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These are the user uploaded subtitles that are being translated: 1 00:00:05,210 --> 00:00:06,630 Welcome to this lesson. 2 00:00:06,650 --> 00:00:11,180 So you've had a discussion with your human resource department, and they actually really like this 3 00:00:11,180 --> 00:00:13,190 table that you've just produced here. 4 00:00:13,340 --> 00:00:19,190 And what they would like to do is to actually produce a summary table that's just got this data in it, 5 00:00:19,190 --> 00:00:21,140 maybe a couple of extra pieces of data. 6 00:00:21,140 --> 00:00:25,190 For example, they would like to know what is the total number of sick leave hours by each of the job 7 00:00:25,190 --> 00:00:27,770 positions and what is the vacation hours. 8 00:00:28,400 --> 00:00:33,020 So let's say we wanted to create this as a separate table, as a summary table that we could then use 9 00:00:33,020 --> 00:00:34,190 within our reports. 10 00:00:34,670 --> 00:00:34,790 Okay. 11 00:00:34,820 --> 00:00:36,920 We're going to go back to our transform data. 12 00:00:36,950 --> 00:00:41,780 And what we're going to look at is how we create this data now and how we could aggregate it. 13 00:00:42,170 --> 00:00:46,100 So we've created a query, and this is called Employee Master. 14 00:00:46,520 --> 00:00:52,430 If I right click on this, it then allows me to be able to have options as to what I want to do with 15 00:00:52,430 --> 00:00:53,180 this query. 16 00:00:53,570 --> 00:00:57,110 Now, two of the important options are called duplicate and reference. 17 00:00:57,740 --> 00:01:02,960 If I use duplicate, what it will do is it will create a new table and it will duplicate all of the 18 00:01:02,960 --> 00:01:05,480 applied steps that the table has. 19 00:01:05,630 --> 00:01:09,800 But it will only duplicate the applied steps as at the moment in time. 20 00:01:10,310 --> 00:01:15,290 Later on, if I go back and I make changes to the source table, it will not actually update the new 21 00:01:15,290 --> 00:01:16,640 table with those changes. 22 00:01:17,150 --> 00:01:22,220 However, if I use reference, what it will do is just reference this table and if I make any changes 23 00:01:22,220 --> 00:01:23,810 to this table, then it will. 24 00:01:24,050 --> 00:01:26,780 It will use those changes with the new table. 25 00:01:27,140 --> 00:01:29,810 So in this example, we're going to use reference. 26 00:01:30,050 --> 00:01:32,090 So I'm going to say we're going to reference the table. 27 00:01:32,300 --> 00:01:35,190 As you can see, I've now got a new query that is being created. 28 00:01:35,210 --> 00:01:39,290 However, it's only got one step, which is my plot step source. 29 00:01:39,890 --> 00:01:44,760 If I go back to my advanced editor, you'll see that the source is the employee master. 30 00:01:44,780 --> 00:01:49,790 So basically, at the moment, all we're doing is referencing that I'm going to change this name, so 31 00:01:49,790 --> 00:01:51,800 let's call this our summary. 32 00:01:52,710 --> 00:01:55,680 Okay, So that's our summary table, right? 33 00:01:55,680 --> 00:02:00,720 So what we want to do now is we want to change this so that we're going to see our job position and 34 00:02:00,720 --> 00:02:03,570 then we're going to see that information that we were just talking about. 35 00:02:03,690 --> 00:02:07,920 And what we're going to do for that is we're going to use a function called group by. 36 00:02:08,009 --> 00:02:09,419 So group by is really great. 37 00:02:09,419 --> 00:02:13,290 When you want to create summary tables, you want to see key metrics, You want to see your key performance 38 00:02:13,290 --> 00:02:14,580 indicators, for example. 39 00:02:15,060 --> 00:02:19,320 So we're going to select group by and you can see that we get two options for group by. 40 00:02:19,320 --> 00:02:20,370 We've got basic and advance. 41 00:02:20,370 --> 00:02:24,840 We're going to jump to Advanced, which just allows us to be able to choose multiple fields. 42 00:02:25,260 --> 00:02:27,840 Now the first one is what are we grouping by now? 43 00:02:27,840 --> 00:02:32,610 In this case, we actually want to group by job position, and I'm actually going to add another grouping, 44 00:02:32,610 --> 00:02:34,280 which is our gender. 45 00:02:34,320 --> 00:02:38,370 So we're going to say we're going to have job position and our gender as our two groupings. 46 00:02:38,610 --> 00:02:41,730 It then allows me to add different aggregations down here. 47 00:02:41,880 --> 00:02:47,340 So let's say that the first one I want to know is what is my average age for each of my job positions 48 00:02:47,340 --> 00:02:48,150 and genders. 49 00:02:48,150 --> 00:02:53,340 So my operation that I'm going to perform on this is an average and I'm going to choose my column. 50 00:02:53,490 --> 00:02:58,290 And what we're going to say is that we actually now want to be able to do this on my age. 51 00:02:58,290 --> 00:03:00,030 So I'm going to pick my age column. 