Meeting Title: Robert Tseng’s Zoom Meeting Date: 2025-02-06 Meeting participants: Robert Tseng, Luke Daque, Awaish Kumar


WEBVTT

1 00:01:15.030 00:01:15.510 Luke Daque: Hi Robert!

2 00:01:15.997 00:01:17.460 Robert Tseng: How’s it going?

3 00:01:18.370 00:01:19.860 Robert Tseng: Good! How are you.

4 00:01:20.350 00:01:21.619 Luke Daque: Yeah, doing? Well.

5 00:01:26.606 00:01:30.759 Robert Tseng: Yeah, I just, I think who comes meeting is being used so.

6 00:01:31.100 00:01:35.649 Luke Daque: Yeah, he did mention earlier that he’s he has like a client meeting

7 00:01:35.880 00:01:39.310 Luke Daque: in person. So he might be, yeah, like

8 00:01:41.270 00:01:45.499 Luke Daque: he might be not. He might not be able to join the meeting. Basically.

9 00:01:46.040 00:01:47.210 Robert Tseng: Okay, no worries.

10 00:01:53.250 00:01:57.329 Robert Tseng: Have the past couple of weeks been for you. You feel like it’s more manageable now.

11 00:01:58.540 00:02:00.340 Luke Daque: Yeah, it’s pretty fine.

12 00:02:00.910 00:02:05.540 Luke Daque: yeah, I’m currently like, focusing on Stat Blitz, like, new data models and stuff.

13 00:02:05.830 00:02:06.660 Robert Tseng: Okay.

14 00:02:07.400 00:02:11.879 Luke Daque: Yeah about you. I I heard. It’s like pretty rough with Eden and stuff. But.

15 00:02:12.460 00:02:22.040 Robert Tseng: Yeah, I think it may get to a point where we might just not

16 00:02:22.560 00:02:31.720 Robert Tseng: continue with them. I just feel like the well, it’s I think we’re

17 00:02:32.000 00:02:34.729 Robert Tseng: we’re not really able to deliver like

18 00:02:35.430 00:02:39.740 Robert Tseng: things that. Well, so I think things have been kind of tense.

19 00:02:40.330 00:02:43.029 Robert Tseng: yeah, we’re still like working on some

20 00:02:43.260 00:02:46.719 Robert Tseng: modeling that was supposed to be done 2 weeks ago. So

21 00:02:46.950 00:02:52.409 Robert Tseng: which is fine, we’ve made progress. And it’s a hard problem. It’s a it is a hard problem, but it’s just

22 00:02:53.240 00:03:06.260 Robert Tseng: Yeah, it’s taken up a lot of my time. And we, Tom, had to jump in to help, too, so I don’t know. Well, I don’t know if it makes sense to. If we keep doing it. If it doesn’t get better, then.

23 00:03:06.480 00:03:12.839 Robert Tseng: you know we’re we’re not able to support the other clients we have, too. So that’s like not.

24 00:03:13.250 00:03:17.809 Luke Daque: I guess, like the effort we’re doing too much effort for like

25 00:03:18.090 00:03:21.290 Luke Daque: very little reward, or something right like.

26 00:03:21.290 00:03:23.179 Robert Tseng: Yeah, yeah, the reward.

27 00:03:23.310 00:03:31.409 Robert Tseng: Utah and I disagree on like, I think the reward is high, like, I do think we can go higher. We can get higher from them, but he

28 00:03:31.810 00:03:35.149 Robert Tseng: may not agree with me, so we’ll see.

29 00:03:35.280 00:03:36.060 Robert Tseng: Yeah,

30 00:03:37.610 00:03:41.150 Luke Daque: Just like too much effort, I guess. At the moment at least.

31 00:03:41.150 00:03:45.470 Robert Tseng: It is. Yeah. So I mean, we’re, we’re we’re trying to like.

