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These are the user uploaded subtitles that are being translated: 1 00:00:00,820 --> 00:00:06,310 So at this point in the Course it's time to shift gears into demo mode so no more slides for a little 2 00:00:06,310 --> 00:00:07,120 while. 3 00:00:07,120 --> 00:00:08,930 No more broad concepts. 4 00:00:08,950 --> 00:00:14,640 It's time to roll up our sleeves stick right here in our reporting pain and power be-I and focus on 5 00:00:14,680 --> 00:00:19,680 individual chart types and visualisations that we can use to build out this report. 6 00:00:19,720 --> 00:00:26,740 Q So looking at what we have here got orders by category order info by subcategories. 7 00:00:26,740 --> 00:00:33,370 Well we know that our Adventure Works client really cares about product level performance to not only 8 00:00:33,370 --> 00:00:38,320 in terms of orders but in terms of how frequently certain products are being returned. 9 00:00:38,320 --> 00:00:44,200 So I need to capture some of that data here in our executive summary and what I'd suggest that we do 10 00:00:44,200 --> 00:00:47,020 is use a matrix which you're already familiar with. 11 00:00:47,020 --> 00:00:53,860 We use this quite a bit in the DAC section and of course this is a great way to show a lot of information 12 00:00:54,220 --> 00:00:55,950 without it being overwhelming. 13 00:00:56,140 --> 00:01:00,760 So we'll use some of that drill through capability here and some conditional formatting to make the 14 00:01:00,760 --> 00:01:02,300 numbers really pop. 15 00:01:02,350 --> 00:01:07,170 Now the data that I want to show lives in the sales table. 16 00:01:07,270 --> 00:01:11,550 So let's go ahead and grab total orders when it pulled into values. 17 00:01:12,070 --> 00:01:18,410 And let's also pull the return rate from our returns table as well. 18 00:01:18,410 --> 00:01:24,590 So you've got two columns of values and the level at which you want to view these values or the row 19 00:01:24,590 --> 00:01:31,030 labels that we want to use to segment them will come from the product lookup table and we actually want 20 00:01:31,030 --> 00:01:32,520 the product name. 21 00:01:32,650 --> 00:01:38,730 So drag that into Rose expand this down a bit. 22 00:01:38,780 --> 00:01:44,780 So now we're looking at total orders and return rates at the product level. 23 00:01:44,840 --> 00:01:50,060 And one thing that's cool about these matrix news is that you can just click on the header and it will 24 00:01:50,060 --> 00:01:50,510 sort. 25 00:01:50,510 --> 00:01:55,130 So we can default to sort the products that drove the most orders. 26 00:01:55,130 --> 00:01:59,780 So in this case we see that water bottle 30 ounce water bottles are of the most orders followed by the 27 00:01:59,780 --> 00:02:02,130 patch kit and then tire tubes. 28 00:02:02,130 --> 00:02:02,870 Now this is good. 29 00:02:02,870 --> 00:02:04,480 It's a lot of information here. 30 00:02:04,640 --> 00:02:11,000 But one thing that I think we can do to really make this come to life a bit more is that some conditional 31 00:02:11,000 --> 00:02:18,710 formatting so we can go ahead and navigate to the format pain and obviously you've got matrix specific 32 00:02:18,710 --> 00:02:24,750 formatting here you can change different kind of matrix styles if you want. 33 00:02:24,770 --> 00:02:27,070 And again you can always revert to the default. 34 00:02:27,460 --> 00:02:32,720 And generally speaking the default is actually going to serve our purposes pretty well in most of these 35 00:02:32,720 --> 00:02:38,080 cases so I'm not going to mess with tons of different formatting options as we build this out. 36 00:02:38,450 --> 00:02:44,540 But what I will do here is go all the way down to conditional formatting and it lets you format each 37 00:02:44,540 --> 00:02:46,340 series individually. 38 00:02:46,340 --> 00:02:52,670 So starting with total orders for this one I want to add data bars and you can see what each of these 39 00:02:52,670 --> 00:02:53,150 looks like. 40 00:02:53,190 --> 00:02:54,800 Those are data bars. 41 00:02:55,250 --> 00:02:56,930 That's the font color. 42 00:02:57,290 --> 00:03:00,410 And this is the background so font color and background work. 43 00:03:00,440 --> 00:03:05,810 Same kind of way it's just you're either updating just the font itself or the whole background of the 44 00:03:05,810 --> 00:03:07,010 cell. 45 00:03:07,010 --> 00:03:13,340 So for this total orders column because it's a volume column kind of like using data bars and that will 46 00:03:13,340 --> 00:03:19,190 really draw attention to the difference between some of our top drivers and some of our lower driver 47 00:03:19,280 --> 00:03:21,150 products in terms of orders. 