Meeting Title: Brainforge Revenue and QA Grooming Date: 2025-10-07 Meeting participants: Emily Giant, Amber Lin


WEBVTT

1 00:00:40.360 00:00:41.490 Emily Giant: Hello.

2 00:00:41.710 00:00:43.000 Amber Lin: Hi there!

3 00:00:43.140 00:00:45.620 Amber Lin: Sorry for pulling you in for our second.

4 00:00:45.620 00:00:46.570 Emily Giant: That’s fine.

5 00:00:46.740 00:00:50.279 Emily Giant: It makes a lot of sense. I have a thought before I forget.

6 00:00:50.440 00:00:54.700 Emily Giant: I think that… for the stuff for Perry to QA,

7 00:00:55.270 00:00:57.389 Emily Giant: I would love to do QA…

8 00:00:57.530 00:01:03.720 Emily Giant: first with, Demolade before Perry, because sometimes…

9 00:01:04.110 00:01:21.369 Emily Giant: it’s not at a spot where Perry’s gonna know how to QA it, and I just want to make sure, like, what he’s planning to show, that I have an idea of what that plan is, so I can better structure it for Perry, because I kind of know, like, what she’s used to looking at and what she’s not, so maybe, like.

10 00:01:21.990 00:01:25.880 Emily Giant: Even if we do a mock session on Thursday, or something like that.

11 00:01:25.880 00:01:28.590 Amber Lin: Yeah, let me send that in the…

12 00:01:35.700 00:01:42.800 Amber Lin: Okay, let me… Send in the client in the external channel.

13 00:01:51.410 00:01:53.880 Amber Lin: Free QA session.

14 00:01:56.760 00:01:58.539 Emily Giant: I’m sorry, one moment, I’ll be right back.

15 00:02:01.130 00:02:02.880 Emily Giant: I’m sorry, can you think honey.

16 00:02:03.540 00:02:04.889 Emily Giant: Oh, baby, yeah, I know.

17 00:02:05.180 00:02:05.949 Emily Giant: Thank you for it.

18 00:02:14.200 00:02:17.749 Emily Giant: Pat needed to be let in. She was meowing very loudly.

19 00:02:21.940 00:02:24.080 Amber Lin: Oh, so sweet.

20 00:02:26.650 00:02:28.200 Amber Lin: Okay, set.

21 00:02:28.810 00:02:33.520 Amber Lin: And then we can look at,

22 00:02:34.110 00:02:36.169 Amber Lin: Can you look at Perry’s calendar for free?

23 00:02:36.170 00:02:41.900 Emily Giant: Let me share the screen, just so you can… see everything.

24 00:02:47.180 00:02:51.530 Emily Giant: Okay, let me pull up… Calendars…

25 00:02:51.820 00:02:53.610 Emily Giant: Alright, can you see my screen?

26 00:03:15.190 00:03:17.089 Amber Lin: Oh, she has a half day.

27 00:03:17.090 00:03:17.970 Emily Giant: A.

28 00:03:18.910 00:03:32.549 Amber Lin: Okay, and her 9 a.m. is booked, because she’s in EST, so it’s just from 11 to 12, which is my… well, I’m not here, which 11…

29 00:03:32.550 00:03:33.329 Emily Giant: Right, yeah.

30 00:03:33.330 00:03:33.980 Amber Lin: Eat.

31 00:03:34.370 00:03:35.370 Amber Lin: Okay.

32 00:03:35.880 00:03:41.339 Amber Lin: So maybe… 11.30 to 12?

33 00:03:41.570 00:03:42.989 Emily Giant: Yeah, that works.

34 00:03:43.520 00:03:44.330 Amber Lin: Okay.

35 00:03:44.920 00:03:48.370 Amber Lin: QA Session 1.

36 00:03:49.180 00:03:52.959 Amber Lin: A fairy, okay.

37 00:03:54.510 00:03:58.140 Amber Lin: 1, 2, 3… every time I have to count 3…

38 00:03:58.140 00:03:59.089 Emily Giant: I know, it’s…

39 00:03:59.890 00:04:01.580 Amber Lin: Yeah, I get it.

40 00:04:03.520 00:04:06.360 Amber Lin: Emily, and then I’ll enjoy.

41 00:04:10.770 00:04:15.180 Amber Lin: Send, and then… I can move…

42 00:04:15.670 00:04:20.859 Amber Lin: the stand-up of… how long do you think our internal QA prep and stuff will take?

43 00:04:21.230 00:04:24.959 Emily Giant: I’ll do it with Demolade during our working session Thursday.

44 00:04:24.960 00:04:26.750 Amber Lin: Okay, okay, awesome.

45 00:04:28.340 00:04:34.170 Amber Lin: Yeah, that sounds good. Okay, that’s done. I’ll wait for her to confirm.

46 00:04:35.340 00:04:40.369 Amber Lin: Okay, back to grooming. I really think we’re very, very close.

47 00:04:40.490 00:04:48.219 Amber Lin: Yeah, I just also said that for the inventory more, and our very, very close took 3 more months.

48 00:04:48.410 00:04:54.650 Emily Giant: That inventory table is not easy to work with. That’s all I can say. Like, there’s no…

49 00:04:55.290 00:05:00.510 Emily Giant: from the source, it’s a mess. So, it was a lot harder than using Shopify tables.

50 00:05:02.290 00:05:07.219 Amber Lin: Yeah, I can share screen, and then we can work on it together.

51 00:05:07.470 00:05:08.130 Emily Giant: Perfect.

52 00:05:08.130 00:05:12.640 Amber Lin: Alright. Share desktop.

53 00:05:12.870 00:05:23.470 Amber Lin: So… Just gonna go through… These and add them to projects first.

54 00:05:23.840 00:05:34.140 Amber Lin: So, that’s… These are… Revenue…

55 00:05:34.330 00:05:37.280 Amber Lin: Revenue… is North Bay also revenue?

56 00:05:37.730 00:05:39.390 Emily Giant: That is marketing.

57 00:05:41.740 00:05:45.109 Amber Lin: So, we should create another project, I think.

58 00:05:45.480 00:05:46.170 Emily Giant: Yeah.

59 00:05:51.800 00:05:53.580 Amber Lin: What does marketing include?

60 00:05:53.980 00:06:02.390 Emily Giant: That is, like… Campaigns,

61 00:06:03.810 00:06:12.660 Emily Giant: attribute, like, North Beam, anything North Beam, like, those attribution models, GA4.

62 00:06:12.970 00:06:14.779 Emily Giant: or Google Analytics.

63 00:06:17.190 00:06:18.549 Amber Lin: Okay. Yes, definitely.

64 00:06:18.550 00:06:19.700 Emily Giant: That’s about all of them, I think.

65 00:06:19.700 00:06:24.629 Amber Lin: So, is his promo… this one is still revenue, right?

66 00:06:24.810 00:06:26.270 Emily Giant: It is, yes.

67 00:06:26.270 00:06:37.830 Amber Lin: I’ll do these, and I’ll say it’s marking… This, I’ll say revenue… Clean up… That per…

68 00:06:38.190 00:06:42.780 Amber Lin: Is this done, or… okay, I guess this is ad hoc.

69 00:06:43.180 00:06:46.120 Emily Giant: Yeah, that’s, like, an ongoing type thing, too.

70 00:06:49.400 00:06:56.450 Amber Lin: carbon cycle… This is also ad hoc.

71 00:06:59.290 00:07:01.399 Amber Lin: So in the current cycle.

72 00:07:01.680 00:07:11.070 Amber Lin: Subscriptions… Is subscriptions part of revenue, or is it just subscriptions?

73 00:07:11.070 00:07:16.119 Emily Giant: It is. It’s part of revenue, but… Also, its own thing.

74 00:07:16.500 00:07:27.820 Emily Giant: There are parts of that and parts of marketing that are a part of revenue, but they also have, like, their own forecasting and budget, so there’s also separate things.

75 00:07:27.820 00:07:28.610 Amber Lin: Huh.

76 00:07:29.840 00:07:37.260 Amber Lin: Ad hoc… Process for package…

77 00:07:37.680 00:07:40.239 Amber Lin: Is this something that we want to do?

78 00:07:40.670 00:07:48.100 Emily Giant: Create new process for packaging costs… yes. Not urgent, though.