32 00:03:46.460 00:03:56.470 Robert Tseng: yeah, we’re trying to hire right? And we’re trying to like, get more people that on board to help. I think there’s been a lot of people rotating in and out of clients. So that’s that’s also been hard to expect

33 00:03:56.770 00:04:00.410 Robert Tseng: people that jump in and then just pick up with no context. So

34 00:04:00.810 00:04:03.460 Robert Tseng: we’re we’re working through it. But yeah.

35 00:04:04.440 00:04:05.030 Luke Daque: Cool.

36 00:04:07.420 00:04:17.220 Robert Tseng: Well cool, I mean, I guess we’ll just. We’ll just chat a bit, and then I guess if you wanna keep keep going. It’s cool. Let me let me pull up. So you got stacked lists right now.

37 00:04:18.810 00:04:27.019 Robert Tseng: yeah, I know I’m not like I’m not really active on this client. But let me just kind of go through the things that are going on. So we have the

38 00:04:27.763 00:04:29.049 Robert Tseng: I guess

39 00:04:29.360 00:04:34.479 Robert Tseng: I have the tickets pulled up. I’ll just. I’ll just share my screen, and then we can. Kinda

40 00:04:35.190 00:04:35.790 Robert Tseng: I agree.

41 00:04:35.790 00:04:41.810 Luke Daque: Yeah, I’ve assigned, like all of the tickets to me, especially those that were initially assigned Tom.

42 00:04:42.508 00:04:46.449 Luke Daque: So I can like monitor everything as well and basically like, own

43 00:04:46.760 00:04:49.960 Luke Daque: the data part of this project as much as possible. So.

44 00:04:50.510 00:04:50.900 Robert Tseng: Okay.

45 00:04:50.900 00:04:59.400 Luke Daque: But yeah, it looks like there’s still a lot that’s still assigned to Utam. Yeah, I’ll have to add my name to those like Hubspot to snowflake

46 00:05:00.460 00:05:03.619 Luke Daque: postgres, Cdc, and and stuff like that. So yeah.

47 00:05:03.620 00:05:07.080 Robert Tseng: Looks like a lot of this is done. Maybe we just talk through like.

48 00:05:07.380 00:05:07.909 Luke Daque: Oh, yeah.

49 00:05:07.910 00:05:11.539 Robert Tseng: Review. So if we need to change due date. So like

50 00:05:11.670 00:05:15.899 Robert Tseng: initializing real stripe data, I I saw some messaging around that I think that’s done right.

51 00:05:16.387 00:05:18.525 Luke Daque: Yeah, that’s done. But I think we’ll have a

52 00:05:19.540 00:05:24.251 Luke Daque: We’ll have a call with Mitch tomorrow, so we can like discuss this with him as well. And like,

53 00:05:24.740 00:05:27.534 Luke Daque: yeah, like, get get some feedback.

54 00:05:28.380 00:05:29.610 Luke Daque: So yeah.

55 00:05:30.070 00:05:32.617 Robert Tseng: We were having trouble with the appointment anymore. Right? So it’s just

56 00:05:32.830 00:05:34.580 Luke Daque: Not anymore. Yeah, we can remove that.

57 00:05:35.750 00:05:39.970 Robert Tseng: Demo which demo on.

58 00:05:40.840 00:05:41.400 Luke Daque: Yep.

59 00:05:42.620 00:05:43.430 Robert Tseng: Hey!

60 00:05:45.680 00:05:53.330 Luke Daque: I guess all of the things that are in Solutions Review would be like for Mitch Demo tomorrow, and, like Mitch, is

61 00:05:53.580 00:06:02.610 Luke Daque: oh, off today, like he’s out of office. I did try to send him a message in the Channel. But I got an auto reply that he’s out of office.

62 00:06:03.405 00:06:06.737 Luke Daque: Yeah, yeah, there’s still a couple of things like,

63 00:06:08.137 00:06:13.820 Luke Daque: the def in development there, like the user and organizations data modeling.