48 00:03:21,200 --> 00:03:25,520 So I can see it right here in the formatting pain and format return rate. 49 00:03:25,520 --> 00:03:31,170 And instead of data bars for the return rate because they're going to be kind of all over the place. 50 00:03:31,190 --> 00:03:35,760 What I'd rather do here is kind of a subtle background conditional format. 51 00:03:36,170 --> 00:03:37,910 So this is not subtle. 52 00:03:37,910 --> 00:03:40,760 This is very loud and aggressive. 53 00:03:40,760 --> 00:03:47,810 What I can do is drill into my advanced controls here and determine exactly what this gradient for my 54 00:03:47,810 --> 00:03:50,080 conditional format should look like. 55 00:03:50,150 --> 00:03:56,930 And in this case instead of this crazy green to red scale for something like return rate which is a 56 00:03:56,930 --> 00:04:01,580 negative metric what I'm going to do is reverse this. 57 00:04:01,580 --> 00:04:06,930 First of all because high values of return rate that's a bad thing not a good thing. 58 00:04:07,040 --> 00:04:11,210 And I'm going to adjust the colors themselves to make them a little bit more muted. 59 00:04:11,390 --> 00:04:15,590 So the maximum meaning for bad return rates. 60 00:04:15,590 --> 00:04:21,380 I want this kind of pale red and for the minimum I want to white. 61 00:04:21,380 --> 00:04:28,010 So this basically means that products with an ok return rate are relatively low return rate will show 62 00:04:28,010 --> 00:04:28,960 up as white. 63 00:04:28,970 --> 00:04:35,150 There won't be huge negative attention drawn to them and only the ones that really start to have some 64 00:04:35,150 --> 00:04:39,920 of the higher levels of return rates will start to pop with this red shading. 65 00:04:40,010 --> 00:04:41,380 So let's press OK there. 66 00:04:41,450 --> 00:04:48,020 And as you can see it's pretty subtle but in this case it does get the job done so you can see certain 67 00:04:48,020 --> 00:04:56,190 cases where individual products are popping a little bit more like this road 650 whereas the other ones 68 00:04:56,190 --> 00:05:01,200 with kind of average or decent below average return rates. 69 00:05:01,200 --> 00:05:02,240 Those kind of just fade. 70 00:05:02,250 --> 00:05:05,780 And with this white background so feel free to make your own adjustments. 71 00:05:05,790 --> 00:05:08,370 But that's kind of my personal style. 72 00:05:08,370 --> 00:05:13,200 Keep it a little bit more muted while still drawing attention to the key trends. 73 00:05:13,200 --> 00:05:19,620 Now last thing that I want to do with this matrix view is go back to fields and instead of only showing 74 00:05:19,620 --> 00:05:22,740 the data by product just like I showed you before. 75 00:05:22,800 --> 00:05:31,790 Let's go ahead and grab the subcategory just beneath my product look up bring the subcategory name in 76 00:05:32,960 --> 00:05:36,340 as well as the category name. 77 00:05:36,740 --> 00:05:38,420 And then you know the drill. 78 00:05:38,600 --> 00:05:42,510 No pun intended you can drill all the way back down. 79 00:05:42,670 --> 00:05:45,090 So now I'm seeing that same product level view. 80 00:05:45,320 --> 00:05:50,710 But I've just given the user the option to aggregate if they choose to do so. 81 00:05:51,090 --> 00:05:53,810 And one last note here that little forked arrow. 82 00:05:53,810 --> 00:06:01,450 The third option that will expand down all the way one by one until you're seeing not only the lowest 83 00:06:01,450 --> 00:06:07,840 level the products but you're also seeing them grouped into subcategories and then into categories. 84 00:06:07,870 --> 00:06:13,620 This is very much like the outline table layout in a pivot table in Excel. 85 00:06:13,780 --> 00:06:19,710 So just go ahead and drill back up and then back down to get back to where we started. 86 00:06:19,720 --> 00:06:21,790 So I love these matrix views. 87 00:06:21,880 --> 00:06:27,760 I think they're incredibly useful and insightful they pack a ton of information and these conditional 88 00:06:27,760 --> 00:06:34,270 formatting tools are great ways to really bring some of that data to life and expose some interesting 89 00:06:34,270 --> 00:06:35,030 patterns. 90 00:06:35,200 --> 00:06:35,940 So there you go. 91 00:06:35,980 --> 00:06:37,360 That's a report matrix view. 9447

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