79 00:07:49.930 00:07:57.399 Emily Giant: This was something that Dem… not Demulade, Utam and I had talked about, when I was gone, and

80 00:07:57.750 00:08:03.020 Emily Giant: That model started failing, that for, courier…

81 00:08:03.430 00:08:09.079 Emily Giant: commissions. It’s because of the packaging cost upload process, and Utam

82 00:08:09.420 00:08:12.959 Emily Giant: Wanted to, like, circle up with me and go over

83 00:08:13.160 00:08:15.920 Emily Giant: how to do it directly in NetSuite.

84 00:08:16.680 00:08:17.620 Amber Lin: Oh…

85 00:08:25.420 00:08:32.059 Amber Lin: Yeah, so I’ll say it’s… Ad hoc. How long would this take?

86 00:08:33.080 00:08:37.139 Emily Giant: I have no idea, there’s a…

87 00:08:37.270 00:08:47.490 Emily Giant: Probably not long at all. Like, one point, probably, but I don’t know if he needs to look up how to do it. If he already knows how to do it, then it’s a matter of, like, training the teams, and then…

88 00:08:48.130 00:08:53.829 Emily Giant: Setting up a new polyatomic model, but… the actual process?

89 00:08:54.080 00:08:56.279 Amber Lin: Do you think Awage can take this?

90 00:08:56.630 00:08:58.020 Emily Giant: No, I don’t think so.

91 00:08:58.020 00:08:58.820 Amber Lin: Okay.

92 00:08:59.400 00:09:05.100 Emily Giant: I think UTAM needs to at first, because it’s less about the model, and more about…

93 00:09:05.390 00:09:09.949 Emily Giant: getting the process into NetSuite so that we can model it.

94 00:09:10.750 00:09:12.380 Emily Giant: Have some ideas there, so…

95 00:09:12.380 00:09:13.800 Amber Lin: Gotcha, okay.

96 00:09:24.150 00:09:27.120 Amber Lin: new process in… NetSuite.

97 00:09:32.800 00:09:36.110 Amber Lin: Great, that’s all the random tickets lying around.

98 00:09:36.110 00:09:37.040 Emily Giant: Nice.

99 00:09:37.040 00:09:43.679 Amber Lin: And for revenue… I think we are, like, we don’t have…

100 00:09:44.740 00:09:53.699 Amber Lin: Yeah, we have some stuff left. We did load the base tables, as you can see, like, once we finish up

101 00:09:53.840 00:10:03.190 Amber Lin: These remaining… ones… We will just need to do the summary tables, which will take definitely, like.

102 00:10:03.320 00:10:10.790 Amber Lin: another week. And then there’s all these Looker… Tickets,

103 00:10:11.840 00:10:16.510 Amber Lin: And these are, like, the training sessions afterwards.

104 00:10:16.510 00:10:17.360 Emily Giant: Okay.

105 00:10:17.360 00:10:21.280 Amber Lin: Yeah, and then historicals…

106 00:10:24.400 00:10:26.550 Amber Lin: Is that historicals?

107 00:10:26.830 00:10:31.659 Emily Giant: Build LMS Refunds Intermediate Model for Refund Mapping. Can you click into it?

108 00:10:31.660 00:10:37.230 Amber Lin: Yes, well, we did. I think I asked you, but I may have mixed it up with another ticket.

109 00:10:37.230 00:10:40.190 Emily Giant: I think you’re correct here, actually.

110 00:10:40.770 00:10:43.080 Emily Giant: I think this is just making sure that

111 00:10:43.830 00:10:46.879 Emily Giant: once we set up Shopify, that the new refund model

112 00:10:47.030 00:10:50.560 Emily Giant: The old data is aligned to the new model.

113 00:10:50.720 00:10:51.450 Amber Lin: Huh.

114 00:10:59.920 00:11:05.549 Amber Lin: But are we able to do this right now, even? Yeah. Okay.

115 00:11:06.550 00:11:10.850 Amber Lin: And, let me remove the due date.

116 00:11:11.950 00:11:13.900 Amber Lin: That we need to do.

117 00:11:14.390 00:11:16.180 Emily Giant: Historicals…

118 00:11:16.950 00:11:21.270 Amber Lin: Do we have any…

119 00:11:21.970 00:11:25.480 Amber Lin: Requirements for how we’re gonna do the historicals?

120 00:11:25.480 00:11:35.689 Emily Giant: So, the requirements are… To align historical subscriptions to the new, fact subscriptions table.

121 00:11:35.690 00:11:36.429 Amber Lin: Huh.

122 00:11:37.300 00:11:44.760 Emily Giant: And so I’m already working on this ticket, so it’s… essentially, like, taking Sticky I.O,

123 00:11:45.130 00:12:01.549 Emily Giant: And then the two other programs we’ve used historically for subscriptions, and making sure that, like, there’s a seamless transition in dbt and Looker, so that we can do year-over-year comps without, like, having to jump between tables.

124 00:12:09.070 00:12:10.250 Amber Lin: Okay.

125 00:12:11.850 00:12:17.799 Amber Lin: Okay, gotcha, that’s good. Priorities would say, like, medium.

126 00:12:17.800 00:12:19.709 Emily Giant: Either high or medium.

127 00:12:19.710 00:12:23.490 Amber Lin: Okay, it is high, because I want to get the stuff for Perry as high first.

128 00:12:24.170 00:12:26.160 Amber Lin: And then this one…

129 00:12:27.890 00:12:36.990 Amber Lin: No, it’s blocked by North Bee. Is this still blocked now that we’re going with the Shopify UTM stuff for North Bean attribution data?

130 00:12:38.320 00:12:39.579 Emily Giant: I don’t know.

131 00:12:39.710 00:12:42.500 Emily Giant: That’s a good question for PK.

132 00:12:42.620 00:12:44.979 Emily Giant: Paid media…

133 00:12:48.650 00:12:55.720 Amber Lin: What are we trying to do here, actually? Same thing as… all the historicals are gonna have the same definition of, like…

134 00:12:56.000 00:13:00.730 Emily Giant: we need… free Shopify data for year-over-year comps.

135 00:13:03.140 00:13:09.689 Emily Giant: And so it’s just updating those tables so that they match the new ideal state, instead of having to, like.

136 00:13:10.340 00:13:16.880 Emily Giant: do it all in a Google Doc, because they’re two different… asynchronous… data models.

137 00:13:16.910 00:13:17.780 Amber Lin: Huh.

138 00:13:18.040 00:13:22.859 Amber Lin: Gotcha, and is it the fact subscriptions data, or is it a different table?

139 00:13:23.910 00:13:25.679 Emily Giant: I think it would be.

140 00:13:25.680 00:13:26.440 Amber Lin: Refresh?

141 00:13:26.630 00:13:28.470 Emily Giant: Paid media. Oof.

142 00:13:29.620 00:13:31.860 Emily Giant: Maybe Google Analytics?

143 00:13:34.550 00:13:37.760 Emily Giant: I would need to find that out from… Chris.

144 00:13:38.330 00:13:39.770 Emily Giant: Let me ask Chris.

145 00:13:43.050 00:13:45.749 Amber Lin: Gotcha. And then… let’s see…

146 00:13:46.330 00:13:52.979 Amber Lin: So we need this table, the one that we’re comparing to, and the pre-Shopify tables, which we…

147 00:13:53.430 00:13:55.680 Amber Lin: Do we know what those are?

148 00:13:58.080 00:14:00.409 Emily Giant: Not for this, that’s what I need to figure out.

149 00:14:00.410 00:14:00.830 Amber Lin: Huh?

150 00:14:00.830 00:14:01.980 Emily Giant: Mmm.

151 00:14:02.420 00:14:03.560 Emily Giant: Chris.

152 00:14:11.370 00:14:12.400 Emily Giant: Let me ask…

153 00:14:19.880 00:14:22.230 Emily Giant: I’ll ask PK at the same time.

154 00:14:22.770 00:14:25.450 Emily Giant: Okay… And Chris.

155 00:14:29.270 00:14:34.200 Amber Lin: And we know the G84 table, where that is?

156 00:14:35.590 00:14:39.040 Amber Lin: Yeah. That’s something we’re working on right now. I know I saw a ticket.

157 00:14:39.040 00:14:41.099 Emily Giant: Yeah, it’s already in…

158 00:14:41.100 00:14:43.070 Amber Lin: Ingest GA session data, okay.

159 00:14:43.070 00:14:43.660 Emily Giant: Yeah.