52 00:03:00,900 --> 00:03:05,160 I could also add a new aggregation unless I want to know what it is the. 53 00:03:06,040 --> 00:03:06,520 Highest. 54 00:03:07,450 --> 00:03:08,590 Just correct that. 55 00:03:09,130 --> 00:03:12,160 And we're going to say operation on this one is going to be a max. 56 00:03:12,790 --> 00:03:15,100 And again, we're going to do it on our edge. 57 00:03:15,550 --> 00:03:17,410 Could also say what is the lowest eight? 58 00:03:18,280 --> 00:03:20,350 So I think you're getting the idea on how this works. 59 00:03:20,350 --> 00:03:25,300 We're just basically putting a column name in or picking a way that this is going to operate. 60 00:03:25,300 --> 00:03:30,340 And then we're choosing what is the field that we're going to do and just see if we can move this up 61 00:03:30,340 --> 00:03:31,030 a little bit. 62 00:03:31,360 --> 00:03:31,500 Okay. 63 00:03:31,600 --> 00:03:32,950 So we just moved it up a little bit. 64 00:03:32,950 --> 00:03:33,370 There we go. 65 00:03:33,370 --> 00:03:35,050 Now you can see the fields a bit better. 66 00:03:35,050 --> 00:03:36,430 I'm going to pick our age again. 67 00:03:36,430 --> 00:03:39,070 So we've got our average age, high stage, low stage. 68 00:03:39,070 --> 00:03:44,560 Let's say we want to count how many people we've got so we can say a number of employees and we're going 69 00:03:44,560 --> 00:03:45,550 to count the rows here. 70 00:03:45,550 --> 00:03:49,600 So we don't need to pick a particular column and add another aggregation. 71 00:03:49,600 --> 00:03:53,800 And we could say that we wanted to know what is the number of vacation hours. 72 00:03:53,800 --> 00:03:57,130 So we're going to say number of vacation hours. 73 00:03:58,060 --> 00:04:03,850 So field name, in this case, we would use a sum and we would then be using our vacation hours. 74 00:04:04,030 --> 00:04:08,230 And let's say the last one is on number of sick leave hours. 75 00:04:10,370 --> 00:04:11,380 Okay, So there we go. 76 00:04:11,430 --> 00:04:14,240 Some Now we're going to pick our sick leave hours. 77 00:04:14,930 --> 00:04:15,040 Okay. 78 00:04:15,080 --> 00:04:18,560 So I'm going to click okay on this and you're going to see quite a transformation happen. 79 00:04:18,589 --> 00:04:23,980 So basically, the table now has changed to show this grouped rows that I have now set up. 80 00:04:23,990 --> 00:04:27,140 So you can see that you've got your job position, you've got your gender, and then you've actually 81 00:04:27,140 --> 00:04:29,240 got the results of all those calculations. 82 00:04:29,240 --> 00:04:33,770 So this is now showing in that table view the results of that. 83 00:04:34,860 --> 00:04:39,810 If it didn't time you wanted to go back and you wanted to make changes, you could click on the icon 84 00:04:39,810 --> 00:04:43,590 and you could just go back in here and you could make any changes that you would want. 85 00:04:44,400 --> 00:04:45,420 Guess I'm happy with that. 86 00:04:45,420 --> 00:04:49,740 We're going to close and apply and we're going to now take this data back into power by and you can 87 00:04:49,740 --> 00:04:55,320 now see that I have a second table, which is my summary table, and I have all that detail. 88 00:04:55,320 --> 00:04:59,460 So if we delete this now, let's just say we create a new table. 89 00:04:59,490 --> 00:05:02,220 We'll just collapse that and create a new table. 90 00:05:04,460 --> 00:05:05,360 And. 91 00:05:06,610 --> 00:05:07,480 Again in this case. 92 00:05:07,480 --> 00:05:14,290 Now, we wanted to see all this just do a bad job position and then you could just drag these fields 93 00:05:14,290 --> 00:05:16,650 in that you wanted to see. 94 00:05:16,660 --> 00:05:16,990 Again. 95 00:05:16,990 --> 00:05:18,850 You can see the average age now it's sundered. 96 00:05:18,850 --> 00:05:21,040 So we would actually have to average that out. 97 00:05:21,900 --> 00:05:22,950 Lowest wage. 98 00:05:23,460 --> 00:05:26,910 See again summed it so we'd now say that we would want to know the men. 99 00:05:28,000 --> 00:05:30,580 Had a pretty easy to change number of employees. 100 00:05:31,680 --> 00:05:32,340 There we go. 101 00:05:32,770 --> 00:05:34,050 Number of sick hours. 102 00:05:35,910 --> 00:05:39,870 And you've now got your new table from your new summary table. 103 00:05:40,110 --> 00:05:44,700 As I said, basically, I just wanted to show you an example of using the group by option and just showing 104 00:05:44,700 --> 00:05:50,340 you how you can easily aggregate data and change the tables into new types of tables that just show 105 00:05:50,340 --> 00:05:51,870 that summary information. 106 00:05:52,260 --> 00:05:52,380 Okay. 107 00:05:52,380 --> 00:05:53,790 We're going to conclude the lesson there. 108 00:05:53,820 --> 00:05:54,930 I will see you in the next one. 10315

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