2025-08-26_inventory_data_mart_sync_1ca17a30

Meeting Title: Inventory Data Mart Sync Date: 2025-08-26 Meeting participants: Emily’s Fellow Note Taker, Emily Giant, Demilade Agboola, Uttam Kumaran

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WEBVTT

1 00:01:21.120 ⇒ 00:01:22.000 Emily Giant: Hi.

2 00:01:22.880 ⇒ 00:01:24.280 Demilade Agboola: Hi, Emily, how are you?

3 00:01:24.950 ⇒ 00:01:27.390 Emily Giant: I’m good, long time no see, how are you?

4 00:01:27.920 ⇒ 00:01:34.580 Demilade Agboola: I’m alright. I was a bit under the weather yesterday, but I’m much better today.

5 00:01:35.660 ⇒ 00:01:48.520 Emily Giant: I was gonna say, you were, like, usually, even if I don’t see you, we’ll chat a bunch during the day, and I didn’t… I didn’t see a lot of action from you, so I… I had, like, a sixth sense that you were under the weather yesterday.

6 00:01:48.830 ⇒ 00:01:53.439 Demilade Agboola: Yeah, yes I was, but… definitely much better today.

7 00:01:53.860 ⇒ 00:02:06.789 Emily Giant: That’s good. I stayed up on… I worked all weekend trying to fix stuff, and stayed up till 6 AM working from… on Sunday morning, woke up, worked till 6 AM Monday morning, so…

8 00:02:06.790 ⇒ 00:02:20.000 Emily Giant: Yesterday, I was, an idiot because I didn’t sleep. So, it was probably for the best that we just didn’t do a lot of work yesterday, in sync. I think he would have been like, okay, she’s… she’s lost it.

9 00:02:20.010 ⇒ 00:02:24.750 Emily Giant: How’s swimming and house tennis? I have to check in with the important things.

10 00:02:25.460 ⇒ 00:02:30.619 Demilade Agboola: Tennis is fine. Started playing games now.

11 00:02:30.910 ⇒ 00:02:31.710 Emily Giant: Oh, sweet.

12 00:02:32.080 ⇒ 00:02:45.330 Demilade Agboola: Yeah, learning how to put everything together is the really tricky part right now. Like, some points I’m really good, some points I’m really bad. Just trying to get, like, a good baseline to have that consistent.

13 00:02:45.770 ⇒ 00:02:50.219 Demilade Agboola: Swimming is alright, not… not drowned yet, but, like.

14 00:02:51.050 ⇒ 00:02:53.659 Demilade Agboola: I’m down to… I’m down to, like, one noodle.

15 00:02:53.940 ⇒ 00:02:56.219 Demilade Agboola: But it’s still… it’s still a big trip.

16 00:02:56.220 ⇒ 00:03:06.840 Emily Giant: That’s awesome, though. Yeah, to me, it’s really hard. I was at the lake last weekend with my nephews, and my family, and I can do it. Like, I can not drown.

17 00:03:07.100 ⇒ 00:03:20.800 Emily Giant: But I’m not good. I’m like, this is not… I wouldn’t call it a survival skill. Like, I’m not surviving. But I can… I can stay afloat. Like, I can take the breath in and, like, float, but I’m not great at, like, actually

18 00:03:22.440 ⇒ 00:03:28.070 Emily Giant: I was thinking, do you… I don’t think pickleball’s huge in Malta. It’s huge here.

19 00:03:28.210 ⇒ 00:03:34.830 Emily Giant: But I haven’t played it all this summer. And a couple summers ago, I was really into it, and I love tennis, but I’m not good.

20 00:03:34.910 ⇒ 00:03:51.309 Emily Giant: But, like, one of the things I forgot that I do, and I need to check, like, I don’t know if there’s a test you take, whenever I hit the ball, I throw it to my left hand and hit it. Like, I take the racket and I toss it, and everyone’s like, Emily, I think you’re left-handed, and I’m like, I don’t think so.

21 00:03:51.400 ⇒ 00:04:00.620 Emily Giant: But it’s so subconscious, like, I just want to use my left hand, and I’m better with my left hand, but I’ve always written with my right hand, I’ve always, like.

22 00:04:01.820 ⇒ 00:04:04.760 Demilade Agboola: Do you know the Rafael Nadal?

23 00:04:05.770 ⇒ 00:04:06.559 Emily Giant: What is it?

24 00:04:06.800 ⇒ 00:04:09.020 Demilade Agboola: Do you know a guy called Rafael Nadal?

25 00:04:11.410 ⇒ 00:04:12.440 Emily Giant: Tennis player?

26 00:04:12.640 ⇒ 00:04:13.260 Demilade Agboola: Yes.

27 00:04:13.710 ⇒ 00:04:15.659 Emily Giant: Yeah, yeah, I know the name.

28 00:04:15.850 ⇒ 00:04:25.039 Demilade Agboola: Okay, so Nadal is one of the greatest tennis players of all times… of all time, and he’s left-handed when he plays, but he’s actually right-handed as an individual, so….

29 00:04:25.040 ⇒ 00:04:32.030 Emily Giant: Oh my gosh, I… I might be one of the best tennis players of all times! I didn’t know!

30 00:04:33.080 ⇒ 00:04:36.149 Demilade Agboola: So, just maybe, maybe.

31 00:04:36.670 ⇒ 00:04:44.450 Emily Giant: oh man, now I really want to take lessons, just so I can tell an instructor that, and have them watch me be as bad as I am.

32 00:04:45.070 ⇒ 00:04:51.890 Emily Giant: True, that’s pretty cool. I really do think tennis would be, like, a fun thing, to just be able to, like, do on weekends.

33 00:04:52.500 ⇒ 00:04:59.969 Demilade Agboola: Well, it definitely is. It’s a really nice sport. Yeah. And it can really be addictive, at least for me. It gets.

34 00:04:59.970 ⇒ 00:05:00.920 Emily Giant: Oh, yeah.

35 00:05:01.890 ⇒ 00:05:05.459 Demilade Agboola: So, yeah, I do enjoy, I really do enjoy it.

36 00:05:05.870 ⇒ 00:05:07.330 Emily Giant: It’s pretty cool.

37 00:05:08.850 ⇒ 00:05:16.700 Demilade Agboola: But yeah, I think that’s… that’s currently what I’m trying to do. I’m trying to just become really good at it.

38 00:05:16.920 ⇒ 00:05:18.240 Demilade Agboola: It’s a process.

39 00:05:18.730 ⇒ 00:05:22.610 Emily Giant: Not just… not just, like, workable, but really good at it. That’s… that’s…

40 00:05:22.940 ⇒ 00:05:26.549 Emily Giant: how I’d sum you up, like, I can’t just do it.

41 00:05:27.360 ⇒ 00:05:30.010 Emily Giant: I gotta slay it!

42 00:05:30.010 ⇒ 00:05:35.039 Demilade Agboola: I really, I really, I really want to be able to hold my own, like, across different, like.

43 00:05:35.910 ⇒ 00:05:38.380 Demilade Agboola: places I play, …

44 00:05:38.490 ⇒ 00:05:52.149 Demilade Agboola: So that, for me, is kind of what pushes me. It’s fun, it really is fun, and there’s always so much to learn. I’m even thinking at some point, I might want to learn with my left hand how to play for a bit, just for the fun of it.

45 00:05:52.150 ⇒ 00:05:57.180 Emily Giant: I’ll tell ya, you might… you might be better. You might be better with your left hand.

46 00:05:57.180 ⇒ 00:05:58.850 Demilade Agboola: You never could tell.

47 00:05:58.850 ⇒ 00:06:10.339 Emily Giant: It’s so funny. You never know until you… well, truly, like, it’s so, like, automatic, my switching. It’s like my brain’s like, no, girl, no, you gotta use that left hand.

48 00:06:10.820 ⇒ 00:06:17.819 Demilade Agboola: You know, you can try it, maybe give it a shot, maybe you’ll discover that it’s a bit more consistent and more stable.

49 00:06:18.850 ⇒ 00:06:23.419 Emily Giant: I need to just, like, work in time to actually practice, because that’s one of those sports, too, that…

50 00:06:23.900 ⇒ 00:06:42.790 Emily Giant: you can play as you get older. You don’t have to be, like, as fast or as strong. Like, you need to to be really good at it, but I’m not gonna be really good at tennis. I think that ship has sailed. So as long as I can just, like, play with friends and not have them mad at me by the end of the game for, like, just being wild, then that’s kind of my goal.

51 00:06:43.270 ⇒ 00:06:43.800 Demilade Agboola: That’s.

52 00:06:43.800 ⇒ 00:06:45.310 Emily Giant: I’m inspired.

53 00:06:45.410 ⇒ 00:07:02.860 Emily Giant: All right, so I’ve done a ton of work, none of it has been deployed, because I’ve just been testing, testing, testing, and I talked to Alex and Zach about, like, the magnitude of the changes I made in one model, but it was one of those where, like, you really can’t change certain things without changing the downstream.

54 00:07:03.510 ⇒ 00:07:08.820 Emily Giant: So I tried to, instead of, like, changing the downstream, just build, like.

55 00:07:09.240 ⇒ 00:07:17.510 Emily Giant: make a new model that won’t be connected to production like we talked about at the beginning of the engagement. But let me share my screen.

56 00:07:19.500 ⇒ 00:07:28.649 Emily Giant: But I think it is gonna tie into some of the work that you’re doing. If not the work you’re doing, it’s probably gonna, like, negate it, but I think that, like, either way, …

57 00:07:29.660 ⇒ 00:07:32.839 Emily Giant: Looker will be in a better place with, like, what…

58 00:07:33.240 ⇒ 00:07:38.740 Emily Giant: what we’ve both been working on. So… First, foremost, …

59 00:07:39.150 ⇒ 00:07:47.029 Emily Giant: I updated the historical inventory so that we no longer have to use the, like, Old formatting, like.

60 00:07:47.190 ⇒ 00:07:56.760 Emily Giant: months ago, we did, like, the Shopify, sales adjustments versus Salesforce sales adjustments. Those were, like, very much aligned to, like.

61 00:07:57.110 ⇒ 00:08:00.079 Emily Giant: An old way that we looked at inventory, so…

62 00:08:00.520 ⇒ 00:08:04.459 Emily Giant: I, refractored all of that into

63 00:08:05.110 ⇒ 00:08:08.099 Emily Giant: Let me go to the mart, and then look at the lineage from there.

64 00:08:09.910 ⇒ 00:08:14.310 Emily Giant: So, now we have the inventory adjustment mart.

65 00:08:14.530 ⇒ 00:08:19.410 Emily Giant: which I’m still having, like, very minor issues with, but them being…

66 00:08:20.020 ⇒ 00:08:27.020 Emily Giant: That, like, some of the uncommitted orders that should have inventory numbers or lots

67 00:08:27.160 ⇒ 00:08:36.799 Emily Giant: are getting tagged as unlauded because they didn’t claim correctly, but that’s, like, so minor, I don’t even care. It’s not throwing off numbers, it’s just throwing off, like.

68 00:08:37.440 ⇒ 00:08:40.940 Emily Giant: the table that it came from. So…

69 00:08:41.080 ⇒ 00:08:47.020 Emily Giant: Here we’ve got, like, our inventory final sales adjustments, final reconciliation adjustments.

70 00:08:47.370 ⇒ 00:08:57.460 Emily Giant: But if you go into these, they both are, like, very cleanly tied in the way that we made the adjustment mart to Legacy. So, …

71 00:08:57.840 ⇒ 00:09:01.750 Emily Giant: like, if I could, I filled in all the information from the legacy lots.

72 00:09:02.420 ⇒ 00:09:04.190 Emily Giant: with, …

73 00:09:04.670 ⇒ 00:09:16.750 Emily Giant: the information that we use now, and for the most part, it looks really good, it’s really helped clean up ComponentsXF, it’s helped clean up revenue, it’s able to, like, wear,

74 00:09:17.250 ⇒ 00:09:24.009 Emily Giant: in ComponentsXF, if there’s missing information about a component in a sale, it’s almost, like.

75 00:09:24.150 ⇒ 00:09:33.919 Emily Giant: Knock on wood, but I haven’t found one yet in Legacy Inventory Adjustments that doesn’t have all the products associated with it. And, prior to, like.

76 00:09:33.920 ⇒ 00:09:44.839 Emily Giant: I mean, our polyatomic stuff was always fine, but the historical was not. There were just things, like, obscured because we didn’t have suborder ID granularity, blah blah blah blah blah. But…

77 00:09:44.860 ⇒ 00:09:49.770 Emily Giant: did that… For reconciliations and adjustments, …

78 00:09:49.950 ⇒ 00:10:00.569 Emily Giant: it’s looking good, it’s testing out, wonderful. I do not know how to update the snapshot, for using surrogate key.

79 00:10:00.860 ⇒ 00:10:11.529 Emily Giant: for inventory adjustments and inventory lot table, I cannot figure it out to save my life. So that’s question number one. Question number two is…

80 00:10:12.050 ⇒ 00:10:13.140 Emily Giant: I…

81 00:10:13.370 ⇒ 00:10:28.870 Emily Giant: so we had talked about, like, having everything available in Walmart instead of inventory adjustments and inventory lot. I still haven’t consolidated it down to that. However, in both, the adjustments and reconciliations.

82 00:10:29.130 ⇒ 00:10:34.020 Emily Giant: I… Let me go to the model where I did this. But I summed…

83 00:10:34.290 ⇒ 00:10:37.360 Emily Giant: All of the sales, so that, like.

84 00:10:37.780 ⇒ 00:10:40.309 Emily Giant: In my head, if I did it early.

85 00:10:40.540 ⇒ 00:10:45.629 Emily Giant: you’d be able to roll it up more easily later on, right? Like, if you do…

86 00:10:46.110 ⇒ 00:10:48.610 Emily Giant: If I show you easier.

87 00:10:49.080 ⇒ 00:10:51.489 Emily Giant: Inventory. Silver Union.