160 00:14:43.660 00:14:44.380 Amber Lin: stir.

161 00:14:51.730 00:14:55.560 Amber Lin: Okay, so I’ll put this as need response.

162 00:14:56.730 00:14:58.050 Amber Lin: And…

163 00:15:01.420 00:15:02.180 Amber Lin: Hmm.

164 00:15:02.800 00:15:09.670 Amber Lin: This seems like an… Ad hoc, or internal task.

165 00:15:11.220 00:15:14.639 Amber Lin: Is this… do you think this is important that we do it?

166 00:15:15.380 00:15:20.340 Emily Giant: It is for the, it should just be done in tandem with the

167 00:15:20.970 00:15:25.729 Emily Giant: the MART models, is the tags are how we’ve controlled the refreshes.

168 00:15:26.020 00:15:26.890 Amber Lin: And…

169 00:15:26.890 00:15:28.980 Emily Giant: The success of the jobs that run.

170 00:15:31.710 00:15:40.259 Amber Lin: Where should we insert this, then? Should we do it after we complete, like, the main model, say, subscriptions? I think that’s the only one left.

171 00:15:40.530 00:15:45.899 Amber Lin: Or should we do it after we do these tables, like, the summary tables?

172 00:15:47.660 00:15:50.479 Emily Giant: I would… I would just do it after.

173 00:15:51.220 00:15:52.460 Amber Lin: After everything?

174 00:15:53.510 00:15:57.699 Emily Giant: Well, not really. I would do it while, like, ask a…

175 00:15:57.830 00:16:07.950 Emily Giant: piece of those models. Like, if there were a checklist of what it means to build a monthly revenue summary table, adding a tag to it would be part of it.

176 00:16:08.510 00:16:13.769 Amber Lin: Okay, do we have a list of… Tags we use?

177 00:16:14.320 00:16:15.880 Amber Lin: We do.

178 00:16:18.090 00:16:26.490 Emily Giant: And that has been largely decided by UTAM and the Malade, so I would want their sign-off that, like, the list that is in

179 00:16:26.760 00:16:30.980 Emily Giant: The project file is the one they want to move forward with.

180 00:16:46.020 00:16:46.960 Amber Lin: Okay.

181 00:16:47.640 00:16:50.099 Amber Lin: Let me just ask that right now.

182 00:16:51.360 00:16:53.280 Amber Lin: Oh, 5 minutes.

183 00:16:54.510 00:16:55.170 Amber Lin: Okay.

184 00:17:11.920 00:17:17.300 Amber Lin: I’ll just ask them, is the list of tags…

185 00:17:22.390 00:17:24.030 Amber Lin: In what file?

186 00:17:25.010 00:17:27.099 Emily Giant: the project.yaml.

187 00:17:27.230 00:17:29.450 Emily Giant: or project.yml.

188 00:17:53.560 00:17:55.440 Amber Lin: Also news…

189 00:18:05.560 00:18:08.760 Amber Lin: Do you know what we’re thinking about, North Beam?

190 00:18:09.040 00:18:13.710 Amber Lin: Like, if we’re… If we can’t get attribution data.

191 00:18:14.220 00:18:20.510 Amber Lin: Okay, are we still going to ingest North Beam, or are we just going to do manual exports?

192 00:18:23.750 00:18:26.369 Emily Giant: I, I don’t know. Okay.

193 00:18:26.670 00:18:34.190 Emily Giant: I think that… Is it Awish that’s been chatting with them? Someone from Brainforge has been talking with them.

194 00:18:35.460 00:18:37.750 Emily Giant: Maybe it was you, Tom, but…

195 00:18:39.180 00:18:44.350 Emily Giant: I don’t know what the plan is, excuse me. I think we’re still going to ingest it. I don’t…

196 00:18:45.840 00:18:47.320 Emily Giant: I can’t say for sure, though.

197 00:18:51.180 00:18:53.560 Amber Lin: What type of data do we need from Northwind?

198 00:18:54.770 00:18:57.359 Emily Giant: Let me check the…

199 00:18:57.360 00:19:00.439 Amber Lin: an attribution data that I know of.

200 00:19:01.920 00:19:10.560 Emily Giant: I think it’s, like, media spend… It’s like our… CRM.

201 00:19:17.420 00:19:19.660 Emily Giant: But it isn’t at the,

202 00:19:20.240 00:19:25.469 Emily Giant: design doc, there’s a bunch of stuff in there about North Beeman Notion.

203 00:19:30.900 00:19:31.730 Amber Lin: crunchy.

204 00:19:33.050 00:19:38.000 Amber Lin: The stems… This one?

205 00:19:40.490 00:19:41.270 Emily Giant: beef.

206 00:19:43.190 00:19:44.289 Amber Lin: I hope so.

207 00:19:48.020 00:19:49.389 Amber Lin: Crash date.

208 00:19:50.480 00:19:51.620 Amber Lin: Press Shift.

209 00:19:59.230 00:20:01.000 Amber Lin: Alright, where is Northwestern?

210 00:20:10.430 00:20:11.210 Amber Lin: Hmm.

211 00:20:12.310 00:20:19.670 Emily Giant: Is it in a different… is there a different design doc? This is the one… yeah, here we go. It’s gonna be in the marketing area.

212 00:20:22.330 00:20:23.580 Emily Giant: Yep, right there.

213 00:20:24.360 00:20:29.949 Emily Giant: Marketing, sales, is there anything about a North Bean plus GA,

214 00:20:31.500 00:20:35.329 Emily Giant: So, what was our session orders and revenue by marketing channel?

215 00:20:43.490 00:20:48.050 Emily Giant: So I guess it looks like if that’s the only question they’re asking of it, then I don’t even know why we…

216 00:20:48.180 00:20:53.849 Emily Giant: I don’t even know why we have that, if… if Shopify is…

217 00:20:54.950 00:20:57.420 Emily Giant: what we’re using. Is there any other…

218 00:20:57.420 00:21:00.869 Amber Lin: I only see two north beams in this dock.

219 00:21:01.420 00:21:03.630 Amber Lin: This is the only one.

220 00:21:03.970 00:21:05.640 Amber Lin: with context.

221 00:21:06.050 00:21:09.800 Amber Lin: I think it’s the attribution model?

222 00:21:10.730 00:21:12.990 Amber Lin: Believe that’s the only thing.

223 00:21:28.010 00:21:31.469 Amber Lin: I think this is just the spend data.

224 00:21:34.740 00:21:36.010 Emily Giant: Yeah, it might be.

225 00:21:36.380 00:21:37.070 Amber Lin: Yeah.

226 00:21:37.770 00:21:39.259 Amber Lin: I’ll just say that.

227 00:21:39.840 00:21:41.739 Amber Lin: It’s not blocked anymore.

228 00:21:43.140 00:21:47.370 Amber Lin: Do next cycle… Wish.

229 00:22:27.830 00:22:34.830 Amber Lin: Shopify categorizations. What are we trying to do here?

230 00:22:36.180 00:22:42.939 Amber Lin: I’m gonna forward this… Is… What’s the deliverable here?

231 00:22:44.240 00:22:47.500 Emily Giant: So we can get all attribution details necessary.

232 00:22:49.880 00:22:52.000 Amber Lin: Does this even need to be a ticket, do you think?

233 00:22:52.000 00:22:54.079 Emily Giant: I don’t… I don’t know…

234 00:22:55.330 00:22:59.600 Amber Lin: This is for this one, the promos and discounts for finance.

235 00:23:04.280 00:23:09.180 Emily Giant: I think it’s, like, a spike ticket, so it’s not necessarily a model, it’s,

236 00:23:10.540 00:23:20.220 Emily Giant: I think it’s researching how Shopify categorizes attribution so that we know if anything is missing.

237 00:23:20.750 00:23:21.360 Amber Lin: Hmm.

238 00:23:25.850 00:23:26.540 Emily Giant: Yeah.

239 00:23:39.530 00:23:40.250 Amber Lin: Okay.

240 00:23:45.000 00:23:47.279 Amber Lin: That one, I was seeing this groomed.

241 00:23:47.680 00:23:56.249 Amber Lin: Tests, test, whatever. This one, okay, that makes sense.

242 00:24:08.910 00:24:10.320 Emily Giant: Okay, yeah, that’s…

243 00:24:10.720 00:24:13.410 Amber Lin: I think it’s… Explanatory.

