is actually create an implicit measure by doing that.
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So we're going to talk about implicit versus explicit measures in a bit but check it out.
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You've already got a head start on understanding how measures work so that we've done our intro to measures
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we've done our intro to calculated columns.
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Let's take a minute to compare the two side by side and then move on and get a little bit deeper into
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how daks really works.
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