88 00:10:56.420 ⇒ 00:10:59.559 Emily Giant: Can’t remember where I do it, maybe in suborder types.

89 00:11:00.770 ⇒ 00:11:02.550 Emily Giant: Yes. Okay.

90 00:11:04.410 ⇒ 00:11:05.190 Emily Giant: No.

91 00:11:05.410 ⇒ 00:11:07.060 Emily Giant: That’s not it at all.

92 00:11:08.260 ⇒ 00:11:13.859 Emily Giant: Oh, yeah. Okay, so, instead of just having coalesce 0, I did a sum.

93 00:11:14.720 ⇒ 00:11:15.859 Demilade Agboola: Does that….

94 00:11:16.250 ⇒ 00:11:18.589 Emily Giant: So, at the earliest part where we’re…

95 00:11:19.050 ⇒ 00:11:30.409 Emily Giant: like, visualizing the sales numbers. I’m doing a sum. Does that mean that later on in the lineage, it’s still summed? So that, like, when we get to this, like.

96 00:11:30.730 ⇒ 00:11:36.060 Emily Giant: Instead of here, where we’d previously Thumbed everything again.

97 00:11:36.850 ⇒ 00:11:39.599 Emily Giant: I don’t need to do that, right? They’re already summed.

98 00:11:42.770 ⇒ 00:11:51.460 Demilade Agboola: Yes, so these are already summed by the… but it has to be the same granularity. These are summed by the inventory number, right? Or is it by the sum?

99 00:11:51.460 ⇒ 00:11:52.290 Emily Giant: Yes.

100 00:11:52.890 ⇒ 00:11:55.570 Emily Giant: Well, yes, the inventory number.

101 00:11:55.570 ⇒ 00:11:58.250 Demilade Agboola: These are sold by the inventory number, and then…

102 00:11:58.460 ⇒ 00:12:02.429 Demilade Agboola: When we use them further down, it’s still on the inventory number.

103 00:12:03.500 ⇒ 00:12:05.149 Emily Giant: No, suborder ID.

104 00:12:07.650 ⇒ 00:12:15.010 Emily Giant: So, the inventory adjustments is one line… no, not even suborder ID, that’s wrong. It’s one line per item.

105 00:12:17.800 ⇒ 00:12:21.920 Emily Giant: And then, in inventory lot balance, it’s one line per lot.

106 00:12:24.180 ⇒ 00:12:27.400 Demilade Agboola: And each lot has multiple items, right?

107 00:12:28.100 ⇒ 00:12:30.369 Emily Giant: No. A lot only has one item.

108 00:12:30.560 ⇒ 00:12:36.929 Emily Giant: But they have multiple… sales, and several varieties, but it’s still only one item.

109 00:12:37.990 ⇒ 00:12:44.459 Demilade Agboola: Alright, so the fact that we’re viewing it either by item or by inventory number should still give us the same number?

110 00:12:46.380 ⇒ 00:12:49.349 Demilade Agboola: Oh, okay Yeah, Max, I don’t think we need to summit.

111 00:12:50.770 ⇒ 00:12:51.630 Emily Giant: Sweet.

112 00:12:52.040 ⇒ 00:12:56.000 Emily Giant: And will it double summit if I do, is my other question.

113 00:12:57.000 ⇒ 00:13:00.440 Demilade Agboola: What’s the… what’s the grain on the table we’re using it for, or using it on?

114 00:13:01.180 ⇒ 00:13:04.309 Emily Giant: The grain is… item.

115 00:13:06.220 ⇒ 00:13:08.770 Demilade Agboola: So it shouldn’t double summit?

116 00:13:09.710 ⇒ 00:13:15.090 Demilade Agboola: Okay. Because there should only be one row for each… of these.

117 00:13:17.680 ⇒ 00:13:23.879 Emily Giant: So, this is essentially, like, a moot point. This whole table is just summing

118 00:13:24.240 ⇒ 00:13:26.380 Emily Giant: The lines that are already summed.

119 00:13:26.510 ⇒ 00:13:35.320 Emily Giant: So, like, in a future where I have human time to do this, I could just X that out and skip right to

120 00:13:36.330 ⇒ 00:13:38.239 Emily Giant: The active lot balance.

121 00:13:39.140 ⇒ 00:13:39.930 Demilade Agboola: Okay.

122 00:13:41.070 ⇒ 00:13:41.740 Emily Giant: Okay.

123 00:13:41.890 ⇒ 00:13:47.080 Emily Giant: So, essentially, I’m, like, creeping slowly towards only one mart.

124 00:13:47.710 ⇒ 00:13:54.560 Emily Giant: … Hard goods are… Part of the snapshot question.

125 00:13:54.950 ⇒ 00:13:59.580 Emily Giant: So, the lot of stuff is, like, Fine.

126 00:13:59.790 ⇒ 00:14:11.210 Emily Giant: it’s the unlotted now that I’m like, okay, how do I present this to stakeholders in a way that makes sense to them? And that’s, I think, where the snapshot data comes in.

127 00:14:12.040 ⇒ 00:14:15.080 Emily Giant: Sorry, that’s a… So, let me pull it up real quick.

128 00:14:18.670 ⇒ 00:14:21.949 Emily Giant: So they obviously don’t have lots or inventory numbers.

129 00:14:22.120 ⇒ 00:14:26.780 Emily Giant: So, you and I talked a million years ago about summing them on, …

130 00:14:29.430 ⇒ 00:14:34.979 Emily Giant: location and item ID, and then date, so that people could

131 00:14:35.090 ⇒ 00:14:50.830 Emily Giant: query them, for a specific period of time. So that, to me, is, like, what the snapshot is, right? Like, I don’t really need to add the grain of date, because a snapshot, if that’s what’s in Looker, that’s what provides

132 00:14:51.940 ⇒ 00:14:53.030 Emily Giant: the date.

133 00:14:53.400 ⇒ 00:15:02.210 Emily Giant: Or do I need to? If I pull this up and stop, like, chicken hawking, it will make more sense. Inventory unlotted reconciliations…

134 00:15:04.620 ⇒ 00:15:05.810 Emily Giant: into ag.

135 00:15:10.350 ⇒ 00:15:16.520 Demilade Agboola: Oh, by the way, I just sent a PR… for, like… Futs.

136 00:15:17.800 ⇒ 00:15:18.440 Demilade Agboola: other….

137 00:15:18.440 ⇒ 00:15:19.250 Emily Giant: Oh, sweet.

138 00:15:19.780 ⇒ 00:15:22.610 Demilade Agboola: It’s… it’s a motherload, to be honest.

139 00:15:22.610 ⇒ 00:15:29.650 Emily Giant: Sounds like we’re both unloading today with our PRs, which is delightful.

140 00:15:30.250 ⇒ 00:15:38.730 Emily Giant: Okay, so… Right and now… This unlotted sales and period’s exactly what I want.

141 00:15:40.500 ⇒ 00:15:43.250 Emily Giant: So, right now, I have, …

142 00:15:50.600 ⇒ 00:15:58.830 Emily Giant: this is the final, like, aggregate before inventory adjustment mart, where I just union this to the, the lots.

143 00:15:59.110 ⇒ 00:16:02.339 Emily Giant: But I have the grain… I have it by adjustment week.

144 00:16:02.510 ⇒ 00:16:05.690 Emily Giant: And then every…

145 00:16:06.300 ⇒ 00:16:14.050 Emily Giant: So we aggregate it by location and item ID, because that’s what makes an unlotted product unique.

146 00:16:14.350 ⇒ 00:16:21.710 Emily Giant: But, because there’s no start and end date, I’m still unclear on how users Could say, like.

147 00:16:22.500 ⇒ 00:16:26.490 Emily Giant: What is the lot balance and sales for last week?

148 00:16:27.180 ⇒ 00:16:35.069 Emily Giant: So… I added weak, but I’m feeling like… It’s different behavior.

149 00:16:36.030 ⇒ 00:16:47.759 Emily Giant: So, hypothetically, let’s say a user’s in Looker, and they want to pull all sales on the firecracker and glass vases by lot vase last week.

150 00:16:48.170 ⇒ 00:16:50.120 Emily Giant: And then also see the balance.

151 00:16:51.710 ⇒ 00:17:02.859 Emily Giant: because… There is no date associated with non-lotted goods outside of the date of the sale.

152 00:17:04.099 ⇒ 00:17:11.009 Emily Giant: I’m still, like, unclear on… How they would query a specific period of time.

153 00:17:11.310 ⇒ 00:17:13.020 Emily Giant: For an unlotted good.

154 00:17:13.569 ⇒ 00:17:15.589 Emily Giant: Without having the date added.

155 00:17:16.030 ⇒ 00:17:16.970 Emily Giant: But…

156 00:17:17.520 ⇒ 00:17:26.100 Emily Giant: is that not what snapshot data does? Like, if we had snapshot data for hard goods in Looker, would that be able to pull

157 00:17:27.109 ⇒ 00:17:29.950 Emily Giant: sales last Tuesday for hard goods.

158 00:17:30.920 ⇒ 00:17:37.809 Demilade Agboola: Yeah, ideally. So, okay, so let me ask you this right now. If you wanted to see the value

159 00:17:38.070 ⇒ 00:17:41.580 Demilade Agboola: Of, like, right now, can we see it?

160 00:17:42.330 ⇒ 00:17:42.980 Emily Giant: Yes.

161 00:17:43.570 ⇒ 00:17:53.339 Demilade Agboola: If it’s… if we can see right now, then the issue will just be, once we run Snapshots, we would always know what’s happening right there, right? Right then.

162 00:17:53.540 ⇒ 00:17:57.480 Demilade Agboola: And so what we can then do is we can aggregate that value

163 00:17:58.560 ⇒ 00:18:02.770 Demilade Agboola: As time goes by, to different days, and then different weeks.

164 00:18:02.950 ⇒ 00:18:03.919 Demilade Agboola: And see here.

165 00:18:03.920 ⇒ 00:18:04.520 Emily Giant: Yes.

166 00:18:04.670 ⇒ 00:18:07.059 Demilade Agboola: This day, this is what that value was.

167 00:18:09.630 ⇒ 00:18:22.110 Emily Giant: Yep, that’s… that is what I need to present to users. But I’m still unclear on, like, what do I put in the snapshot table for unmodded goods to create that? Like, what kind of

168 00:18:23.130 ⇒ 00:18:27.730 Emily Giant: do I need to have the adjustment week here? Or is that just confusing?

169 00:18:29.690 ⇒ 00:18:33.480 Emily Giant: Because that’s going to create more lines. It’s going to create one line per week.

170 00:18:33.660 ⇒ 00:18:36.450 Emily Giant: Per item and location.

171 00:18:37.480 ⇒ 00:18:39.750 Demilade Agboola: Yeah, that’s fine. …

172 00:18:40.250 ⇒ 00:18:46.139 Demilade Agboola: But then the adjustment week, how do we get that? Like, what does the adjustment week represent? Is that the….

173 00:18:47.060 ⇒ 00:18:55.939 Emily Giant: it’s the date that any kind of movement on that product was made. So if it was deleted from inventory, if new ones came in, if

174 00:18:56.250 ⇒ 00:19:01.840 Emily Giant: there were sales. All of that would be represented. Like, the date that that happened.

175 00:19:02.310 ⇒ 00:19:02.660 Demilade Agboola: Okay.

176 00:19:02.660 ⇒ 00:19:11.249 Emily Giant: adjustment week. And I could do adjustment date, we could do, like, one line per day per item, but I feel like because lots are one line per lot.

177 00:19:11.410 ⇒ 00:19:14.779 Emily Giant: This is a… it’s a different grain.

178 00:19:18.110 ⇒ 00:19:25.179 Demilade Agboola: … let me say so… So, for each adjustment that occurs.

179 00:19:25.430 ⇒ 00:19:31.150 Demilade Agboola: So, the granularity of this is basically the adjustment week, And then, to lock the…

180 00:19:31.340 ⇒ 00:19:37.250 Demilade Agboola: Inventory, and then the value for that adjustment, or that week, basically.

181 00:19:37.610 ⇒ 00:19:38.130 Demilade Agboola: Right.

182 00:19:40.330 ⇒ 00:19:49.230 Emily Giant: So, yeah, the… It’s a weird table, but it does essentially mirror what the lot tables are.

183 00:19:49.500 ⇒ 00:19:58.800 Emily Giant: So these, like, the upper part of this merge is the movement of the inventory, and then the bottom part is just, like, the static

184 00:19:58.960 ⇒ 00:20:01.040 Emily Giant: current available inventory.

185 00:20:01.660 ⇒ 00:20:12.800 Demilade Agboola: Okay, that’s… so my… I think my question is this. Why are we having issues going into the past if we already know what adjustments

186 00:20:13.520 ⇒ 00:20:15.009 Demilade Agboola: Fell into what week?

187 00:20:17.490 ⇒ 00:20:25.110 Emily Giant: … I… I’m not saying that we do have issues.

188 00:20:25.250 ⇒ 00:20:36.920 Emily Giant: I’m saying that I’m concerned there are going to be issues, because of… There being multiple rows per week.

189 00:20:37.670 ⇒ 00:20:42.819 Emily Giant: Per item location for allotted versus one row per lot.

190 00:20:43.280 ⇒ 00:20:54.339 Emily Giant: for lawned goods. Like, are those two different to be in a table together? I want them to be in the table together. That is my goal, because that is how users

191 00:20:54.660 ⇒ 00:20:57.260 Emily Giant: like, I tried doing it separately, they don’t get it.

192 00:20:58.200 ⇒ 00:21:00.420 Demilade Agboola: Oh, that’s the issue.

193 00:21:03.440 ⇒ 00:21:07.360 Emily Giant: And I was thinking that, like, snapshot data

194 00:21:08.100 ⇒ 00:21:13.449 Emily Giant: If that is used for hard goods, or, I keep saying hard goods, for unlotted goods.