244 00:24:17.120 00:24:25.620 Amber Lin: Do we need to have a revenue validation session with finance?

245 00:24:26.130 00:24:27.199 Emily Giant: I don’t think so.

246 00:24:27.910 00:24:28.680 Amber Lin: Okay.

247 00:24:29.530 00:24:32.069 Amber Lin: So… it’s canceled.

248 00:24:33.100 00:24:34.500 Amber Lin: Bags here.

249 00:24:35.360 00:24:37.880 Amber Lin: Okay.

250 00:24:38.600 00:24:43.709 Amber Lin: Summary tables. What needs to go into these summary tables?

251 00:24:43.830 00:24:46.750 Amber Lin: They’re not snapshots, right? They’re different.

252 00:24:47.170 00:24:55.249 Emily Giant: Yeah, so I would like Demolade’s feedback on this, because I don’t remember… Creating these tickets,

253 00:24:56.220 00:25:04.070 Emily Giant: as far as, like, a monthly revenue summary table, I’m not sure how this is different than, like, other…

254 00:25:05.090 00:25:11.400 Emily Giant: tables, unless it’s, like, specifically for finance. So,

255 00:25:12.830 00:25:18.250 Emily Giant: Yeah, I would… I would need his feedback there on… What was discussed.

256 00:25:18.600 00:25:20.120 Emily Giant: Or what… yeah.

257 00:25:20.120 00:25:33.939 Amber Lin: I wish I could help more on those, but those were new to me when I came back, and I’m not sure. Yeah, they were… I think I created them when we first had this design dog, so it’s actually from the very, very beginning,

258 00:25:33.940 00:25:34.590 Emily Giant: Okay.

259 00:25:34.590 00:25:42.700 Amber Lin: Let’s see if there’s… Monthly… Monthly report…

260 00:25:46.780 00:25:53.040 Amber Lin: Export monthly finance and marketing roll-ups. I think it’s for the monthly roll-ups.

261 00:25:54.330 00:25:55.490 Amber Lin: Okay.

262 00:25:56.750 00:25:57.800 Emily Giant: sense…

263 00:25:57.800 00:25:58.960 Amber Lin: Murray.

264 00:25:59.080 00:26:05.000 Amber Lin: Table… Oh, here’s something.

265 00:26:06.030 00:26:09.000 Amber Lin: Summary table…

266 00:26:19.530 00:26:20.360 Amber Lin: Okay.

267 00:26:28.410 00:26:32.770 Amber Lin: Where we will show revenue and conversions by source.

268 00:26:33.870 00:26:34.560 Amber Lin: Huh.

269 00:26:36.500 00:26:48.040 Amber Lin: Daily, sorry. Okay, let me… Add these… And then… Oh, I’ll ask here.

270 00:26:54.220 00:26:54.875 Amber Lin: Hmm…

271 00:27:11.910 00:27:13.430 Amber Lin: Brilliant.

272 00:27:28.970 00:27:29.710 Amber Lin: Right.

273 00:27:31.090 00:27:36.260 Amber Lin: So, I’ll say that this is… it’s for me.

274 00:27:36.570 00:27:37.420 Amber Lin: Alright.

275 00:27:37.790 00:27:48.710 Amber Lin: Now these Looker… First, I guess, these Looker Explorers. Did you get the… Model for fact transactions?

276 00:27:49.510 00:27:58.479 Emily Giant: I think so. I feel like Demolade sent it to me yesterday. We had a chat about it after. Let me double check, because…

277 00:27:59.090 00:28:03.059 Emily Giant: I didn’t do anything with it yet, but we did talk about it.

278 00:28:03.430 00:28:09.730 Amber Lin: I just want to confirm you have it, because then I can go ask Sutum. I think he was the one that would say, oh, I know where it is.

279 00:28:09.910 00:28:10.730 Emily Giant: Yeah.

280 00:28:12.370 00:28:14.310 Emily Giant: Let me see…

281 00:28:24.820 00:28:29.460 Emily Giant: Sorry, I have to… Refresh my Git state, okay, let me see…

282 00:28:46.600 00:28:51.099 Emily Giant: I only see old versions. Let me look at my conversation with them a lot.

283 00:29:11.650 00:29:16.440 Emily Giant: I know we talked about this, I just have to figure out where… We talked about it.

284 00:29:19.170 00:29:22.110 Amber Lin: Maybe we can search transactions?

285 00:29:22.610 00:29:26.680 Emily Giant: Oh, here, okay, so, fact, transactions, model.

286 00:29:27.420 00:29:29.649 Emily Giant: was pushed by Utom.

287 00:29:29.780 00:29:32.229 Emily Giant: Yesterday at 4.45.

288 00:29:32.730 00:29:36.139 Amber Lin: So it just wasn’t… it looks like it just wasn’t.

289 00:29:36.140 00:29:37.270 Emily Giant: deployed.

290 00:29:38.370 00:29:39.929 Amber Lin: Gosh, so we have it now.

291 00:29:40.570 00:29:41.230 Emily Giant: Yep.

292 00:29:42.860 00:29:45.209 Amber Lin: Awesome, I’ll put one touch boot.

293 00:29:45.750 00:29:50.570 Amber Lin: And then… And you have the suborders, right?

294 00:29:50.770 00:29:51.480 Emily Giant: Yes.

295 00:29:52.840 00:29:58.210 Amber Lin: What about these Looker UAT sessions?

296 00:29:59.360 00:30:05.989 Emily Giant: Yeah, I’m not going to schedule those this week.

297 00:30:06.330 00:30:07.670 Amber Lin: Oh, definitely. I think they’re gonna.

298 00:30:07.670 00:30:08.540 Emily Giant: Yes.

299 00:30:08.540 00:30:12.359 Amber Lin: after… maybe even after these? Because I feel like.

300 00:30:12.360 00:30:12.690 Emily Giant: Hmm.

301 00:30:12.690 00:30:18.610 Amber Lin: It would help you make those Looker Explorers, too. Because a lot of times they want to see…

302 00:30:18.900 00:30:22.450 Amber Lin: Month over month, week over week, even day by day.

303 00:30:22.450 00:30:22.920 Emily Giant: Thank you.

304 00:30:22.920 00:30:29.919 Amber Lin: That’s what these are for. Yeah. So these would be… maybe not even next week, they might have to be later.

305 00:30:29.920 00:30:42.039 Emily Giant: I would say 2 weeks, yeah. I’m doing smaller user acceptance testing with Perry and Felipe, and then I added the care team yesterday, too, because they do a lot of, like, refund and transactional data.

306 00:30:42.680 00:30:48.850 Emily Giant: I’m… But yeah, validate SKU-level promotions and subscriptions dashboards.

307 00:30:59.340 00:31:00.270 Emily Giant: I re…

308 00:31:01.200 00:31:03.339 Amber Lin: Do we even have those dashboards?

309 00:31:03.590 00:31:08.579 Amber Lin: Like, are we validating their dashboards, or are we giving them something to validate?

310 00:31:09.880 00:31:11.940 Emily Giant: I… I think it would…

311 00:31:12.200 00:31:18.410 Emily Giant: Right now, we’re just giving them something to val… no, they’re, like, playing around with the data while… while…

312 00:31:19.130 00:31:23.630 Emily Giant: no dashboard is, like, ex… in existence. So I think it would…

313 00:31:23.810 00:31:31.070 Emily Giant: Probably be a good idea to take their dashboards, or at least one of their main ones, and recreate it with our new data tables.

314 00:31:31.960 00:31:37.079 Emily Giant: And use that for UAT, so that they’re looking at it in a format that they understand.

315 00:31:38.660 00:31:41.420 Amber Lin: So, are we going to make that dashboard, or are we helping.

316 00:31:41.420 00:31:44.449 Emily Giant: We should. Yeah. Okay, so we need…

317 00:31:45.060 00:31:51.189 Amber Lin: to… get what dashboard, and then make them. Do you know what dashboards…

318 00:31:52.130 00:31:56.180 Amber Lin: The dashboard audit. Okay, great. So we have that.

319 00:31:57.410 00:32:01.109 Amber Lin: And then… create… I’m gonna just create a ticket.

320 00:32:01.640 00:32:11.420 Amber Lin: create, re-create… Dashboard… Alright.

321 00:32:13.860 00:32:15.340 Amber Lin: Cool models.

322 00:32:17.660 00:32:20.779 Amber Lin: Would you be doing those… these type of tickets?

