All language subtitles for 9. Step-by-Step DAX Measure Calculation

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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:00,630 --> 00:00:06,570 All right so we talked about filter context and we talked about how measures evaluate based on that 2 00:00:06,570 --> 00:00:08,080 filter context. 3 00:00:08,100 --> 00:00:13,410 But it's time to take a peek under the hood and try to learn about how this actual engine works. 4 00:00:13,470 --> 00:00:16,660 How are these specific measure calculations happening. 5 00:00:17,040 --> 00:00:20,370 So let's consider a simple matrix view like this. 6 00:00:20,370 --> 00:00:25,440 In this case we're evaluating a total return's measure based on category names. 7 00:00:25,650 --> 00:00:30,460 And what we want to figure out is how this particular cell accessories returns. 8 00:00:30,480 --> 00:00:35,330 Number of 1115 is calculated. 9 00:00:35,340 --> 00:00:41,160 So what I'm about to show you all happens behind the scenes and it happens instantly every time the 10 00:00:41,160 --> 00:00:43,170 filter or context changes. 11 00:00:43,200 --> 00:00:50,400 So I like to think of it as a three step process where Step one is when the filter or context is detected 12 00:00:50,730 --> 00:00:51,710 and applied. 13 00:00:51,720 --> 00:00:57,870 So this is where power be-I looks at the filter context for that particular value and says OK I'm being 14 00:00:57,900 --> 00:01:05,610 asked to only care about rows where the category name in my product table equal accessories as a result 15 00:01:05,640 --> 00:01:11,730 that product table gets filtered down to the point where you're only left with accessories Rose. 16 00:01:12,060 --> 00:01:19,020 And from there we move into step two which is where that filter context category name equals accessories 17 00:01:19,530 --> 00:01:23,620 flows to all downstream related tables. 18 00:01:23,640 --> 00:01:30,150 So if you had a model like this where that product table or connected to data tables sales and returns 19 00:01:30,540 --> 00:01:36,390 you would see both of those data tables filtered down accordingly to only the product IDs where the 20 00:01:36,390 --> 00:01:38,670 category equals accessories. 21 00:01:38,700 --> 00:01:43,560 So you end up with filtered down versions of both of those data tables as well. 22 00:01:43,560 --> 00:01:50,670 And that brings us to step three which is one to measure formula actually evaluates against that filter 23 00:01:50,670 --> 00:01:51,730 table. 24 00:01:51,750 --> 00:01:57,720 So the measure that we're looking at here what it's essentially doing is it's counting the rows in that 25 00:01:57,720 --> 00:02:00,770 return's data table but not the whole thing. 26 00:02:00,810 --> 00:02:06,980 It's counting the rows of the filtered down version where the product category is accessories. 27 00:02:07,140 --> 00:02:15,440 And as a result the number of rows that exist after the filter context has been applied is 1115. 28 00:02:15,510 --> 00:02:20,910 So I'd recommend keeping this on hand just as a helpful reference in those cases where your measures 29 00:02:21,090 --> 00:02:23,990 might not be calculating as you expect them to. 30 00:02:24,390 --> 00:02:30,720 So that that wraps up the high level kind of conceptual part of this section of the course from here 31 00:02:30,720 --> 00:02:37,080 we're going to move into daks syntax operators common function categories and then get hands on with 32 00:02:37,080 --> 00:02:38,430 a bunch of different examples. 3555

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