195 00:21:14.470 ⇒ 00:21:24.920 Emily Giant: That, to me, is a more, like, one-to-one with a lot of data, because it’s taking… It’s taking stock

196 00:21:25.920 ⇒ 00:21:29.750 Emily Giant: Of one thing over time versus multiple rows.

197 00:21:32.460 ⇒ 00:21:34.980 Emily Giant: per… item.

198 00:21:35.420 ⇒ 00:21:36.429 Emily Giant: location over here.

199 00:21:36.430 ⇒ 00:21:37.150 Demilade Agboola: Just…

200 00:21:37.820 ⇒ 00:21:43.670 Demilade Agboola: Can we, can we open, like, an, like, a random spreadsheet and just kind of, like, walk through the…

201 00:21:43.800 ⇒ 00:21:45.359 Demilade Agboola: In terms of sample data.

202 00:21:45.730 ⇒ 00:21:54.209 Demilade Agboola: Like, or just sample data doesn’t mean… just like, okay, so this has four rows, but we need it to have two rows, or we need it to have one row. So it’s much easier to…

203 00:21:54.810 ⇒ 00:21:55.410 Demilade Agboola: grasping.

204 00:21:55.410 ⇒ 00:21:56.120 Emily Giant: So…

205 00:21:59.510 ⇒ 00:22:00.560 Emily Giant: Product.

206 00:22:01.090 ⇒ 00:22:03.090 Emily Giant: The firecracker.

207 00:22:04.940 ⇒ 00:22:07.170 Emily Giant: inventory number.

208 00:22:10.810 ⇒ 00:22:12.089 Emily Giant: 1, 2, 3, 4.

209 00:22:12.880 ⇒ 00:22:16.070 Emily Giant: And then, like… on hand.

210 00:22:17.240 ⇒ 00:22:18.790 Emily Giant: Quantity sold…

211 00:22:20.000 ⇒ 00:22:30.430 Emily Giant: So, obviously, we need, like, all the columns that are currently in the mart, but, on hand and quantity sold are ostensibly different things, because one is, like.

212 00:22:30.750 ⇒ 00:22:34.309 Emily Giant: I mean, they are always different things, but it’s, like, a different…

213 00:22:34.530 ⇒ 00:22:39.190 Emily Giant: kind of movement, where quantity sold is, like, aggregating?

214 00:22:39.820 ⇒ 00:22:49.200 Emily Giant: on hand… oops… on hand is, like, what’s left, right? So they’re just different things, which, on a lot, makes sense.

215 00:22:49.590 ⇒ 00:22:51.929 Emily Giant: Okay, so on hand, let’s say 10.

216 00:22:52.710 ⇒ 00:22:54.250 Emily Giant: And quantity sold.

217 00:22:54.380 ⇒ 00:22:55.280 Emily Giant: 20.

218 00:22:56.340 ⇒ 00:22:57.690 Emily Giant: And then… ugh.

219 00:22:59.270 ⇒ 00:23:05.320 Emily Giant: These have the… Start date.

220 00:23:06.740 ⇒ 00:23:08.280 Emily Giant: an expiration date.

221 00:23:25.820 ⇒ 00:23:29.789 Emily Giant: Alright, so when users query this, they’ll usually put in, like.

222 00:23:31.050 ⇒ 00:23:34.240 Emily Giant: And there’s an adjustment date column.

223 00:23:34.570 ⇒ 00:23:42.019 Emily Giant: But what this will give you is, like, the max adjustment date, technically. So… It’s called Updated App.

224 00:23:43.420 ⇒ 00:23:44.240 Demilade Agboola: Okay.

225 00:23:44.580 ⇒ 00:23:45.589 Emily Giant: So this is…

226 00:23:52.000 ⇒ 00:24:00.090 Emily Giant: Alright, so for unlotted goods, we still have the adjustment dates, we just don’t have a start and expiration date, right? Yes, I have them set at, like.

227 00:24:02.060 ⇒ 00:24:08.230 Emily Giant: 2099 as the expiration, and, like, 20…

228 00:24:08.480 ⇒ 00:24:13.330 Emily Giant: 09 as the start. Just, like, a big, broad band of time.

229 00:24:13.570 ⇒ 00:24:16.380 Emily Giant: So, what happens is, you get, like.

230 00:24:17.470 ⇒ 00:24:21.950 Emily Giant: 1 million sales if you don’t have a start and end date.

231 00:24:22.250 ⇒ 00:24:25.589 Emily Giant: Or parameters for the updated app.

232 00:24:25.820 ⇒ 00:24:34.060 Emily Giant: But, what’s happening is… So… Last phase.

233 00:24:36.140 ⇒ 00:24:39.509 Emily Giant: Whereas these always change within the one line.

234 00:24:40.320 ⇒ 00:24:42.860 Emily Giant: Glass vase is gonna have a line.

235 00:24:43.140 ⇒ 00:24:50.620 Emily Giant: for every week So the on-hand number is gonna be the same.

236 00:24:51.480 ⇒ 00:24:55.470 Emily Giant: No matter what the week is that it’s sold.

237 00:24:58.000 ⇒ 00:25:03.770 Emily Giant: Because this is, like, a current active view of what is at the inventory.

238 00:25:03.900 ⇒ 00:25:06.419 Emily Giant: Or, in inventory at the location.

239 00:25:15.560 ⇒ 00:25:18.589 Emily Giant: Quantity sold is going to be the same, because

240 00:25:18.800 ⇒ 00:25:21.580 Emily Giant: It’s just an aggregate across the same thing.

241 00:25:26.050 ⇒ 00:25:27.649 Emily Giant: These will be the same.

242 00:25:28.320 ⇒ 00:25:33.819 Emily Giant: But, I don’t know what happens, like, when you… have this…

243 00:25:34.380 ⇒ 00:25:37.120 Emily Giant: Like, lines that are broken up by date.

244 00:25:38.600 ⇒ 00:25:43.239 Emily Giant: I don’t imagine that it thumbs correctly, because

245 00:25:43.870 ⇒ 00:25:55.450 Emily Giant: we really only have 10, but if I do a large band of time, it’s gonna sum these, or it will be 30 instead of 10, is my concern.

246 00:25:55.960 ⇒ 00:25:58.169 Demilade Agboola: Oh, okay, I get what you mean.

247 00:25:58.450 ⇒ 00:26:05.350 Demilade Agboola: But then… Are each of these rows supposed to, like, what is the… what…

248 00:26:06.140 ⇒ 00:26:12.489 Demilade Agboola: differentiates all these three class phase rows? Is it the… the week they were updated at?

249 00:26:12.890 ⇒ 00:26:13.640 Emily Giant: Yes.

250 00:26:19.450 ⇒ 00:26:20.450 Demilade Agboola: Gotcha.

251 00:26:23.640 ⇒ 00:26:28.870 Demilade Agboola: So instead of taking a snapshot, though, don’t we just need to filter out?

252 00:26:31.570 ⇒ 00:26:33.209 Demilade Agboola: Okay, now, I’m trying to think.

253 00:26:39.960 ⇒ 00:26:46.930 Demilade Agboola: Because I think what I’m trying to say, or what I’m trying to understand is this. So when we’re trying to look at it for…

254 00:26:49.820 ⇒ 00:26:52.309 Demilade Agboola: For, say, like, 2 weeks ago.

255 00:26:53.950 ⇒ 00:26:58.250 Demilade Agboola: We do want to see the quantity sold, right? Like, the appropriate quantity sold.

256 00:26:59.260 ⇒ 00:27:02.609 Emily Giant: I was gonna say, this actually won’t be 14, it will be different.

257 00:27:02.850 ⇒ 00:27:06.729 Emily Giant: The on-hand will be the same, but the quantity sold that week…

258 00:27:07.790 ⇒ 00:27:11.219 Emily Giant: will be different. So I’m gonna say this is….

259 00:27:26.420 ⇒ 00:27:28.559 Demilade Agboola: So the issue will just be….

260 00:27:33.920 ⇒ 00:27:35.859 Emily Giant: Will its sum be on hand?

261 00:27:39.060 ⇒ 00:27:41.100 Demilade Agboola: Yeah, I think… Heck.

262 00:27:41.490 ⇒ 00:27:51.440 Demilade Agboola: So, instead of summing the on-hand, why don’t we just pick the value… Because we’re….

263 00:27:51.440 ⇒ 00:27:53.530 Emily Giant: We could do a window function, right? Like….

264 00:27:53.570 ⇒ 00:27:55.440 Demilade Agboola: Do the most recent always?

265 00:27:55.820 ⇒ 00:27:57.480 Demilade Agboola: Yeah, that’s what I’m thinking.

266 00:27:59.780 ⇒ 00:28:04.190 Demilade Agboola: Because I’m thinking, do we need to, like, does the snapshot really solve the problem?

267 00:28:05.200 ⇒ 00:28:06.440 Emily Giant: Not really.

268 00:28:06.800 ⇒ 00:28:12.250 Demilade Agboola: Because if the problem is… Over a period of time, or over a larger window.

269 00:28:12.850 ⇒ 00:28:22.759 Demilade Agboola: we don’t know what the on-hand was over that period. It appears to just be the last version of it, right? Or the most recent update of that.

270 00:28:23.960 ⇒ 00:28:24.720 Emily Giant: Yep.

271 00:28:27.550 ⇒ 00:28:32.340 Emily Giant: Now, we still want that information, but you’re right in that I don’t think we need it for this

272 00:28:32.710 ⇒ 00:28:34.500 Emily Giant: Question that we’re answering.

273 00:28:34.740 ⇒ 00:28:43.399 Demilade Agboola: Yeah, yeah, that’s fair. We could, I mean, definitely we could still build it, but I’m just curious, like, which is kind of why I said let’s visualize it. If this is the question we’re trying to solve.

274 00:28:44.310 ⇒ 00:28:49.910 Demilade Agboola: Then we could just use the most recent update at… to…

275 00:28:50.350 ⇒ 00:28:54.090 Demilade Agboola: Get the quantity enhanced so we don’t sum it.

276 00:28:54.720 ⇒ 00:28:56.679 Demilade Agboola: And then for quantities, what we can sell.

277 00:28:56.680 ⇒ 00:28:57.749 Emily Giant: That makes sense.

278 00:28:58.040 ⇒ 00:29:01.330 Emily Giant: So that would be for, like, any of these.

279 00:29:02.350 ⇒ 00:29:09.820 Emily Giant: … There’s a… there’s a model just for… the, …

280 00:29:10.680 ⇒ 00:29:16.289 Emily Giant: Available for sale, on hand, on hand committed. These are the ones that need to be a window function.

281 00:29:17.220 ⇒ 00:29:19.769 Emily Giant: And then the others can be the… okay.

282 00:29:20.010 ⇒ 00:29:26.849 Emily Giant: That makes sense to me. I’m glad we talked this out. I was just having trouble, like, visualizing how this would work in my head.

283 00:29:47.240 ⇒ 00:29:48.640 Emily Giant: Cool. Alright.

284 00:29:48.890 ⇒ 00:29:56.370 Emily Giant: So the next question is snapshots. … So…

285 00:29:59.500 ⇒ 00:30:04.119 Emily Giant: Where is this configured? How did you do this? I do not understand.

286 00:30:04.890 ⇒ 00:30:06.289 Emily Giant: Where this came from.

287 00:30:07.340 ⇒ 00:30:15.790 Demilade Agboola: So, for this… this is taking a snapshot of the inventory lot table.

288 00:30:16.450 ⇒ 00:30:17.370 Emily Giant: ….

289 00:30:17.450 ⇒ 00:30:23.140 Demilade Agboola: It ain’t take… look at the entire, … Like, the select all.

290 00:30:23.330 ⇒ 00:30:28.030 Demilade Agboola: This means look at the entire table, but you can also select particular columns that you’re interested in.

291 00:30:29.040 ⇒ 00:30:33.290 Demilade Agboola: What this does is you’re seeing… Hey.

292 00:30:33.460 ⇒ 00:30:39.450 Demilade Agboola: check each… the unique ID is the inventory number ID, and check every column.

293 00:30:39.570 ⇒ 00:30:40.420 Demilade Agboola: Right?

294 00:30:41.450 ⇒ 00:30:45.620 Demilade Agboola: When a value within the rule.

295 00:30:46.260 ⇒ 00:30:51.270 Demilade Agboola: of the inventory number ID changes, take a snapshot, let us know that new value.

296 00:30:51.530 ⇒ 00:31:00.470 Demilade Agboola: And then if the value is deleted as well, like, if all of a sudden inventory number ID of that name just vanishes, that’s the invalidate had delete as true.

297 00:31:00.590 ⇒ 00:31:04.089 Demilade Agboola: It would just go, like, okay, this value doesn’t exist anymore.

298 00:31:04.240 ⇒ 00:31:09.360 Demilade Agboola: So it was valid to only this point. So this just allows us to keep track of what’s going on.

299 00:31:09.570 ⇒ 00:31:14.290 Demilade Agboola: Saying, hey, I want this to appear in…

300 00:31:14.710 ⇒ 00:31:19.939 Demilade Agboola: the database, analytics under schema snapshots.

301 00:31:20.290 ⇒ 00:31:23.349 Demilade Agboola: And it would appear as the name of the…

302 00:31:23.700 ⇒ 00:31:30.690 Demilade Agboola: the snapshot will be the first line, SMP, blah blah blah. So that’s what determines the name of a snapshot, by the way.

303 00:31:31.100 ⇒ 00:31:31.850 Demilade Agboola: Yeah.

304 00:31:32.250 ⇒ 00:31:39.830 Emily Giant: So, is there any additional configuration in, like, a YAML file, or do you just write this and press save and it does it?

305 00:31:40.560 ⇒ 00:31:45.759 Demilade Agboola: Write it, press save, and then, push it.

306 00:31:46.040 ⇒ 00:31:46.540 Demilade Agboola: Thank you very much.

307 00:31:46.540 ⇒ 00:31:47.310 Emily Giant: Okay.