323 00:32:21.350 00:32:25.590 Emily Giant: It’d probably be best to split it up.

324 00:32:26.000 00:32:30.110 Emily Giant: between… because these will come once, like…

325 00:32:30.440 00:32:41.290 Emily Giant: revenue is totally done, and descriptions are totally done, so it would be best to split it up between the three of us, Awash, Devilati, and myself.

326 00:32:42.820 00:32:49.220 Amber Lin: Yeah, that makes sense. So, how many dashboards are we recreating, or are we just doing one per team?

327 00:32:49.390 00:33:00.849 Emily Giant: I would say probably one for every team but SNOP, and we should do two for them. We should do the daily performance send, and the daily inventory send.

328 00:33:01.610 00:33:04.060 Amber Lin: Bailey Performance…

329 00:33:05.680 00:33:10.180 Amber Lin: Dashboard… Great. Great.

330 00:33:15.350 00:33:20.700 Amber Lin: Oh, we add… Daily… what cent?

331 00:33:20.700 00:33:21.950 Emily Giant: Inventory.

332 00:33:22.400 00:33:29.589 Amber Lin: Inventory. Okay, do you know which one we’re doing for the marketing slash sales team?

333 00:33:29.590 00:33:31.869 Emily Giant: Mmm… let me see…

334 00:33:43.230 00:33:47.610 Emily Giant: I know that we have all of these saved in Looker, under Brainforge.

335 00:33:47.800 00:33:51.220 Emily Giant: This is much I know, but I don’t know the exact name of it.

336 00:33:56.360 00:34:00.279 Emily Giant: For that one in particular, I would do…

337 00:34:01.360 00:34:07.490 Emily Giant: The subs… there’s one that’s called Subscriptions Reporting Example. Let me see what this is.

338 00:34:10.280 00:34:12.250 Emily Giant: This is just a report, though.

339 00:34:12.600 00:34:14.040 Emily Giant: Hmm,

340 00:34:25.510 00:34:31.160 Emily Giant: Here, it’s subscriptions dash would be the one. Here’s a link to it.

341 00:34:31.380 00:34:31.989 Amber Lin: Huh.

342 00:34:34.280 00:34:35.790 Amber Lin: Oops, oops.

343 00:34:37.550 00:34:39.750 Amber Lin: Is it in the… okay, I’m gone.

344 00:34:43.409 00:34:46.679 Amber Lin: And then for the finance team, what will we be doing?

345 00:34:47.520 00:34:48.239 Emily Giant: Oof.

346 00:34:49.590 00:34:50.770 Emily Giant: Let’s see…

347 00:35:03.850 00:35:12.080 Emily Giant: Oh, here’s a bunch more for the sales team that are really… Good, and we’re never,

348 00:35:13.040 00:35:17.779 Emily Giant: Able to be in… Looker before?

349 00:35:19.060 00:35:25.680 Emily Giant: let me… maybe this is a better one. For finance? I don’t know… so…

350 00:35:25.810 00:35:33.189 Emily Giant: the reason I’m being cagey with that is that, they’re changing their process to move everything into NetSuite instead of QuickBooks.

351 00:35:33.190 00:35:33.680 Amber Lin: So.

352 00:35:33.680 00:35:38.049 Emily Giant: I don’t want to spend too much time doing anything for them until that process is over.

353 00:35:53.570 00:35:59.730 Amber Lin: Gotcha, so I will just put it as that. For the marketing and sales team.

354 00:36:00.890 00:36:04.030 Amber Lin: Are we still doing just one, or should we do more?

355 00:36:04.030 00:36:09.200 Emily Giant: The other one that I just sent, is a Shopify

356 00:36:09.510 00:36:12.839 Emily Giant: report, but if we can recreate that in Looker.

357 00:36:15.950 00:36:18.830 Amber Lin: So we’re not doing the… are we still doing subscriptions dashboard?

358 00:36:18.830 00:36:20.330 Emily Giant: Yeah, we should do both.

359 00:36:20.330 00:36:21.040 Amber Lin: Okay.

360 00:36:29.750 00:36:33.200 Amber Lin: This is Shopify…

361 00:36:37.110 00:36:42.030 Amber Lin: Alright, so those would take… sometime.

362 00:36:45.870 00:36:53.800 Amber Lin: So I’ll do the… Looker Explores, and then these are all blocked.

363 00:36:56.000 00:36:57.510 Amber Lin: Aren’t they unblocked?

364 00:36:59.120 00:37:06.269 Emily Giant: No, not necessarily. All the marketing one… the marketing one is, but, yeah, no, yep, they’re all blocked.

365 00:37:06.500 00:37:07.220 Amber Lin: Oh.

366 00:37:07.570 00:37:10.509 Emily Giant: Like, all of revenue and all of subscriptions.

367 00:37:10.660 00:37:13.220 Amber Lin: It’ll need to be done.

368 00:37:16.430 00:37:26.150 Emily Giant: They’re blocked by… All of the… Revenue tables not being done.

369 00:37:27.540 00:37:33.839 Emily Giant: And subscription tables not being finalized in… both dbt and Looker.

370 00:37:34.800 00:37:35.640 Amber Lin: Okay.

371 00:37:45.890 00:37:52.789 Amber Lin: Do you know roughly, like, how long it would take to recreate? Do you think, like, 2 or 3 hours each?

372 00:37:53.340 00:37:54.789 Emily Giant: Probably 2 hours.

373 00:37:54.920 00:37:55.930 Amber Lin: Max.

374 00:37:56.140 00:38:01.369 Emily Giant: Once… the fields are there. It’s super easy to recreate them.

375 00:38:01.370 00:38:02.779 Amber Lin: Okay.

376 00:38:03.590 00:38:10.080 Amber Lin: Oh… What’s these… And then…

377 00:38:14.480 00:38:15.960 Amber Lin: And for…

378 00:38:16.350 00:38:23.319 Emily Giant: Let me see if I can find a component dashboard, because that’s what’s been so broken. Component…

379 00:38:24.690 00:38:26.809 Emily Giant: Current week product here.

380 00:38:33.180 00:38:38.159 Emily Giant: Yeah, we should try to recreate this, like, for Perry’s QA.

381 00:38:38.880 00:38:42.669 Emily Giant: This is one of those areas that has just been a disaster.

382 00:38:45.800 00:38:47.240 Emily Giant: Since Shopify.

383 00:39:19.010 00:39:20.929 Amber Lin: Where do I add that?

384 00:39:21.740 00:39:24.540 Emily Giant: to SNOP revenue.

385 00:39:24.680 00:39:27.400 Emily Giant: For, like, QA or dashboards to rebuild.

386 00:39:28.460 00:39:29.860 Emily Giant: So it goes the same.

387 00:39:30.390 00:39:31.000 Emily Giant: Yeah.

388 00:39:31.000 00:39:34.489 Amber Lin: I’ll just add it to QA, because I don’t think we’re building the dashboards.

389 00:39:34.490 00:39:35.040 Emily Giant: Okay.

390 00:39:35.040 00:39:39.330 Amber Lin: Before… before Perry leaves, I think I’ll still take one.

391 00:39:39.330 00:39:47.619 Emily Giant: It’s possible. If revenue, if his ticket, Demolade’s ticket with the bundles and kits is done this week, then there’s really no blocker to that.

392 00:39:47.800 00:39:49.060 Amber Lin: Oh, okay.

393 00:39:49.060 00:39:49.710 Emily Giant: Yeah.

394 00:39:49.980 00:40:02.820 Emily Giant: I see, okay. S&OP, outside of subscriptions, which is the other huge problem with revenue, it’s really just that component kit level view that’s currently broken.

395 00:40:02.820 00:40:07.609 Amber Lin: And we don’t need to do… it would be great to do historicals with Perry, because she has such a good, like.

396 00:40:08.120 00:40:14.789 Emily Giant: historical knowledge, but she has documents on all of those that I can use as QA, so…

397 00:40:16.730 00:40:21.860 Emily Giant: just making sure the Shopify stuff is working the way we wanted it to is…

398 00:40:22.400 00:40:23.129 Amber Lin: What we should do.

399 00:40:23.130 00:40:23.990 Emily Giant: with her.

400 00:40:24.520 00:40:30.339 Amber Lin: Sorry, I… what is the requirement for this ticket that we’re queuing this dashboard?

401 00:40:31.450 00:40:37.790 Emily Giant: SNRPQA for Perry built Int, splint line items directory model for bundle overrides.

402 00:40:37.790 00:40:39.910 Amber Lin: Is this related to this ticket?

403 00:40:42.400 00:40:44.100 Amber Lin: No, no, right?

404 00:40:44.100 00:40:50.159 Emily Giant: I can’t see… sorry, all I see is that for SNOPQA, no, that one’s definitely related.

405 00:40:50.350 00:40:51.130 Amber Lin: Okay.

406 00:40:51.600 00:40:53.960 Emily Giant: That’s the components.

407 00:40:54.180 00:40:56.079 Emily Giant: Slash bundles kits.

408 00:40:57.650 00:41:00.800 Emily Giant: the ticket that Demolade’s working on right now.

409 00:41:03.590 00:41:08.359 Amber Lin: And then for this SONPQA, what are we trying to do?

410 00:41:08.710 00:41:12.020 Amber Lin: We are trying to.

411 00:41:12.020 00:41:20.109 Emily Giant: validate… that… revenue… in Looker.

412 00:41:23.350 00:41:38.449 Emily Giant: matches… revenue… in Shopify, As well as, making sure that bundles

413 00:41:40.260 00:41:44.309 Emily Giant: And kits are broken down correctly in revenue.

414 00:41:44.780 00:41:57.089 Emily Giant: Okay, that the components of bundles and kits are correct in revenue, and then lastly, that, and most importantly, that orders that were touched by care

415 00:41:57.450 00:42:00.350 Emily Giant: Are correctly documented in revenue data.

416 00:42:10.030 00:42:12.230 Amber Lin: Gotcha, so 3 points.

417 00:42:12.890 00:42:16.370 Amber Lin: for… Exceptions criteria.

418 00:42:16.810 00:42:23.729 Amber Lin: Okay, so that we would… seems like we want to do this week, or at least la- next week.

419 00:42:23.920 00:42:25.360 Emily Giant: Yes.

420 00:42:26.650 00:42:29.140 Amber Lin: for Perry QA.

421 00:42:35.880 00:42:39.479 Amber Lin: Alrighty, I’ll add that to this cycle.

422 00:42:52.390 00:43:03.000 Amber Lin: And then… we have some stuff… Like, where would… Goes into QA… Oh,

423 00:43:03.110 00:43:08.240 Amber Lin: For the skip, delays, and pause on subscriptions, what are we trying to do here?

424 00:43:09.000 00:43:18.870 Emily Giant: I think that’s done. It’s, correctly…

425 00:43:19.210 00:43:25.590 Emily Giant: We’re building a table that correctly documents Subscriptions that are not…

426 00:43:29.540 00:43:31.759 Emily Giant: Active, but are not canceled.

427 00:43:32.760 00:43:34.190 Emily Giant: And then, I think…

428 00:43:34.480 00:43:48.579 Emily Giant: that ticket specifically relates to a comment I made about the fact that Loop has a lot of different options when it comes to skipping, delaying, and pausing, and that we want to make sure

429 00:43:48.830 00:43:52.889 Emily Giant: That that’s correctly broken out in the table and not lumped together.

430 00:44:00.640 00:44:07.249 Emily Giant: Or maybe we want to lump it together. I think that’s, one of those questions that we just didn’t want to lose

431 00:44:08.030 00:44:11.359 Emily Giant: Site of when we were building out the new subscription tables.

432 00:44:12.120 00:44:15.830 Amber Lin: I see. We just created this ticket last week, is it…

433 00:44:16.310 00:44:19.279 Amber Lin: Confirm that it’s done, or how do we confirm that it’s done?

434 00:44:19.280 00:44:31.529 Emily Giant: And as I was talking, I don’t think that it’s done, but I would assign it to Utam, because he built out the tables, and this is just one of those, like, checkpoints of building the subscription tables.

435 00:44:32.900 00:44:38.999 Emily Giant: And he might assign… reassign it to me, but I just don’t want to, like… because it’s a nuance of loop.

436 00:44:39.240 00:44:47.149 Emily Giant: Don’t want to lose sight of the fact that these three, exactly the same, yet different in the interface, options exist.

437 00:44:48.040 00:44:50.760 Emily Giant: And they’re important because of forecasting, like.

438 00:44:51.440 00:44:57.140 Emily Giant: Skip may not have a start date for the next billing date, whereas cause…

439 00:44:57.390 00:45:06.950 Emily Giant: will have, like, a 3-6 month marker, whereas delay will have a specific date that the customer chose to restart, so that’s all gonna play into, like.

440 00:45:07.210 00:45:23.449 Emily Giant: forecasting, and if there is a next bill date missing, we need to use those elements to, like, build another column called, like, projected bill date, or something like that. But that’s why we were chatting through those three things.

441 00:45:24.650 00:45:28.050 Amber Lin: Gotcha. So, UTAM is helping you decide how or when.

442 00:45:28.760 00:45:29.110 Amber Lin: Ew?

443 00:45:29.110 00:45:32.450 Emily Giant: Yeah. He was designing the staging tables, so…

444 00:45:33.060 00:45:42.469 Emily Giant: If he wants to pass it back to me, that’s totally cool. He did the groundwork, but I think he was excited about doing this, so I also don’t want to, like…

445 00:45:43.330 00:45:51.049 Emily Giant: Take away his, His, whatever it’s called, the this about doing that task.

446 00:45:51.250 00:45:52.770 Amber Lin: Gotcha. Okay.

447 00:45:55.400 00:45:57.970 Amber Lin: And… is this walking anything?

448 00:45:59.220 00:46:06.540 Emily Giant: Yep, that would block rebuilding any of the Forecasting subscription dashboards.

449 00:46:19.270 00:46:20.630 Amber Lin: Gotcha, okay.

450 00:46:22.990 00:46:23.880 Amber Lin: That’s good.

451 00:46:25.130 00:46:35.830 Amber Lin: Japan U. Freight, that goes into… Subscriptions… What is this one?

452 00:46:37.910 00:46:45.779 Emily Giant: Oh, that’s a one-pointer. Oh, he already did that. He just needs to make a CSV in dbt for how,

453 00:46:46.240 00:46:52.140 Emily Giant: PK categorized the promo codes, for historical promos.

454 00:46:53.940 00:46:57.809 Emily Giant: Yeah, I would add to the ad promo seed.

455 00:46:58.170 00:47:10.230 Emily Giant: I would say, in addition to two Tableau Items XF, because we’re gonna kill that, so it’s like, we don’t want to add it to that. I would say 4 historical promo categorization.

456 00:47:16.180 00:47:22.230 Emily Giant: and maybe in parentheses, like, pre-Shopify… Promos.

457 00:47:31.690 00:47:36.380 Amber Lin: So, create and add free Shopify promo seeds for historical.

458 00:47:36.380 00:47:48.690 Emily Giant: And I think we should do that together during the working session, so that PK knows how to do it. It’s very easy. And it’s something that PK should learn how to do.

459 00:47:50.130 00:47:55.239 Emily Giant: So I’ll go ahead and add it to our, agenda and fellow for tomorrow.

460 00:47:56.780 00:47:59.410 Amber Lin: Awesome, so I will say this is…

461 00:47:59.410 00:48:00.980 Emily Giant: S389.

462 00:48:00.980 00:48:01.795 Amber Lin: Tomorrow…

463 00:48:23.530 00:48:24.410 Amber Lin: Alright.

464 00:48:27.040 00:48:31.769 Amber Lin: And is there any… we have…

465 00:48:31.960 00:48:35.820 Amber Lin: About 10 minutes left, or is any of these…

466 00:48:36.270 00:48:45.340 Amber Lin: Do you think we would not do, or do? We have never, like, groomed these. They were added when we made the project.

467 00:48:45.460 00:48:47.119 Emily Giant: Yes, they make me wanna…

468 00:48:47.280 00:49:05.909 Emily Giant: die, but, yeah, deprecation for existing rev-related tables. I think that at the end of all of this, if there is time, we should do every single one of these. If not, I would rather put our focus into building the tables. I know what needs to be deprecated. I’d rather, like.