308 00:31:47.910 ⇒ 00:31:55.389 Emily Giant: So, next question. Now that we’re adding hard goods to the lot table, it’s gonna have to be inventory number ID, location.

309 00:31:56.290 ⇒ 00:31:57.970 Emily Giant: And, ….

310 00:31:58.840 ⇒ 00:32:00.170 Demilade Agboola: item ID.

311 00:32:00.550 ⇒ 00:32:07.070 Emily Giant: And I also have, like, a surrogate key in both this table and the inventory adjustment mart.

312 00:32:07.640 ⇒ 00:32:11.570 Emily Giant: Which would probably be a better proxy for changes.

313 00:32:11.670 ⇒ 00:32:12.710 Emily Giant: ….

314 00:32:13.510 ⇒ 00:32:15.509 Demilade Agboola: Yeah, because she’s sort of got cancer.

315 00:32:16.160 ⇒ 00:32:21.080 Emily Giant: So, I tried, and it’s like, no, you can’t change this!

316 00:32:21.900 ⇒ 00:32:25.739 Emily Giant: Yeah, let me show you the other one. It, like, hates me.

317 00:32:25.880 ⇒ 00:32:26.910 Emily Giant: …

318 00:32:30.120 ⇒ 00:32:31.940 Emily Giant: Oh, I try.

319 00:32:36.100 ⇒ 00:32:38.850 Emily Giant: And I can’t… I can’t run the snap.

320 00:32:57.160 ⇒ 00:32:59.500 Emily Giant: It’s gonna tell me, Sergei, he doesn’t exist.

321 00:33:02.180 ⇒ 00:33:08.089 Demilade Agboola: Can you check your local… like, dbt…

322 00:33:08.560 ⇒ 00:33:14.949 Demilade Agboola: on the Scotia, and if, like, what the latest output of Martin, the Scott Double and Scott Inventure Science looks like.

323 00:33:17.520 ⇒ 00:33:18.420 Emily Giant: Akir?

324 00:33:18.950 ⇒ 00:33:19.780 Demilade Agboola: Yeah, yeah, yeah.

325 00:33:21.450 ⇒ 00:33:23.440 Demilade Agboola: So is that a surrogate key?

326 00:33:24.180 ⇒ 00:33:24.950 Demilade Agboola: column.

327 00:33:31.510 ⇒ 00:33:33.329 Emily Giant: What’s it called? SNP….

328 00:33:34.510 ⇒ 00:33:36.879 Demilade Agboola: No, no, no, just not the… not the snapshot.

329 00:33:36.880 ⇒ 00:33:40.969 Emily Giant: Oh, oh, oh, oh, got you, got you, okay. Just the MART data, yeah.

330 00:33:40.970 ⇒ 00:33:41.550 Demilade Agboola: Yeah.

331 00:33:50.770 ⇒ 00:33:54.369 Emily Giant: Oh, you know what? I can just look right here. It’s already pulled up.

332 00:34:05.040 ⇒ 00:34:17.289 Emily Giant: Oh, this is… while we’re here, this is what I’m saying. This is not an unlotted item, it’s the firecracker. But because it doesn’t have a commitment, it’s… the system is like, oh, this isn’t allotted good, but that’s…

333 00:34:17.400 ⇒ 00:34:18.979 Emily Giant: A problem for another day.

334 00:34:19.469 ⇒ 00:34:21.950 Emily Giant: Surrogate key, right there.

335 00:34:23.199 ⇒ 00:34:26.299 Demilade Agboola: Okay, so it does have a certain key, so can we go back, please?

336 00:34:26.619 ⇒ 00:34:27.909 Demilade Agboola: to dbt.

337 00:34:29.019 ⇒ 00:34:32.109 Demilade Agboola: So what does the error say? Just one more time.

338 00:34:34.569 ⇒ 00:34:36.489 Demilade Agboola: It goes…

339 00:34:41.229 ⇒ 00:34:42.059 Demilade Agboola: Sorry, excuse me.

340 00:34:43.290 ⇒ 00:34:46.919 Emily Giant: Surrogate key does not exist in SnapMart inventory adjustments.

341 00:34:47.070 ⇒ 00:34:48.970 Demilade Agboola: I can’t go back to the column.

342 00:34:49.170 ⇒ 00:34:49.980 Demilade Agboola: The….

343 00:34:51.030 ⇒ 00:34:51.750 Emily Giant: This?

344 00:34:53.710 ⇒ 00:34:56.860 Demilade Agboola: No, no, … DBC.

345 00:35:00.820 ⇒ 00:35:08.080 Demilade Agboola: Oh… Try… so when you want to build, let’s, like, click… Buh.

346 00:35:09.770 ⇒ 00:35:13.250 Demilade Agboola: So my guess is you might need… my guess is you might need to refresh it.

347 00:35:13.800 ⇒ 00:35:15.179 Demilade Agboola: So, of course, you’re changing.

348 00:35:15.180 ⇒ 00:35:16.250 Emily Giant: Right?

349 00:35:16.920 ⇒ 00:35:20.300 Emily Giant: So, it’s dbt Snapshot full refresh.

350 00:35:21.540 ⇒ 00:35:23.689 Demilade Agboola: Yeah, over my guess.

351 00:35:24.210 ⇒ 00:35:27.660 Emily Giant: Do I have to select it, or do I just do, like, snapshot full refresh?

352 00:35:28.780 ⇒ 00:35:34.479 Demilade Agboola: It’s always best to select so that you don’t refresh all the things that you don’t… you’re not trying to.

353 00:35:45.180 ⇒ 00:35:48.039 Emily Giant: Hello! Oh, I need to tell the team that I’m not…

354 00:35:48.490 ⇒ 00:35:52.669 Emily Giant: coming to our stand-up today. As soon as I saw your Tom’s face, I was like, oh, I’ve gotta….

355 00:35:52.670 ⇒ 00:35:54.920 Uttam Kumaran: I think that’s Hi!

356 00:36:02.470 ⇒ 00:36:06.680 Emily Giant: this was at, like, 4 in the morning, I was trying to do this, and then I was like, fuck it.

357 00:36:06.970 ⇒ 00:36:08.640 Emily Giant: Let’s just wait.

358 00:36:09.020 ⇒ 00:36:18.180 Emily Giant: Yeah, it’s real sticky with the snapshots, and I don’t know why. I even tried building a new one, and it was like, no! You already have one for this model.

359 00:36:18.560 ⇒ 00:36:21.899 Demilade Agboola: Yeah, but you have to change the name, if you want to build a new one.

360 00:36:22.920 ⇒ 00:36:26.749 Demilade Agboola: Like, you would have to… you can have multiple snapshots in…

361 00:36:27.060 ⇒ 00:36:29.279 Demilade Agboola: The names have to be different, though.

362 00:36:30.340 ⇒ 00:36:31.319 Demilade Agboola: So… Okay.

363 00:36:32.810 ⇒ 00:36:36.799 Emily Giant: So I could just copy this, and literally, like, make a new snapshot file.

364 00:36:37.170 ⇒ 00:36:42.510 Demilade Agboola: Yeah, but you would have to change the… so remember, like, like I said, line 1, defines them.

365 00:36:42.710 ⇒ 00:36:46.170 Demilade Agboola: rampshot. So you would have to ensure that you change, like, one.

366 00:36:47.070 ⇒ 00:36:50.139 Emily Giant: Okay, let me try that real quick, and then…

367 00:36:50.420 ⇒ 00:36:53.199 Emily Giant: I will let you go so that Utam and I can…

368 00:36:53.930 ⇒ 00:36:56.509 Emily Giant: Or, I mean, you can stick around, you’re always invited.

369 00:37:00.430 ⇒ 00:37:04.939 Emily Giant: And do I need to end it with SQL, or, like, I… is there any special… yeah.

370 00:37:05.330 ⇒ 00:37:05.800 Demilade Agboola: Korea has to….

371 00:37:05.800 ⇒ 00:37:07.380 Emily Giant: call this snap.

372 00:37:10.240 ⇒ 00:37:13.460 Emily Giant: I’m just gonna flip the name a little. Inventory Adjustment.

373 00:37:13.850 ⇒ 00:37:14.730 Emily Giant: marked.

374 00:37:14.840 ⇒ 00:37:16.540 Emily Giant: dot…

375 00:37:57.630 ⇒ 00:37:59.029 Emily Giant: Okay, cool.

376 00:37:59.910 ⇒ 00:38:08.299 Emily Giant: So, now that that’s up and running, can we just touch base tomorrow on how to add it to Looker in a way that I can, like, teach people to use it?

377 00:38:08.940 ⇒ 00:38:10.030 Demilade Agboola: Sounds good.

378 00:38:10.780 ⇒ 00:38:11.710 Emily Giant: Wait….

379 00:38:12.000 ⇒ 00:38:15.849 Demilade Agboola: Alright, I also sent the PR in, so if you take a look at that, that would be helpful.

380 00:38:16.520 ⇒ 00:38:18.199 Emily Giant: Okay, I will do that.

381 00:38:19.070 ⇒ 00:38:23.230 Emily Giant: Thank you. Thank you so much. I’ll see you tomorrow… well, I’ll see you at some point today.

382 00:38:23.230 ⇒ 00:38:25.260 Uttam Kumaran: Thank you, dude.

383 00:38:25.380 ⇒ 00:38:26.580 Emily Giant: Bye.

384 00:38:27.140 ⇒ 00:38:27.720 Demilade Agboola: Alright.

385 00:38:27.720 ⇒ 00:38:30.090 Emily Giant: Alright. Bye.

386 00:38:31.830 ⇒ 00:38:34.059 Uttam Kumaran: Okay, so the big thing is I’ve just been…

387 00:38:34.510 ⇒ 00:38:37.709 Uttam Kumaran: Taking hacks at cleaning a bunch of stuff up.

388 00:38:38.370 ⇒ 00:38:38.700 Emily Giant: So….

389 00:38:38.700 ⇒ 00:38:43.150 Uttam Kumaran: larger swings, trying to listen to Zach. And yeah, I think….

390 00:38:43.150 ⇒ 00:38:43.750 Emily Giant: Yeah.

391 00:38:43.750 ⇒ 00:38:52.709 Uttam Kumaran: You could probably just, like, tell me what is… No longer being, … Yes. …used, and I could….

392 00:38:52.710 ⇒ 00:38:53.200 Emily Giant: Let’s….

393 00:38:53.200 ⇒ 00:38:55.409 Uttam Kumaran: Well, you just hack all that out, so….

394 00:38:55.410 ⇒ 00:38:56.520 Emily Giant: Love it.

395 00:38:56.730 ⇒ 00:38:57.240 Emily Giant: Oh.

396 00:38:57.240 ⇒ 00:39:00.369 Uttam Kumaran: What’s, what’s easiest? Should I share, or…?

397 00:39:01.230 ⇒ 00:39:04.250 Uttam Kumaran: Like, you… or you can finish this up too, whichever.

398 00:39:04.830 ⇒ 00:39:06.539 Emily Giant: I just have to commit this, because…

399 00:39:06.900 ⇒ 00:39:16.229 Emily Giant: there’s… I’ve done a bad, bad thing with, like, the amount of work that’s in one branch is, like, absurd, and I’m so afraid of committing it, and I’m so afraid of losing.

400 00:39:16.230 ⇒ 00:39:24.700 Uttam Kumaran: Well, just put… if you push it, we can split it up, like, as long as it… you put a bow on it, I can help you split it up a little bit.

401 00:39:25.830 ⇒ 00:39:29.929 Emily Giant: Are you sure? It’s… I’ll walk you through it if we have any time, but it’s like…

402 00:39:30.490 ⇒ 00:39:31.150 Emily Giant: like, a whole.

403 00:39:31.150 ⇒ 00:39:33.869 Uttam Kumaran: Well, what, what, what other option… what’s, what’s your….

404 00:39:33.870 ⇒ 00:39:39.969 Emily Giant: I know, I know, there’s no, there’s no other… quitting. Quitting. Just, like, going and finding work elsewhere. That’s my.

405 00:39:39.970 ⇒ 00:39:42.260 Uttam Kumaran: But we should, we should also talk about…

406 00:39:42.860 ⇒ 00:39:46.169 Uttam Kumaran: splitting up the PR a little bit in the future. I know.

407 00:39:46.170 ⇒ 00:40:02.340 Emily Giant: Like, it… yes, I know that this is, like, my biggest problem, and I even, like, had to come to Jesus with Zach and Alex about that. I was like, listen, I’m doing this one more time this way, and I realize what I’ve done. Like, you don’t need to tell me, I know, but I… I have to push it. Like.

408 00:40:02.760 ⇒ 00:40:07.020 Emily Giant: It’s huge because it doesn’t touch production that much.

409 00:40:07.330 ⇒ 00:40:10.649 Emily Giant: So, like, in that way, like, I kept…

410 00:40:11.180 ⇒ 00:40:24.269 Emily Giant: snowballing what was there, because, like, if you moved one piece of historical inventory, it smacks all the way down to Tableau Items XF. Like, there is no not changing everything.

411 00:40:24.850 ⇒ 00:40:25.880 Emily Giant: But…

412 00:40:26.040 ⇒ 00:40:37.590 Emily Giant: I should have done what I did halfway through this PR, like, I should have made new models so that it didn’t touch production at all, so that, like, we could do it in chunks. Instead, I built an entire new, like.

413 00:40:37.870 ⇒ 00:40:38.850 Emily Giant: thing.

414 00:40:39.740 ⇒ 00:40:40.660 Uttam Kumaran: Yeah.

415 00:40:40.660 ⇒ 00:40:53.599 Emily Giant: Big swing. It’s so much easier to read, it’s so, so, so much cleaner and, like, more accurate. However, there’s probably, like, 90 separate commits. Anyway, okay, so…

416 00:40:54.060 ⇒ 00:40:55.370 Emily Giant: Let’s…

417 00:40:56.740 ⇒ 00:41:02.490 Emily Giant: Let’s actually stay in this branch, because this will, like, to a degree, be what it looks like by the end of the week.