469 00:49:06.090 00:49:14.990 Emily Giant: part ways with everything beautiful and perfect, but, like, it is not high priority. Kayo also did a lot of the work,

470 00:49:15.980 00:49:17.190 Emily Giant: So…

471 00:49:17.480 00:49:30.840 Emily Giant: in hindsight, I would say we should have always planned to do this at the end and not the beginning, so that, like, everything was there, and then we’re like, okay, we can trash this stuff for real, instead of, like, incrementally

472 00:49:31.220 00:49:32.800 Emily Giant: deprecating stuff.

473 00:49:33.070 00:49:37.129 Emily Giant: But yeah, we definitely should do it if we have time at the end.

474 00:49:37.130 00:49:37.840 Amber Lin: Tropic.

475 00:49:38.130 00:49:45.349 Amber Lin: So, the end… Cut over… Cut over plan?

476 00:49:46.450 00:49:53.140 Amber Lin: Who is… is this for… this is for the Urban Strems analysts, and so that they know what to do, right?

477 00:49:54.640 00:49:57.210 Emily Giant: Yeah, I mean, this, of all things.

478 00:49:57.230 00:50:15.260 Emily Giant: is something that we can probably not do. This is, like, a blanket statement for all the deprecation work, and we are doing it differently. There is no cutover. We’re doing this, like, very incrementally, especially with how everything’s getting added to Looker. I’m no longer doing a new model, because it’s…

479 00:50:15.850 00:50:21.879 Emily Giant: it… it would take… Far more work.

480 00:50:22.360 00:50:24.680 Amber Lin: It will be clean either way.

481 00:50:25.040 00:50:26.590 Amber Lin: Gotcha.

482 00:50:27.290 00:50:30.200 Amber Lin: Execute parallel run validation.

483 00:50:30.400 00:50:32.839 Amber Lin: This is just historicals, right?

484 00:50:33.290 00:50:45.120 Emily Giant: I have no idea what that is. Run side-by-side data comparison for revenue refunds. This is, again, one of those, like, checkpoints that should be done every time we release a model. It’s not its own task, so you could probably, like.

485 00:50:47.430 00:50:53.009 Amber Lin: Yeah, I would… yeah, you’re right. I’ll keep this, I’ll add it to historicals.

486 00:50:53.010 00:50:53.340 Emily Giant: Yeah.

487 00:50:53.340 00:50:58.290 Amber Lin: we check. Bye.

488 00:51:03.410 00:51:06.440 Amber Lin: Decommission legacy OMS models.

489 00:51:08.060 00:51:08.810 Emily Giant: Yep.

490 00:51:08.810 00:51:09.350 Amber Lin: Okay.

491 00:51:09.650 00:51:11.570 Emily Giant: Kill it once it’s all done.

492 00:51:12.330 00:51:14.239 Emily Giant: We can make a new list.

493 00:51:14.530 00:51:17.050 Emily Giant: A definitive list, and kill it.

494 00:51:17.220 00:51:17.900 Amber Lin: Hmm.

495 00:51:19.420 00:51:22.400 Amber Lin: Great. Make list, and kill.

496 00:51:26.230 00:51:28.849 Amber Lin: Archive… yeah, makes sense.

497 00:51:28.850 00:51:29.250 Emily Giant: Same.

498 00:51:29.250 00:51:30.100 Amber Lin: Sure.

499 00:51:30.790 00:51:33.130 Amber Lin: Mrs.

500 00:51:33.400 00:51:37.140 Amber Lin: So we have Marts, OMS, Looker…

501 00:51:37.320 00:51:42.120 Amber Lin: Then we have migrate… oops, migrate plan…

502 00:51:42.780 00:51:46.299 Amber Lin: Migration plans, move, dashboards, that’s the…

503 00:51:47.420 00:51:56.490 Amber Lin: Right, because I know we’re building some stuff for the teams to compare. There’s also new dashboards, and we can’t build everything for them.

504 00:51:56.490 00:52:04.140 Emily Giant: Right. We’re only gonna do, like, the net new stuff. Like, I would say for Northbeam.

505 00:52:04.410 00:52:14.379 Emily Giant: For loop, just giving stakeholders an example of what can be done, and the biggest one that I would put in is snapshot data.

506 00:52:14.530 00:52:23.860 Emily Giant: Like, make sure that we build snapshot dashboards so that they understand how to utilize that new stuff, because that’s what we’ve really been missing in the past.

507 00:52:25.110 00:52:28.510 Amber Lin: I’m sure I didn’t see the… Okay.

508 00:52:28.510 00:52:35.000 Emily Giant: If we did nothing but the snapshot data, I think that I would call that a worthwhile and complete ticket.

509 00:52:35.430 00:52:36.500 Amber Lin: Gotcha.

510 00:52:40.470 00:52:50.489 Amber Lin: And analysts can do… Replicate… In dash… towards renewed data.

511 00:52:51.330 00:53:00.710 Amber Lin: Demo dashboards… For a team to verify data accuracy.

512 00:53:01.340 00:53:02.260 Amber Lin: Okay.

513 00:53:05.100 00:53:05.930 Amber Lin: Alright.

514 00:53:09.170 00:53:11.300 Emily Giant: Look at us, we’re doing so good.

515 00:53:11.300 00:53:18.900 Amber Lin: Great, that’s all. Current cycle… Estimates…

516 00:53:20.970 00:53:24.229 Amber Lin: Huh. You think this would just take one point?

517 00:53:26.130 00:53:27.960 Emily Giant: Probably not, honestly.

518 00:53:28.210 00:53:28.705 Amber Lin: Oh…

519 00:53:31.240 00:53:36.980 Emily Giant: Cleanup deprecations? Oh, sure, yeah, sorry, I thought you meant, all of the other…

520 00:53:36.980 00:53:38.349 Amber Lin: Just to speak.

521 00:53:38.350 00:53:40.610 Emily Giant: We’re adding tags to everything.

522 00:53:40.910 00:53:54.660 Emily Giant: one point’s fine. One of the things that isn’t in here that I really want to talk through with the team is all of these Google Sheet upload things, and just doing a review of

523 00:53:55.240 00:53:59.789 Emily Giant: how we’re ingesting Google Sheets, and what the process is, so that

524 00:54:00.070 00:54:10.580 Emily Giant: I can get some ideas of how to streamline the process. Because what’s happening right now is that, like, every time there’s a new forecast, every time there’s a new holiday, there’s a new…

525 00:54:10.580 00:54:22.150 Emily Giant: spreadsheet that they want me to, like, set up in dbt, and then I have to write code, and it’s always the same code over and over and over again through the years when it, like, it’s all the same information, nothing’s changed.

526 00:54:22.150 00:54:26.629 Emily Giant: So, I… I… Don’t know if there’s a way to, like…

527 00:54:26.970 00:54:33.509 Emily Giant: or some program that UTAM knows about, where they can, like, enter forecasting stuff, but I would love for this to be…

528 00:54:33.740 00:54:49.380 Amber Lin: going to be… if it’s ingestion, I think they… which can help you look at if we can use Daxter, because then it’s… I do think it’s helping with automating the data flows of ingestions and stuff. Okay.

529 00:54:49.490 00:54:56.379 Emily Giant: And that’s fine, I think… Just, like, updating the process in an official way, so that…

530 00:54:56.580 00:55:02.850 Emily Giant: we don’t have to build a new table every time there’s a new Google Sheet that has the same information it did for the.

531 00:55:02.850 00:55:05.340 Amber Lin: Is it just for forecasting, or just…

532 00:55:05.340 00:55:08.869 Emily Giant: It’s for Comp… Forecast Comp.

533 00:55:09.110 00:55:11.340 Emily Giant: to… actuals.

534 00:55:14.650 00:55:15.630 Amber Lin: Compare.

535 00:55:17.000 00:55:24.740 Emily Giant: And then I’ll give you, like, an example folder, so that if it’s not me working on it, everyone knows what I’m talking about.

536 00:55:35.180 00:55:41.919 Emily Giant: there’s a whole Google Sheets folder. Anything in that Google Sheets folder is like, what are we doing here, people?

537 00:55:42.100 00:55:49.910 Emily Giant: holidays. So, I’ll send this to you in the chat, so that you don’t have to, like… Google Sheets.

538 00:55:56.140 00:55:57.910 Amber Lin: Is that the delivery?

539 00:55:58.150 00:55:59.420 Amber Lin: Oh.

540 00:55:59.790 00:56:00.910 Emily Giant: in dbt.

541 00:56:07.040 00:56:14.360 Amber Lin: Gotcha. So you want to standardize the workflow in dbt, or how we create that in dbt?