418 00:41:02.690 ⇒ 00:41:05.939 Emily Giant: a lot cleaner. Most of the stuff is, like.

419 00:41:06.090 ⇒ 00:41:09.420 Emily Giant: in the new mart folder at this point, like, I’ve…

420 00:41:09.530 ⇒ 00:41:15.420 Emily Giant: Made a lot of progress migrating, a lot of the, like, …

421 00:41:15.960 ⇒ 00:41:30.570 Emily Giant: what’s it called? The old Pandera Paradigm folder, which is the biggest one that exists, into new models in the new model folder. But, so you want to know, like, what does not need to be refreshed? Ever?

422 00:41:30.570 ⇒ 00:41:31.990 Uttam Kumaran: Yes. Yes. Okay.

423 00:41:31.990 ⇒ 00:41:38.810 Emily Giant: So sweet. So… I think a good place to start would be… inventory adjustments.

424 00:41:39.520 ⇒ 00:41:40.829 Emily Giant: the old one.

425 00:41:42.050 ⇒ 00:41:47.800 Emily Giant: And my other thing on the agenda that I didn’t get to with Demolade was, like, what do I do with the models?

426 00:41:48.050 ⇒ 00:41:57.409 Emily Giant: that shouldn’t run anymore. Like, once I’ve replaced them, like, what do I do with them? Because I’m afraid of deleting them, that seems wrong. Like, we might.

427 00:41:57.410 ⇒ 00:42:04.340 Uttam Kumaran: Yeah, we can shove it into Archived. We can shove… we can create an archived folder and put it there, but yeah, I can show… show you how to do that.

428 00:42:05.130 ⇒ 00:42:12.560 Emily Giant: And we can even do that, like, I can start doing that maybe in a different branch, but no.

429 00:42:12.780 ⇒ 00:42:14.290 Emily Giant: So, okay.

430 00:42:14.740 ⇒ 00:42:17.020 Emily Giant: Deletions, we still use.

431 00:42:17.610 ⇒ 00:42:20.220 Emily Giant: That’s all this week.

432 00:42:22.560 ⇒ 00:42:24.070 Emily Giant: This, okay.

433 00:42:24.290 ⇒ 00:42:34.390 Emily Giant: So, starting with inventory adjustments, this is, like, a deprecated… this is, like, what I’ve redone, is this old style that we used to look at inventory adjustments.

434 00:42:34.540 ⇒ 00:42:38.559 Emily Giant: So this entire flow Where does it start?

435 00:42:43.300 ⇒ 00:42:47.650 Emily Giant: Do you want me to, like, pull up, a note and, like, just write these down?

436 00:42:47.650 ⇒ 00:42:49.810 Uttam Kumaran: I am writing that down on my side.

437 00:42:50.160 ⇒ 00:42:55.810 Emily Giant: Okay, so OMS staging orders, that’s gonna go away soon, but not yet.

438 00:42:55.930 ⇒ 00:42:58.610 Emily Giant: This can be done.

439 00:42:58.830 ⇒ 00:43:00.180 Emily Giant: in Salesforce.

440 00:43:00.430 ⇒ 00:43:04.570 Emily Giant: Not today, but, like, you can stop refreshing it. It’s okay.

441 00:43:08.190 ⇒ 00:43:08.750 Uttam Kumaran: Okay.

442 00:43:10.170 ⇒ 00:43:16.850 Emily Giant: So that flows to Shopify. These are both gonna be done as soon as I push that PR. They were, like.

443 00:43:17.030 ⇒ 00:43:22.610 Emily Giant: Temporary historical alignment of models that we’re not going to use anymore.

444 00:43:22.950 ⇒ 00:43:23.550 Uttam Kumaran: Okay.

445 00:43:24.410 ⇒ 00:43:26.380 Emily Giant: Inventory adjustments, done.

446 00:43:27.080 ⇒ 00:43:28.749 Emily Giant: Doesn’t need to refresh anymore.

447 00:43:32.110 ⇒ 00:43:32.690 Uttam Kumaran: Okay.

448 00:43:34.180 ⇒ 00:43:40.909 Emily Giant: Inventory transactions component speeder, at the end of today, done. That one’s gonna be replaced in this PR.

449 00:43:43.110 ⇒ 00:43:43.660 Uttam Kumaran: Okay.

450 00:43:48.730 ⇒ 00:43:49.570 Uttam Kumaran: Okay.

451 00:43:49.570 ⇒ 00:43:52.040 Emily Giant: Inventory Transactions XF.

452 00:43:54.090 ⇒ 00:43:54.900 Uttam Kumaran: Okay.

453 00:43:55.920 ⇒ 00:43:57.890 Emily Giant: Let me go, like, plus 5.

454 00:44:05.590 ⇒ 00:44:08.260 Emily Giant: Inventory transactions historical, done.

455 00:44:12.680 ⇒ 00:44:13.280 Uttam Kumaran: Okay.

456 00:44:15.290 ⇒ 00:44:17.439 Emily Giant: NetSuite cash failures, done.

457 00:44:18.120 ⇒ 00:44:18.730 Uttam Kumaran: Okay.

458 00:44:23.240 ⇒ 00:44:26.050 Emily Giant: Inventory adjustments XF, done.

459 00:44:26.530 ⇒ 00:44:27.190 Uttam Kumaran: Okay.

460 00:44:28.720 ⇒ 00:44:30.319 Emily Giant: Inventory XF snapshot.

461 00:44:32.240 ⇒ 00:44:32.900 Uttam Kumaran: Okay.

462 00:44:32.900 ⇒ 00:44:37.470 Emily Giant: Done. Inventory X transactions XF snap, done.

463 00:44:38.800 ⇒ 00:44:45.210 Emily Giant: Inventory snapshot, don’t even know what that is. What is this? I’m guessing it’s done, because everything leading to it is done.

464 00:44:45.470 ⇒ 00:44:46.710 Emily Giant: Yeah, done.

465 00:44:46.880 ⇒ 00:44:47.840 Emily Giant: …

466 00:44:54.340 ⇒ 00:44:55.770 Emily Giant: Get me out of here.

467 00:45:08.110 ⇒ 00:45:09.980 Emily Giant: That’s current.

468 00:45:11.130 ⇒ 00:45:13.960 Emily Giant: Wait, Inventory Adjustments Union.

469 00:45:14.770 ⇒ 00:45:17.959 Emily Giant: Let me check this out, because I’m thinking, like, done.

470 00:45:18.470 ⇒ 00:45:19.780 Emily Giant: This looks old.

471 00:45:31.890 ⇒ 00:45:35.449 Emily Giant: Done. This one. Inventory Adjustments Union.

472 00:45:53.830 ⇒ 00:45:59.530 Emily Giant: Okay, so that’s, like, a big chunk there that… Doesn’t need to run.

473 00:46:00.690 ⇒ 00:46:06.269 Emily Giant: … Let’s go over to…

474 00:46:14.050 ⇒ 00:46:15.320 Emily Giant: subscriptions.

475 00:46:18.920 ⇒ 00:46:20.880 Emily Giant: Oh my god, what is all that?

476 00:46:21.270 ⇒ 00:46:22.110 Emily Giant: Alright.

477 00:46:22.230 ⇒ 00:46:24.650 Emily Giant: Delivery area, distribution point.

478 00:46:27.070 ⇒ 00:46:29.229 Emily Giant: Inventory deliveries? Done.

479 00:46:30.450 ⇒ 00:46:31.140 Uttam Kumaran: Okay.

480 00:46:40.060 ⇒ 00:46:43.580 Emily Giant: Some of these I put, like… I think this one’s done, but let me check.

481 00:46:43.840 ⇒ 00:46:48.370 Emily Giant: … Almost positive. Let me just check the max date on this.

482 00:46:48.760 ⇒ 00:46:49.650 Emily Giant: …

483 00:47:08.890 ⇒ 00:47:11.630 Emily Giant: Oh my god, is this Postgres? Hold on.

484 00:47:12.580 ⇒ 00:47:13.780 Emily Giant: Done.

485 00:47:13.920 ⇒ 00:47:14.530 Emily Giant: Done.

486 00:47:14.530 ⇒ 00:47:15.090 Uttam Kumaran: Okay.

487 00:47:15.840 ⇒ 00:47:16.720 Emily Giant: …

488 00:47:22.280 ⇒ 00:47:25.820 Emily Giant: I’m guessing this is… Done.

489 00:47:26.520 ⇒ 00:47:28.739 Emily Giant: The product category relationships.

490 00:47:29.570 ⇒ 00:47:35.340 Uttam Kumaran: So for these, like, you’re… all you’re seeing… They haven’t connected to anything. Yeah, you’re seeing just the ones that aren’t connected.

491 00:47:35.860 ⇒ 00:47:36.780 Emily Giant: Okay, so this….

492 00:47:36.780 ⇒ 00:47:39.700 Uttam Kumaran: That’s submit… okay, yeah, alright, great.

493 00:47:43.460 ⇒ 00:47:48.540 Uttam Kumaran: So, one thing that I can do is I can look through, like, the…

494 00:47:49.190 ⇒ 00:47:52.709 Uttam Kumaran: like, if you could just point out the folders, and basically I kind of want to say.

495 00:47:52.710 ⇒ 00:47:53.160 Emily Giant: Yeah, just in life.

496 00:47:53.160 ⇒ 00:47:56.570 Uttam Kumaran: like… If these aren’t connected to anything.

497 00:47:56.990 ⇒ 00:48:07.030 Uttam Kumaran: there’s kind of a couple of categories, right? There’s, like, non-connected, There’s also just, like, non-refreshing …

498 00:48:11.300 ⇒ 00:48:13.570 Uttam Kumaran: Yeah, I guess those are… those are both…

499 00:48:16.630 ⇒ 00:48:19.330 Uttam Kumaran: those are both the two categories. So, like, between.

500 00:48:19.330 ⇒ 00:48:19.680 Emily Giant: Yeah.

501 00:48:19.680 ⇒ 00:48:23.429 Uttam Kumaran: refreshing and non-connected, so Zendesk, all the Zendesk stuff is non-refreshing.

502 00:48:24.120 ⇒ 00:48:24.830 Emily Giant: Yes.

503 00:48:25.740 ⇒ 00:48:26.410 Uttam Kumaran: Okay.

504 00:48:27.680 ⇒ 00:48:29.489 Emily Giant: All of that.

505 00:48:30.290 ⇒ 00:48:48.000 Emily Giant: So this is gonna be, like, the bread and butter of, like, what I’m currently replacing, and what Demolade’s currently replacing. It’s this OMS folder, and the Pandera paradigm, and the Postgres, but not all of them are done. So it’s kind of like…

506 00:48:48.280 ⇒ 00:48:54.289 Emily Giant: hit and miss with, like, what’s getting replaced. Like, we already talked about this one, this is gonna be archived.

507 00:48:56.430 ⇒ 00:48:57.489 Uttam Kumaran: Do we do, like….

508 00:48:58.010 ⇒ 00:49:01.850 Emily Giant: put these in a folder, or something? Like, I feel like I’m just….

509 00:49:03.030 ⇒ 00:49:03.909 Uttam Kumaran: Whoa, no, we won’t.

510 00:49:03.910 ⇒ 00:49:05.520 Emily Giant: models, as long as you’re writing them down.

511 00:49:05.520 ⇒ 00:49:08.819 Uttam Kumaran: I’m writing them down, but we will move them to an archived folder.

512 00:49:08.820 ⇒ 00:49:09.540 Emily Giant: Okay.

513 00:49:09.780 ⇒ 00:49:10.450 Uttam Kumaran: Yeah.

514 00:49:11.780 ⇒ 00:49:15.709 Emily Giant: Alright, so these should be able to be replaced by, …

515 00:49:16.220 ⇒ 00:49:30.890 Emily Giant: I would start replacing this, the XF base, XF plant kits, and regular kits at end of week. So my new, deployment is gonna replace all these, but I just want, like, some proof of concept first. …

516 00:49:31.750 ⇒ 00:49:34.609 Emily Giant: Before we, like, archive, archive them.

517 00:49:35.050 ⇒ 00:49:37.129 Uttam Kumaran: Okay, so XL….

518 00:49:38.790 ⇒ 00:49:41.660 Emily Giant: Same with the… same with OMS line item components.

519 00:49:47.000 ⇒ 00:49:48.689 Uttam Kumaran: Okay. I don’t know what this is.

520 00:49:48.730 ⇒ 00:49:50.919 Emily Giant: On the flip order items component base.

521 00:49:51.540 ⇒ 00:50:00.789 Emily Giant: Yeah, so everything in this folder can be non-refreshing, once, like, internal testing is done, which hopefully will be, like.

522 00:50:01.120 ⇒ 00:50:02.310 Emily Giant: this week.

523 00:50:02.920 ⇒ 00:50:10.200 Emily Giant: they’re already written, they’re just not tested out in the wild on dashboards. … Line items.

524 00:50:17.030 ⇒ 00:50:19.440 Emily Giant: Okay, these all still have to stay alive.

525 00:50:26.620 ⇒ 00:50:28.750 Emily Giant: Oh my god, there’s so many different folders.

526 00:50:29.390 ⇒ 00:50:36.290 Emily Giant: This one, same bucket as those others, this is getting replaced with my… Next PR.

527 00:50:37.330 ⇒ 00:50:39.010 Emily Giant: Dim Light Item Union.

528 00:50:39.360 ⇒ 00:50:41.910 Emily Giant: So that, like, can be archived.

529 00:50:42.300 ⇒ 00:50:45.720 Emily Giant: Same with int Components Dataset Union.

530 00:50:48.270 ⇒ 00:50:51.449 Emily Giant: And it split line item strikethrough.

531 00:50:55.900 ⇒ 00:51:05.589 Emily Giant: I think this one has to stay the same. This one needs to be replaced, but, like, nothing is in the works to replace it yet, so I don’t think we can just yet.