542 00:56:14.360 00:56:16.100 Emily Giant: Yeah, standardized forecasts.

543 00:56:16.800 00:56:25.310 Emily Giant: Into a single… Persisting spreadsheet, instead of making new ones.

544 00:56:28.130 00:56:30.779 Emily Giant: Or something else.

545 00:56:30.920 00:56:35.459 Emily Giant: if Utam or Oish or Demolati know about, like.

546 00:56:35.830 00:56:39.710 Emily Giant: a program that isn’t Google Sheets, that’s

547 00:56:40.500 00:56:47.720 Emily Giant: easily ingested, easier to upkeep, less user error. The problem with Google Sheets is the user error is just.

548 00:56:47.720 00:56:48.330 Amber Lin: It’s like…

549 00:56:49.700 00:56:51.980 Emily Giant: like, one day, Perry changed.

550 00:56:52.390 00:56:57.879 Emily Giant: The name of a column, and it broke all of her reports, and we didn’t know why for, like, 4 hours.

551 00:56:57.880 00:56:58.490 Amber Lin: Yeah.

552 00:56:58.490 00:57:06.210 Emily Giant: So just little things like that, that I’m like, I know that these guys have so much experience, and I’m just, like, herding cats.

553 00:57:08.520 00:57:11.429 Emily Giant: I mean, I love cats. Herding cats is my dream job, but…

554 00:57:11.430 00:57:12.290 Amber Lin: Book of action.

555 00:57:12.290 00:57:13.019 Emily Giant: Oh, cats.

556 00:57:14.830 00:57:17.170 Amber Lin: Standardized…

557 00:57:22.300 00:57:24.250 Amber Lin: I don’t know how to name this ticket?

558 00:57:39.420 00:57:47.049 Amber Lin: We will… we can discuss that. Do you want to ask at stand-up tomorrow?

559 00:57:49.330 00:57:50.649 Emily Giant: Yeah.

560 00:57:51.250 00:57:52.920 Amber Lin: Yeah, okay.

561 00:57:52.920 00:57:54.830 Emily Giant: Where are you? Are you gonna go on vacation?

562 00:57:54.830 00:58:00.410 Amber Lin: My family is here, so I’m just gonna go around. It’s their vacation? Because they’re coming to LA.

563 00:58:00.410 00:58:04.390 Emily Giant: Great. I’m so glad you’re taking time off. You work way too much.

564 00:58:05.330 00:58:06.340 Amber Lin: You too.

565 00:58:06.550 00:58:07.570 Amber Lin: Thank you.

566 00:58:07.570 00:58:14.330 Emily Giant: I’m trying to be better about it. I got back from my trip, I’m, like, trying to stop working at 6. Do not start working until 8.

567 00:58:14.330 00:58:16.020 Amber Lin: It’s just really late.

568 00:58:16.330 00:58:17.860 Amber Lin: Sex is really late.

569 00:58:17.860 00:58:25.119 Emily Giant: It’s so much better. It’s so much better than what I was doing, but we’re in a better spot, too, so…

570 00:58:26.200 00:58:36.769 Emily Giant: Yeah, things aren’t, like, knock on wood, actively broken. There was stuff broken when I was staying up all night, and those are not broken anymore. Knock on wood, so…

571 00:58:37.290 00:58:41.629 Amber Lin: Whew! Who will be doing this one that we just created today?

572 00:58:43.010 00:58:45.370 Emily Giant: Either myself or Utam.

573 00:58:45.490 00:58:46.220 Amber Lin: Okay.

574 00:58:46.880 00:58:49.579 Emily Giant: It just depends on if he wants to do it or not.

575 00:58:50.140 00:58:54.300 Amber Lin: Don’t think he will want to, he just does not have any time right now.

576 00:58:54.300 00:58:55.420 Emily Giant: Okay.

577 00:58:55.710 00:58:56.060 Emily Giant: Nice.

578 00:58:56.060 00:58:57.089 Amber Lin: I’m super concerned.

579 00:58:57.090 00:59:09.189 Emily Giant: You can assign it to me, but… and, like, I know how to do it, it’s okay. He just was like, I want to do it last time. I think he just wanted to practice with cursor, so… yeah. You can totally assign that to me, it’s fine.

580 00:59:09.190 00:59:20.490 Amber Lin: Okay, great. Let’s look at your points. Is this reasonable for this cycle? It’s already 15 hours of work.

581 00:59:20.610 00:59:22.770 Emily Giant: Does it end on Friday?

582 00:59:23.340 00:59:27.770 Amber Lin: Yeah. I just… I made it into Monday because it was so hard to plan.

583 00:59:27.940 00:59:30.889 Amber Lin: When it was Tuesday to Friday.

584 00:59:31.730 00:59:33.830 Amber Lin: Tuesday to Tuesday, Monday.

585 00:59:35.350 00:59:40.610 Emily Giant: Definitely not gonna do 405. The sprint. Kick that one out.

586 00:59:45.300 00:59:50.390 Emily Giant: I would say, realistically, kick out 296.

587 00:59:51.820 00:59:53.790 Emily Giant: And then I can do the rest of these.

588 00:59:54.120 00:59:55.429 Amber Lin: Yeah.

589 00:59:56.210 00:59:56.740 Emily Giant: Yeah, this.

590 00:59:56.740 01:00:00.950 Amber Lin: We already have enough explorers to play with. Yeah.

591 01:00:01.360 01:00:03.940 Emily Giant: Technically, fax subscriptions is done.

592 01:00:04.720 01:00:08.340 Emily Giant: that one, I’m just waiting on UTAM to deploy.

593 01:00:08.830 01:00:13.019 Emily Giant: the PR, so really all I have to do is transactions.

594 01:00:13.020 01:00:18.510 Amber Lin: Fields not working, historicals, and fact line items, which I’m pretty sure is done.

595 01:00:18.510 01:00:20.290 Emily Giant: I just need to double check it.

596 01:00:21.020 01:00:22.290 Amber Lin: Gotcha. Okay.

597 01:00:22.290 01:00:24.300 Emily Giant: So it really isn’t as bad as it looks.

598 01:00:24.550 01:00:29.059 Amber Lin: Yeah, that’s awesome, and then… We’ll do that.

599 01:00:29.530 01:00:31.390 Amber Lin: Does he have to do this?

600 01:00:31.650 01:00:34.189 Amber Lin: Actually, oh yeah, I remember, we need to consult.

601 01:00:34.460 01:00:37.810 Emily Giant: consult, but you can add it to mine. And those are…

602 01:00:39.090 01:00:43.930 Emily Giant: Nevermind. It is totally different. You can add that to me, though, and I’ll just ask him.

603 01:00:47.510 01:00:58.329 Emily Giant: And I will try to get that done by Friday, and I’ll, like, I’ll… at stand-up tomorrow, I know you’re gone. I’ll change it tomorrow, if I haven’t gotten further with my other ones.

604 01:00:58.330 01:00:59.440 Amber Lin: Okay.

605 01:00:59.650 01:01:04.130 Amber Lin: Would you mind just sending that message right now? I think we’re done with all the other stuff.

606 01:01:05.900 01:01:06.940 Emily Giant: Do a what?

607 01:01:06.940 01:01:12.090 Amber Lin: I’ll just pinged Utam about the skip, delay, pause. Yep, yep, yep.

608 01:01:13.700 01:01:14.640 Amber Lin: Alright.

609 01:01:15.520 01:01:16.810 Amber Lin: Sounds good.

610 01:01:16.810 01:01:19.320 Emily Giant: Okay, cool. Thanks, I’m glad we did this.

611 01:01:19.320 01:01:20.960 Amber Lin: Yeah, thank you so much.

612 01:01:20.960 01:01:25.829 Emily Giant: Okay, enjoy your family, and don’t answer any emails, no matter.

613 01:01:25.830 01:01:29.180 Amber Lin: It’s gonna be so hard.

614 01:01:29.180 01:01:32.580 Emily Giant: gonna love it. It’s gonna be her the first day, and then you’re gonna love it.

615 01:01:32.840 01:01:33.630 Amber Lin: Okay.

616 01:01:33.630 01:01:35.229 Emily Giant: Alright, I’ll talk to you later.

617 01:01:35.230 01:01:36.270 Amber Lin: Alrighty, bye-bye.

618 01:01:36.270 01:01:36.930 Emily Giant: Bye.