532 00:51:05.910 ⇒ 00:51:07.280 Emily Giant: The outbound cost.

533 00:51:09.020 ⇒ 00:51:09.640 Uttam Kumaran: Okay.

534 00:51:10.490 ⇒ 00:51:12.890 Uttam Kumaran: It needs to get replaced just because….

535 00:51:13.750 ⇒ 00:51:17.239 Emily Giant: It’s static. Like, it’s pulling in…

536 00:51:17.620 ⇒ 00:51:29.519 Emily Giant: old costs of things based on, like, what somebody wrote in this file, so all of our outbound costing is based on, like, hard-coded junk. Which, it’s probably not part of the Brainforge sprint.

537 00:51:29.520 ⇒ 00:51:30.580 Uttam Kumaran: Sadly. Okay.

538 00:51:30.580 ⇒ 00:51:35.579 Emily Giant: But, … It’s not accurate.

539 00:51:38.510 ⇒ 00:51:44.510 Emily Giant: And with that… anything that says Legacy obviously doesn’t need to be refreshed.

540 00:51:50.220 ⇒ 00:51:50.940 Uttam Kumaran: Okay.

541 00:51:53.450 ⇒ 00:51:57.669 Emily Giant: These don’t need to be updated, products XF old, products XF.

542 00:51:59.330 ⇒ 00:52:06.859 Emily Giant: staging shop product tags, I have replaced that with a different, Shopify model, so those can all be archived.

543 00:52:24.270 ⇒ 00:52:25.100 Emily Giant: Okay.

544 00:52:26.530 ⇒ 00:52:31.739 Emily Giant: This… I’m trying to find what needs to be refreshed in here.

545 00:52:32.700 ⇒ 00:52:41.880 Emily Giant: This doesn’t, this doesn’t… anything with sticky, this does need to stay refreshed until we replace it with the loop data.

546 00:52:44.010 ⇒ 00:52:45.879 Emily Giant: So these three stay.

547 00:52:48.200 ⇒ 00:52:51.379 Emily Giant: DIM recurring subscriptions timeline? Nope.

548 00:52:53.040 ⇒ 00:52:54.989 Emily Giant: That does not need to refresh.

549 00:52:56.370 ⇒ 00:52:57.910 Emily Giant: But it stays.

550 00:53:00.150 ⇒ 00:53:05.360 Emily Giant: Subscription orders XF, Subscriptions XF, these are all, like, the same title.

551 00:53:09.550 ⇒ 00:53:20.030 Emily Giant: So from this, I would just say anything with sticky in it does not need to refresh, but it does… it can’t be archived yet until I do, like, the historical alignment, but they will be.

552 00:53:20.680 ⇒ 00:53:23.740 Emily Giant: And then legacy obviously doesn’t need to be refreshed.

553 00:53:25.340 ⇒ 00:53:25.930 Uttam Kumaran: Okay.

554 00:53:27.170 ⇒ 00:53:28.590 Emily Giant: These all stay.

555 00:53:32.710 ⇒ 00:53:38.229 Emily Giant: … These do not need to be refreshed. Staging legacy.

556 00:53:39.850 ⇒ 00:53:47.079 Emily Giant: These do for now, but, like, only once a day, maybe? Like… the staging GA4.

557 00:53:47.290 ⇒ 00:53:51.029 Emily Giant: Any of that GA4, like, once a day is fine for now.

558 00:53:51.490 ⇒ 00:53:52.140 Uttam Kumaran: Okay.

559 00:53:56.480 ⇒ 00:53:57.130 Emily Giant: Okay.

560 00:53:57.650 ⇒ 00:54:04.829 Emily Giant: So… Until… this is the same bucket that’s getting replaced with my upcoming PR.

561 00:54:05.000 ⇒ 00:54:13.359 Emily Giant: This is gonna archive. This is gonna get archived. This is gonna get archived. This is not… yet.

562 00:54:16.470 ⇒ 00:54:18.319 Emily Giant: This is gonna get archived.

563 00:54:19.330 ⇒ 00:54:21.340 Emily Giant: This is gonna get archived.

564 00:54:22.410 ⇒ 00:54:24.829 Emily Giant: Not yet, not yet, not yet.

565 00:54:29.250 ⇒ 00:54:30.010 Uttam Kumaran: Okay.

566 00:54:39.820 ⇒ 00:54:41.809 Emily Giant: All of these can be archived.

567 00:54:46.520 ⇒ 00:54:48.909 Uttam Kumaran: And they’re just not connected right now.

568 00:54:49.600 ⇒ 00:54:50.280 Emily Giant: Right.

569 00:54:52.630 ⇒ 00:54:54.820 Uttam Kumaran: What’s the sub… okay, yeah.

570 00:54:56.000 ⇒ 00:54:59.150 Uttam Kumaran: Like, we’ve already replaced these with new models.

571 00:55:00.230 ⇒ 00:55:02.569 Emily Giant: In the new item folder.

572 00:55:03.180 ⇒ 00:55:03.790 Uttam Kumaran: Okay.

573 00:55:05.130 ⇒ 00:55:07.569 Emily Giant: And yet another subscription folder.

574 00:55:10.860 ⇒ 00:55:12.140 Emily Giant: …

575 00:55:12.970 ⇒ 00:55:20.780 Emily Giant: Yeah, do you… I don’t know what any of these are. You can, archive. Well, not, not, archive, so they just don’t need to refresh.

576 00:55:20.960 ⇒ 00:55:25.869 Emily Giant: I gotta keep them around until I replace them. That’s, like, my current Sprint ticket.

577 00:55:30.540 ⇒ 00:55:39.309 Emily Giant: I don’t think we use anything from Postgres except for, like, Delivery area, maybe?

578 00:55:40.320 ⇒ 00:55:45.820 Emily Giant: and the product… or the customers, which you and I chatted about, and you already worked that into that model.

579 00:55:46.820 ⇒ 00:55:50.070 Emily Giant: But I don’t think we use anything else from Postgres at all.

580 00:55:50.660 ⇒ 00:55:53.729 Uttam Kumaran: Okay, so I can just check to see what’s connected there.

581 00:56:00.580 ⇒ 00:56:03.189 Emily Giant: Done, done.

582 00:56:03.870 ⇒ 00:56:06.219 Emily Giant: Done. We already talked about those.

583 00:56:08.790 ⇒ 00:56:15.340 Emily Giant: So everything but the inventory adjustment snap and inventory snapshot can get, like, Archived.

584 00:56:18.000 ⇒ 00:56:19.050 Emily Giant: Archives. Okay.

585 00:56:27.830 ⇒ 00:56:32.340 Emily Giant: Archives, archives, archives… Archive.

586 00:56:34.180 ⇒ 00:56:35.220 Emily Giant: Archive.

587 00:56:35.500 ⇒ 00:56:36.300 Emily Giant: Keep.

588 00:56:37.890 ⇒ 00:56:39.450 Emily Giant: Cause I just don’t know what that is.

589 00:56:40.240 ⇒ 00:56:40.780 Uttam Kumaran: Okay.

590 00:56:49.400 ⇒ 00:56:51.629 Emily Giant: Well, that’s empty, so….

591 00:56:51.630 ⇒ 00:56:52.740 Uttam Kumaran: Okay. It’s gone.

592 00:56:53.250 ⇒ 00:56:55.180 Emily Giant: Go ahead and delete that right now.

593 00:56:55.450 ⇒ 00:56:56.540 Emily Giant: …

594 00:57:03.540 ⇒ 00:57:04.490 Emily Giant: Keep it.

595 00:57:05.620 ⇒ 00:57:08.750 Emily Giant: Zendesk, we talked through that, anything in there.

596 00:57:08.960 ⇒ 00:57:12.409 Emily Giant: not archived, I’m… you just… they don’t refresh, but I need….

597 00:57:12.410 ⇒ 00:57:12.980 Uttam Kumaran: Yeah. Excuse that.

598 00:57:12.980 ⇒ 00:57:14.650 Emily Giant: for historical alignment.

599 00:57:14.810 ⇒ 00:57:19.349 Emily Giant: And then… Everything stays in the new model structure. That’s all good.

600 00:57:20.430 ⇒ 00:57:23.879 Emily Giant: … I mean, that’s…

601 00:57:24.030 ⇒ 00:57:30.310 Emily Giant: the lion’s share that I think that we went through. Like, QuickBooks doesn’t need to refresh, …

602 00:57:30.870 ⇒ 00:57:32.990 Emily Giant: I don’t think it does, but…

603 00:57:40.750 ⇒ 00:57:45.109 Emily Giant: These do. Keep those, keep them refreshing in the customer service folder.

604 00:57:53.930 ⇒ 00:57:56.830 Emily Giant: I think this one can just get deleted, but I’ll do that.

605 00:58:06.080 ⇒ 00:58:07.479 Emily Giant: That stays.

606 00:58:08.320 ⇒ 00:58:09.700 Emily Giant: Beast Day.

607 00:58:12.630 ⇒ 00:58:25.530 Emily Giant: I need to go through these, because Demolati did replace these order tables in the new schema, but didn’t plug them in to any of the existing models so that we can actually archive them. So, just keep those for now, but, like.

608 00:58:26.090 ⇒ 00:58:31.209 Emily Giant: This should be… In short order, ….

609 00:58:31.210 ⇒ 00:58:31.800 Uttam Kumaran: Okay.

610 00:58:38.040 ⇒ 00:58:42.080 Emily Giant: These are all just Google Sheets, so they’re not… a big deal.

611 00:58:47.790 ⇒ 00:58:52.389 Emily Giant: You keep… That’s all of it. Is that… did we go through everything?

612 00:58:55.250 ⇒ 00:58:55.840 Uttam Kumaran: Love you.

613 00:58:55.840 ⇒ 00:58:56.359 Emily Giant: I’ll just update.

614 00:59:09.970 ⇒ 00:59:15.130 Uttam Kumaran: So, what about, like, DIM GA orders? We need that?

615 00:59:16.520 ⇒ 00:59:17.670 Emily Giant: Yes.

616 00:59:18.270 ⇒ 00:59:19.020 Uttam Kumaran: Okay.

617 00:59:20.630 ⇒ 00:59:22.299 Uttam Kumaran: This is all gone, and….

618 00:59:27.840 ⇒ 00:59:29.939 Emily Giant: One sec, I gotta write a quick message.

619 00:59:38.790 ⇒ 00:59:42.209 Uttam Kumaran: And then anything that’s, like, a CSV dump.

620 00:59:42.380 ⇒ 00:59:47.059 Uttam Kumaran: Like, anything from S3CSV, I’m gonna consolidate.

621 00:59:48.950 ⇒ 00:59:50.640 Emily Giant: Okay, that sounds good.

622 00:59:52.300 ⇒ 00:59:53.100 Uttam Kumaran: May…

623 01:00:00.560 ⇒ 01:00:04.559 Uttam Kumaran: There is also this loan analysis folder.

624 01:00:07.790 ⇒ 01:00:08.610 Emily Giant: Huh?

625 01:00:10.130 ⇒ 01:00:11.769 Emily Giant: Oh, gosh.

626 01:00:11.770 ⇒ 01:00:14.310 Uttam Kumaran: IMS analysis site interactions?

627 01:00:16.420 ⇒ 01:00:18.210 Emily Giant: What is this plugged into?

628 01:00:18.830 ⇒ 01:00:20.340 Emily Giant: No plow?

629 01:00:23.050 ⇒ 01:00:25.999 Uttam Kumaran: Yeah, Snowplow is, is like, …

630 01:00:26.240 ⇒ 01:00:30.239 Uttam Kumaran: I mean, if nobody knows it, then it’s… it’s just a product analytics thing.

631 01:00:31.200 ⇒ 01:00:33.970 Emily Giant: This doesn’t… this doesn’t seem like a thing.

632 01:00:34.170 ⇒ 01:00:35.000 Uttam Kumaran: Okay.

633 01:00:44.680 ⇒ 01:00:45.510 Uttam Kumaran: Okay….

634 01:00:45.510 ⇒ 01:00:49.160 Emily Giant: Okay, chowder mill, this never needs to refresh.

635 01:00:54.170 ⇒ 01:00:55.879 Uttam Kumaran: Oh, where is it coming from, this one?

636 01:00:56.410 ⇒ 01:00:58.330 Uttam Kumaran: from, like, a Google shop.

637 01:00:58.330 ⇒ 01:01:00.109 Emily Giant: It’s a program that we don’t use anymore.

638 01:01:00.470 ⇒ 01:01:01.080 Uttam Kumaran: Oh, okay.

639 01:01:01.080 ⇒ 01:01:02.050 Emily Giant: Chattermelt? Yeah.

640 01:01:02.050 ⇒ 01:01:04.129 Uttam Kumaran: But what is the source for this?

641 01:01:06.740 ⇒ 01:01:12.960 Uttam Kumaran: Like, it’s coming from the… like, where is the chatter mill, the top query coming from?

642 01:01:12.960 ⇒ 01:01:13.540 Emily Giant: tick.

643 01:01:13.910 ⇒ 01:01:17.640 Emily Giant: I don’t know, it doesn’t have a… oh, yep, uploads.

644 01:01:17.640 ⇒ 01:01:19.160 Uttam Kumaran: Oh, okay, okay, great.

645 01:01:20.550 ⇒ 01:01:23.500 Emily Giant: So, that’s probably not doing anything much, but….

646 01:01:23.500 ⇒ 01:01:24.920 Uttam Kumaran: Is there any Google Sheets in that?

647 01:01:24.920 ⇒ 01:01:25.440 Emily Giant: 3 years.

648 01:01:25.440 ⇒ 01:01:27.229 Uttam Kumaran: Why is it in Google Sheets?

649 01:01:29.160 ⇒ 01:01:30.530 Uttam Kumaran: The Chatter Mill one.

650 01:01:32.670 ⇒ 01:01:35.550 Emily Giant: I think it is, like, the Google Sheet folder, you mean?

651 01:01:35.550 ⇒ 01:01:36.310 Uttam Kumaran: Yeah.

652 01:01:37.050 ⇒ 01:01:44.489 Emily Giant: I think it is a Google Sheet. I don’t… they upload it via… they’re probably dumping the input into a Google Sheet, but yeah, you can just archive that.

653 01:01:45.260 ⇒ 01:01:45.860 Uttam Kumaran: Okay.

654 01:01:48.780 ⇒ 01:01:53.580 Emily Giant: What else in Google Sheets? You said you already have a plan for the Google Sheets?

655 01:01:55.120 ⇒ 01:01:55.840 Uttam Kumaran: Yes.

656 01:01:56.270 ⇒ 01:01:56.950 Emily Giant: Okay.

657 01:02:06.180 ⇒ 01:02:09.520 Emily Giant: I don’t know, I think the Facebook ads we keep, but….

658 01:02:11.490 ⇒ 01:02:12.130 Uttam Kumaran: Okay.

659 01:02:15.560 ⇒ 01:02:24.499 Emily Giant: Are there any other… specific… Like, areas that you’re looking at.

660 01:02:39.150 ⇒ 01:02:49.270 Uttam Kumaran: Well, okay, so there is this tracking.js… within… The high-level folder.

661 01:02:51.120 ⇒ 01:02:52.360 Uttam Kumaran: Can I get rid of this?

662 01:02:58.370 ⇒ 01:02:59.140 Emily Giant: I mean….

663 01:02:59.140 ⇒ 01:03:00.510 Uttam Kumaran: I don’t know… I don’t know why.

664 01:03:00.510 ⇒ 01:03:01.360 Emily Giant: It looks slick.

665 01:03:01.360 ⇒ 01:03:02.239 Uttam Kumaran: tripped in here.

666 01:03:02.610 ⇒ 01:03:07.360 Emily Giant: Yeah, I don’t think this is… Anything.

667 01:03:09.740 ⇒ 01:03:11.299 Uttam Kumaran: Alright, that’s great.

668 01:03:12.050 ⇒ 01:03:20.750 Uttam Kumaran: … So, should I move all snapshots into… The snapshots folder.

669 01:03:21.120 ⇒ 01:03:22.710 Emily Giant: Yes, absolutely.

670 01:03:32.470 ⇒ 01:03:33.850 Uttam Kumaran: Great…

671 01:03:38.100 ⇒ 01:03:43.159 Uttam Kumaran: And then, yeah, I guess, tell me about, like, QuickBooks? Like, what…

672 01:03:43.610 ⇒ 01:03:46.679 Uttam Kumaran: Maybe I just haven’t, like, poked at it yet.

673 01:03:46.680 ⇒ 01:03:52.740 Emily Giant: Yeah, we’re not really using it, and the plan is to move all of that into NetSuite.

674 01:03:53.050 ⇒ 01:03:57.950 Emily Giant: So that will be additional, like, polyatomic data in the future. …

675 01:03:58.290 ⇒ 01:04:01.650 Emily Giant: So, has Zach shown you the, like.

676 01:04:01.890 ⇒ 01:04:09.460 Emily Giant: I mean, I think we both have our own versions of these, but, like, the kind of sweeping plan that we have for

677 01:04:09.990 ⇒ 01:04:13.640 Emily Giant: Like, when things happen in the engagement?

678 01:04:13.870 ⇒ 01:04:16.230 Emily Giant: Let me see if I have it somehow.

679 01:04:21.610 ⇒ 01:04:24.930 Emily Giant: And I put this together, so if somebody needs to change, but this is, like.

680 01:04:25.520 ⇒ 01:04:28.030 Emily Giant: Generally, what we’ve talked about, …

681 01:04:28.760 ⇒ 01:04:32.100 Emily Giant: day after day, and, like, how things are going. So, inventory data mart.

682 01:04:32.260 ⇒ 01:04:38.039 Emily Giant: Right now, we’re working on the SNOP revenue mark, and that is, like, August, September.

683 01:04:38.040 ⇒ 01:04:38.500 Uttam Kumaran: Yeah.

684 01:04:38.500 ⇒ 01:04:42.210 Emily Giant: That ends, like, second week of September.

685 01:04:42.440 ⇒ 01:04:44.239 Emily Giant: By that point, …

686 01:04:44.950 ⇒ 01:04:51.779 Emily Giant: we already have the loop work, so, like, these are actually happening in tandem, because I’m working on historical subscription info.

687 01:04:51.780 ⇒ 01:04:55.570 Uttam Kumaran: I’m gonna… yeah, I’m gonna be working on Loop this… this week, also.

688 01:04:55.570 ⇒ 01:05:18.049 Emily Giant: Great. So these are kind of happening together. This is the month of September, and then this is, like, the North Beam Historical Data Alignment, like, making sense of our marketing data in October. And then, I know we’re planning the end at, November 30th as the contract, but this, the finance mart, is, like, the entire last month of the engagement, which would be, like, where

689 01:05:18.180 ⇒ 01:05:23.080 Emily Giant: any, … Polyatomic building out what we need.

690 01:05:23.320 ⇒ 01:05:31.529 Emily Giant: … in the NetSuite data for finance, since we’re moving all of that into that area, but we’re…

691 01:05:32.100 ⇒ 01:05:35.759 Emily Giant: I don’t know how much historical alignment finance really needs.

692 01:05:36.080 ⇒ 01:05:36.760 Uttam Kumaran: Okay.

693 01:05:37.910 ⇒ 01:05:40.439 Emily Giant: Because they’ve done their own thing, and…

694 01:05:41.100 ⇒ 01:05:51.540 Emily Giant: I mean, maybe, like, in a separate thing, I can, like, take their random Google Sheets and make them into something, but this will mostly be just building out the new mart.

695 01:05:52.460 ⇒ 01:05:53.080 Uttam Kumaran: Okay.

696 01:06:06.520 ⇒ 01:06:07.270 Uttam Kumaran: Okay.

697 01:06:15.780 ⇒ 01:06:20.200 Emily Giant: Okay, and then, … in…

698 01:06:20.960 ⇒ 01:06:27.559 Emily Giant: in terms of, like, incremental strategy, I think there’s a ton of opportunity with, like.

699 01:06:27.900 ⇒ 01:06:30.500 Emily Giant: The new models in inventory.

700 01:06:31.040 ⇒ 01:06:39.770 Emily Giant: … like… Oh, where’s my… So, for example, like.

701 01:06:40.850 ⇒ 01:06:44.690 Emily Giant: Nothing in these two folders here, like…

702 01:06:45.130 ⇒ 01:06:48.400 Emily Giant: In the intermediate inventory, it’s incremental right now.

703 01:06:48.640 ⇒ 01:06:50.870 Emily Giant: Like, the staging models are.

704 01:06:51.240 ⇒ 01:06:52.190 Emily Giant: But…

705 01:06:52.930 ⇒ 01:06:59.679 Emily Giant: none of the in-betweeners are. So I can start working on that. Once I do the deployment, I can, like, immediately go back

706 01:06:59.960 ⇒ 01:07:03.030 Emily Giant: And turn those into incremental.

707 01:07:03.560 ⇒ 01:07:03.880 Uttam Kumaran: Okay.

708 01:07:03.880 ⇒ 01:07:24.720 Emily Giant: So that, like, I think that part of what’s making it take so long, and you could probably, like, not listen to me conjecture about this, because we have metaplane in testing mode, but it’s that we’re building models in addition to the ones in production, so we’ve, like, doubled our instance in the last

709 01:07:24.880 ⇒ 01:07:26.000 Emily Giant: Couple weeks.

710 01:07:26.770 ⇒ 01:07:27.360 Uttam Kumaran: It’s just like….

711 01:07:27.360 ⇒ 01:07:29.979 Emily Giant: Legitimately more to run.

712 01:07:29.980 ⇒ 01:07:44.869 Uttam Kumaran: Yeah, there’s more to run, that’s why things are tripping over themselves a little bit, but also, like, there are old stuff, like, there is a lot of old models, like Zendesk, like GA, like, some of these ones that are still taking a long time to run, and they’re…

713 01:07:45.210 ⇒ 01:07:49.180 Uttam Kumaran: Completely refreshing sale data, so… I want to.

714 01:07:49.180 ⇒ 01:07:49.630 Emily Giant: Great.

715 01:07:49.630 ⇒ 01:07:56.710 Uttam Kumaran: eliminate the old ones that aren’t connected. I want to move the non-refreshing ones to just…

716 01:07:57.060 ⇒ 01:08:00.480 Uttam Kumaran: Like, I’ll basically, again, just… …

717 01:08:01.900 ⇒ 01:08:05.050 Uttam Kumaran: I guess we can turn them all into views, technically?

718 01:08:05.980 ⇒ 01:08:11.810 Uttam Kumaran: I have to decide, and then everything that’s heavy at that point is gonna get turned into incremental.

719 01:08:12.250 ⇒ 01:08:25.610 Uttam Kumaran: And that should cut down a lot. Like, even… I… like, I’ve turned Tableau items XF incremental, I’ve turned several, tables incremental over the last few days that have, like, significantly improved the speed of

720 01:08:25.870 ⇒ 01:08:30.170 Uttam Kumaran: Full refresh and the daily job, the intraday job, so…

721 01:08:30.450 ⇒ 01:08:33.209 Uttam Kumaran: Just sort of systematically going through and doing that.

722 01:08:33.899 ⇒ 01:08:34.619 Emily Giant: Okay.

723 01:08:34.969 ⇒ 01:08:37.169 Emily Giant: Yeah, that sounds good.

724 01:08:38.179 ⇒ 01:08:46.179 Emily Giant: And I’ll keep working on, like, once I… if I’m building anything new, and I know it’s heavy, just, like, making the incremental refresh part of it.

725 01:08:46.770 ⇒ 01:08:47.399 Uttam Kumaran: Okay.

726 01:08:49.460 ⇒ 01:08:52.070 Emily Giant: Are there any other areas you wanted to go over?

727 01:08:52.850 ⇒ 01:08:54.439 Uttam Kumaran: I think that’s…

728 01:08:58.109 ⇒ 01:08:59.200 Uttam Kumaran: Fitz.

729 01:09:00.399 ⇒ 01:09:01.119 Emily Giant: Sweet.

730 01:09:01.960 ⇒ 01:09:07.489 Uttam Kumaran: And then I may just do a little bit of renaming, probably after your PR gets in.

731 01:09:07.649 ⇒ 01:09:08.309 Emily Giant: Yeah.

732 01:09:08.510 ⇒ 01:09:13.120 Uttam Kumaran: Because I wanna… I wanna rename and then do… set up tags for everything.

733 01:09:15.029 ⇒ 01:09:16.589 Emily Giant: Yeah, that would be awesome.

734 01:09:16.719 ⇒ 01:09:23.769 Emily Giant: … Question. Can you show me how… or, like, send me an article or whatever on how to drop?

735 01:09:23.949 ⇒ 01:09:27.199 Emily Giant: tables in Redshift, if there’s just, like, a command, because

736 01:09:27.369 ⇒ 01:09:32.379 Emily Giant: With all the renaming, we’re just getting a lot of clutter again.

737 01:09:32.679 ⇒ 01:09:39.219 Emily Giant: And I’d love to, like, be able to just, when I know something’s junk, just go in and, like, trash it in redshift.

738 01:09:39.590 ⇒ 01:09:43.710 Uttam Kumaran: Sure, … Yeah, I can do that. So…

739 01:09:48.560 ⇒ 01:09:54.229 Uttam Kumaran: Another thing we can do is… …

740 01:09:54.350 ⇒ 01:10:00.230 Uttam Kumaran: have this kind of, like… the typical way this works is you do what’s called, like, kind of, like, garbage collection, which…

741 01:10:00.380 ⇒ 01:10:05.060 Uttam Kumaran: You… we could run a script that looks at

742 01:10:05.720 ⇒ 01:10:09.330 Uttam Kumaran: Any table that hasn’t been queried, like, in the last 60 days.

743 01:10:09.490 ⇒ 01:10:15.350 Uttam Kumaran: Or 90 days. And then that sort of builds… it spills a report for us.

744 01:10:15.770 ⇒ 01:10:18.750 Uttam Kumaran: And then we can look at, can we just go ahead and drop these?

745 01:10:19.700 ⇒ 01:10:22.230 Emily Giant: Nice, yeah, that would be awesome.

746 01:10:22.230 ⇒ 01:10:22.910 Uttam Kumaran: Okay.

747 01:10:30.540 ⇒ 01:10:34.999 Uttam Kumaran: And that should line up with, yeah, with the ones that are not connected, anyways.

748 01:10:41.110 ⇒ 01:10:48.430 Uttam Kumaran: The other thing I’m starting to do is also I’m moving, kind of, like, large pieces of logic to, like, macros.

749 01:10:48.830 ⇒ 01:10:49.970 Emily Giant: Mmm.

750 01:10:51.150 ⇒ 01:10:54.969 Uttam Kumaran: It’s just, like, cleaning up some of the existing tables.

751 01:10:55.160 ⇒ 01:10:58.849 Uttam Kumaran: I also moved… I’m moving part of, like, the…

752 01:10:59.000 ⇒ 01:11:10.389 Uttam Kumaran: like, the grant logic, which happens at the end of, like, model runs, where it grants select a Looker user. I moved that to a macro, because we can add… we added metaplane user, we’re gonna add a couple more.

753 01:11:10.670 ⇒ 01:11:11.400 Uttam Kumaran: ….

754 01:11:11.400 ⇒ 01:11:11.930 Emily Giant: Sweet, okay.

755 01:11:11.930 ⇒ 01:11:14.390 Uttam Kumaran: So I’m sort of, like, consolidating that a little bit.

756 01:11:14.560 ⇒ 01:11:21.119 Uttam Kumaran: … And then, the other thing I did is, …

757 01:11:21.570 ⇒ 01:11:29.340 Uttam Kumaran: I added a functionality, so there are incremental models that we will make modifications to, but when we test in

758 01:11:29.540 ⇒ 01:11:44.700 Uttam Kumaran: staging, like, in the staging PR, they can often take, like, really long, because they’re running the entire thing. So I created a macro that actually just, like, cuts it off, so anything incremental that runs in staging is just the last 3 days.

759 01:11:45.460 ⇒ 01:11:50.520 Uttam Kumaran: So that, because, you know, when we’re making a change, you don’t… we don’t care about, like, it…

760 01:11:50.940 ⇒ 01:11:58.400 Uttam Kumaran: Doing the full refresh, and… Staging, it’s creating a new schema for every… staging run.

761 01:11:58.920 ⇒ 01:11:59.950 Uttam Kumaran: …

762 01:12:00.220 ⇒ 01:12:06.900 Uttam Kumaran: So, like, for example, I was making changes to Tableau items like Ceph, and it’s taking… it was, like, timing out.

763 01:12:07.040 ⇒ 01:12:13.190 Uttam Kumaran: And then I was like, why am I running this… the whole thing every time? I just want to check that the last, like, few days works.

764 01:12:13.440 ⇒ 01:12:19.070 Uttam Kumaran: So, I built, like, this sort of, like, dynamic logic that says if it’s in this… if it’s staging

765 01:12:19.510 ⇒ 01:12:24.399 Uttam Kumaran: if it’s the target equals staging, then just filter the last 3 days. Otherwise.

766 01:12:24.690 ⇒ 01:12:34.049 Uttam Kumaran: let the whole thing go. So that way we can test things and staging a bit faster. Because I don’t think anyone’s altered some of these tables, and some of these I’ve moved to incremental.

767 01:12:34.340 ⇒ 01:12:39.809 Uttam Kumaran: But, like, I’m getting frustrated that just testing simple stuff is taking, like.

768 01:12:39.810 ⇒ 01:12:40.200 Emily Giant: 15 minutes.

769 01:12:40.200 ⇒ 01:12:40.840 Uttam Kumaran: That’s…

770 01:12:41.010 ⇒ 01:12:48.129 Uttam Kumaran: So there’s kind of two things that I’ve been doing. Yeah, I’ve been… I’ve been running things locally, so, well…

771 01:12:48.470 ⇒ 01:12:49.780 Uttam Kumaran: Yeah, technically, locally.

772 01:12:49.910 ⇒ 01:12:55.889 Uttam Kumaran: And then I, … send things to Staging PR.

773 01:12:56.050 ⇒ 01:13:01.879 Uttam Kumaran: So, one thing that I can also probably share is just, like, how to do that. ….

774 01:13:01.880 ⇒ 01:13:06.769 Emily Giant: Yeah, definitely. I want to see the macros, too, because I don’t know how to do that.

775 01:13:07.200 ⇒ 01:13:09.219 Emily Giant: learn, but I don’t know how to do them.

776 01:13:09.510 ⇒ 01:13:11.079 Emily Giant: I mean, I know what they are.

777 01:13:11.370 ⇒ 01:13:16.090 Emily Giant: But… I’m not sure, like, best practices type stuff.

778 01:13:16.330 ⇒ 01:13:20.850 Uttam Kumaran: Yeah, one thing I want to share with you is I’ve been using Cursor for, like, everything, but I….

779 01:13:20.850 ⇒ 01:13:22.620 Emily Giant: Yeah, how do I use it?

780 01:13:22.620 ⇒ 01:13:37.989 Uttam Kumaran: Yeah, I want to give you, like, the masterclass. I think probably, like, later this week. I… I’ve been using it all last week for different types of fixes, and so I can… I can show you. But then I’ll also… I want to set up how you can run things locally.

781 01:13:38.110 ⇒ 01:13:44.979 Uttam Kumaran: Meaning, like, it actually hits the dbt Cloud instance, but then you can kind of move… you can move to…

782 01:13:45.630 ⇒ 01:13:49.629 Uttam Kumaran: out of this, and just move all into cursor, and then….

783 01:13:49.630 ⇒ 01:13:51.970 Emily Giant: Try it, make fixes, change it.

784 01:13:51.970 ⇒ 01:13:54.880 Uttam Kumaran: Try it, then push it to staging, try it.

785 01:13:55.010 ⇒ 01:13:58.400 Uttam Kumaran: And then… and then get it reviewed and merge.

786 01:13:58.950 ⇒ 01:14:01.390 Uttam Kumaran: So I can show you my, like, development workflow.

787 01:14:01.630 ⇒ 01:14:04.980 Emily Giant: Yeah, that would be really great. Like, I feel like what’s taken me so long with…

788 01:14:05.240 ⇒ 01:14:13.780 Emily Giant: this PR is just, like, the testing in my local, like, the amount of time it takes to do all of those steps the way I’m doing it is, like, impossible and unsustainable.

789 01:14:14.080 ⇒ 01:14:18.750 Uttam Kumaran: Yeah, so maybe we should aim for that. I’ll… maybe we should just try to do that, like, Friday, maybe.

790 01:14:19.080 ⇒ 01:14:20.679 Emily Giant: Yeah, that’d be awesome.

791 01:14:25.410 ⇒ 01:14:29.450 Emily Giant: And I really want to get into cursor, but I’ve been so busy that I’m like, I know that this.

792 01:14:29.450 ⇒ 01:14:31.700 Uttam Kumaran: No, I’ll get you in there. You’ll be like.

793 01:14:31.700 ⇒ 01:14:32.849 Emily Giant: This is insane.

794 01:14:32.850 ⇒ 01:14:42.839 Uttam Kumaran: you’ll be like, this is crazy. You may… you may, like, not like that I waited, because it’s actually incredible, but I just, like, needed to figure out, like, how to use it with dbt.

795 01:14:42.950 ⇒ 01:14:44.720 Uttam Kumaran: And what are, like.

796 01:14:44.870 ⇒ 01:14:54.780 Uttam Kumaran: what are the pitfalls? Because, for example, you can have Cursor, like, say, go do something, and then it will just, like, start looping, because it’ll just keep taking steps.

797 01:14:55.080 ⇒ 01:14:58.990 Uttam Kumaran: And so you want to be careful with, like, how much information you provide it.

798 01:14:59.440 ⇒ 01:15:03.619 Uttam Kumaran: Yeah. Like, the way you… yeah, there’s, like, some nuance.

799 01:15:03.920 ⇒ 01:15:08.100 Uttam Kumaran: That I just had to learn the hard way this past week, so….

800 01:15:08.740 ⇒ 01:15:21.719 Emily Giant: Well, thank you for doing that for the both of us, but I would love, like, to get into Cursor and start using it. I feel like I’m really missing an opportunity. I definitely have learned how to, like, be an old horse that pulls the plow manually.

801 01:15:21.720 ⇒ 01:15:22.560 Uttam Kumaran: No, it’s really nice.

802 01:15:22.560 ⇒ 01:15:23.540 Emily Giant: I mean, you’re still neat.

803 01:15:23.540 ⇒ 01:15:26.700 Uttam Kumaran: to know DBT, like, but…

804 01:15:27.050 ⇒ 01:15:38.010 Uttam Kumaran: there’s things like, look through these five tables. For example, some of the optimizations I did, I was like, hey, can you brainstorm with me, like, what optimizations there are for a table like this?

805 01:15:38.010 ⇒ 01:15:38.640 Emily Giant: Oh my god.

806 01:15:38.640 ⇒ 01:15:49.509 Uttam Kumaran: gives me some ideas, and I’m like, okay, idea 1 and 3, I’m good for. Let’s go ahead and, like, try to make that change. And it just, like, took what would have taken me quite a while to…

807 01:15:50.270 ⇒ 01:15:51.940 Uttam Kumaran: To do that really quick.

808 01:15:51.940 ⇒ 01:15:53.470 Emily Giant: really nice.

809 01:15:53.660 ⇒ 01:15:54.830 Uttam Kumaran: Yeah.

810 01:15:54.830 ⇒ 01:16:00.389 Emily Giant: Yeah. Cool, okay, so on Friday, you think we can set up some time to just, like.

811 01:16:00.740 ⇒ 01:16:03.840 Emily Giant: do the get Emily into cursor with dbt? Yes.

812 01:16:03.920 ⇒ 01:16:04.890 Uttam Kumaran: Yassin.

813 01:16:05.320 ⇒ 01:16:06.000 Emily Giant: Okay.

814 01:16:08.290 ⇒ 01:16:09.779 Emily Giant: That makes me happy.

815 01:16:10.900 ⇒ 01:16:15.469 Uttam Kumaran: Okay, cool, so as soon as you’re ready with… I’m gonna just go ahead…

816 01:16:16.020 ⇒ 01:16:20.790 Uttam Kumaran: Well, I guess I can wait till your PR is there, but I’ll probably start prepping some of this.

817 01:16:21.470 ⇒ 01:16:26.020 Emily Giant: Yeah, oh, that doesn’t matter. They’re not gonna touch, really. So, … Okay.

818 01:16:26.650 ⇒ 01:16:35.230 Emily Giant: Yeah, I don’t… all of the models are, like, net new that I’m deploying, since I didn’t want to, like, completely disrupt production.

819 01:16:35.350 ⇒ 01:16:44.140 Emily Giant: But, like, once that’s out there, and I’ve been testing it so much that, like, knock on wood, but I’m pretty sure we’re not gonna need those old models anymore, we can….

820 01:16:44.630 ⇒ 01:16:46.419 Uttam Kumaran: get rid of those, and they’re….

821 01:16:46.420 ⇒ 01:16:50.330 Emily Giant: like, chunky models that we’re getting rid of, too. So, that’ll be good.

822 01:16:50.330 ⇒ 01:16:50.920 Uttam Kumaran: Okay.

823 01:16:52.000 ⇒ 01:16:57.130 Emily Giant: All right, cool. Well, thank you. Really looking forward to cursor time.

824 01:16:57.130 ⇒ 01:17:02.520 Uttam Kumaran: Oh, I have one other question. So, the North Beam API key is not working?

825 01:17:02.640 ⇒ 01:17:04.729 Uttam Kumaran: Are you in North Beam, by the way?

826 01:17:05.010 ⇒ 01:17:14.429 Emily Giant: Oh my god, yes, but I… this is really embarrassing. I think I’ve been sent two invites and didn’t sign in in time, and I’m, like, too embarrassed to ask Chris to send me another invite. Hold on.

827 01:17:14.780 ⇒ 01:17:21.440 Uttam Kumaran: I think Zach’s very busy, and I would love your help with this API key nonsense that I’m happy to deal with.

828 01:17:21.530 ⇒ 01:17:22.779 Emily Giant: And I feel bad for you.

829 01:17:22.780 ⇒ 01:17:25.840 Uttam Kumaran: him, but I just, like, need to get it figured out.

830 01:17:27.900 ⇒ 01:17:32.969 Emily Giant: … I bet either PK or Chris can help.

831 01:17:33.130 ⇒ 01:17:36.049 Emily Giant: So the API key just isn’t working.

832 01:17:36.350 ⇒ 01:17:42.029 Uttam Kumaran: Yeah, I think I… I just, like, I just need to see the interface and try a couple things, like….

833 01:17:43.900 ⇒ 01:17:47.220 Emily Giant: Okay. Either that could be me, or I could just sit on the phone with someone and do that.

834 01:17:47.990 ⇒ 01:17:55.889 Emily Giant: … No, I… Sorry, I’m just so, like, humiliated that I’ve two times…

835 01:17:56.150 ⇒ 01:18:03.270 Emily Giant: Not logged in in time to friggin’… North Beam.

836 01:18:03.530 ⇒ 01:18:04.960 Emily Giant: I thought I had.

837 01:18:05.240 ⇒ 01:18:06.620 Emily Giant: I’ll ask Chris.

838 01:18:06.770 ⇒ 01:18:09.360 Emily Giant: … One sec.

839 01:18:10.650 ⇒ 01:18:11.820 Emily Giant: We’ll just do it now.

840 01:18:30.960 ⇒ 01:18:33.560 Emily Giant: I’ll just do a group message real quick here.

841 01:19:28.220 ⇒ 01:19:31.310 Emily Giant: Sorry that I’m making you, like, babysit me while I write this message, but sometimes.

842 01:19:31.310 ⇒ 01:19:35.490 Uttam Kumaran: No, no, no, I’m not… don’t worry, I’m… I’m… yeah, no problem.

843 01:19:36.750 ⇒ 01:19:48.740 Emily Giant: Alright, I have reached out to Chris to give you access, so that way, like, I think in the long run, that’ll be helpful too, just to be able to, like, see, like, for Polytomic even, like, what it is that they’re…

844 01:19:49.580 ⇒ 01:19:50.750 Emily Giant: working with.

845 01:19:57.640 ⇒ 01:19:59.009 Emily Giant: So we’ve got that.

846 01:20:02.240 ⇒ 01:20:06.679 Emily Giant: Big deployment and route. Just gotta do a little bit more testing.

847 01:20:09.030 ⇒ 01:20:11.710 Emily Giant: And then… Yeah.

848 01:20:12.800 ⇒ 01:20:13.520 Uttam Kumaran: Okay.

849 01:20:13.900 ⇒ 01:20:14.530 Emily Giant: Cool.

850 01:20:15.140 ⇒ 01:20:15.480 Uttam Kumaran: Okay.

851 01:20:15.480 ⇒ 01:20:20.250 Emily Giant: Alright, I’m around, I pretty much work from the moment I wake up till the

852 01:20:21.230 ⇒ 01:20:24.619 Emily Giant: The night, so if you need anything, just let me know.

853 01:20:24.620 ⇒ 01:20:26.419 Uttam Kumaran: Okay, alright, thank you.

854 01:20:26.420 ⇒ 01:20:28.090 Emily Giant: Alright, talk to you later. Bye.