64 00:06:14.400 00:06:18.929 Luke Daque: those are in progress. I already have a Pr for for those.

65 00:06:19.470 00:06:19.800 Robert Tseng: Okay.

66 00:06:21.280 00:06:22.530 Luke Daque: But yeah, there’s still a lot of.

67 00:06:22.530 00:06:23.549 Robert Tseng: For tomorrow.

68 00:06:24.260 00:06:25.370 Luke Daque: Yeah, we can, yeah.

69 00:06:25.690 00:06:26.010 Robert Tseng: Perfect.

70 00:06:26.010 00:06:26.890 Luke Daque: Today.

71 00:06:27.130 00:06:35.219 Luke Daque: Yeah, that’s also like for discussion with Mitch tomorrow, especially like the logic that needs to be

72 00:06:35.560 00:06:39.040 Luke Daque: verified and and stuff like that or other fields that

73 00:06:39.170 00:06:45.730 Luke Daque: might be coming from different sources other than postgres and stuff like that. So yeah.

74 00:06:46.200 00:06:46.940 Robert Tseng: Okay.

75 00:06:47.090 00:06:47.460 Luke Daque: That’s for.

76 00:06:47.460 00:06:56.091 Luke Daque: What about this architecture diagram, that one? I haven’t started that yet, but that’s the one where?

77 00:06:57.960 00:07:00.190 Luke Daque: yeah, that’s that’s like in Figma.

78 00:07:01.370 00:07:04.580 Luke Daque: showing, like the sources, all the data sources, all the

79 00:07:04.730 00:07:08.350 Luke Daque: data models, and like dashboards and stuff like that.

80 00:07:09.520 00:07:16.770 Robert Tseng: Okay, I mean, this is, yeah. If you’re working on that, I mean, I would like that for other clients, too. So that’d be good to see how you’re doing that.

81 00:07:17.100 00:07:17.670 Luke Daque: Yeah, I think.

82 00:07:17.670 00:07:23.631 Luke Daque: Think of Who’s the what? I can’t pronounce his name? What

83 00:07:24.090 00:07:24.740 Robert Tseng: Oh, wait!

84 00:07:24.900 00:07:35.140 Luke Daque: Aisha. A wish is also working on that for both pool parts, and I believe Eden even.

85 00:07:35.430 00:07:37.009 Robert Tseng: Okay, are you?

86 00:07:37.010 00:07:39.670 Robert Tseng: Are you? Are you still on Javi? Or you’re just right now.

87 00:07:39.670 00:07:45.390 Luke Daque: Oh, Javi, it’s Javi! Actually, I’m I’m with Javi and Statlitz.

88 00:07:46.190 00:07:48.100 Luke Daque: Pull pull parts and stack bits. It’s.

89 00:07:48.100 00:07:48.490 Robert Tseng: You’re pulling.

90 00:07:48.490 00:07:50.750 Luke Daque: I wish it’s doing, Javi and

91 00:07:52.430 00:07:53.240 Luke Daque: You didn’t.

92 00:07:53.750 00:07:58.230 Robert Tseng: Okay, cool? Then. So I’ll move this to what like next week.

93 00:07:58.950 00:08:01.129 Luke Daque: Yeah, let’s do next week. Let’s do Monday.

94 00:08:01.691 00:08:03.649 Robert Tseng: Okay, yeah, we’ll move. Monday.

95 00:08:05.370 00:08:07.859 Robert Tseng: Okay, cool. I think that should be clear.

96 00:08:08.270 00:08:11.720 Robert Tseng: Let’s I mean, we can check through pool parts a bit here, too.

97 00:08:12.255 00:08:17.029 Robert Tseng: I think a wish has been messaging me, so let me just make sure if he wants to.

98 00:08:17.750 00:08:20.899 Luke Daque: Yeah, he might be like trying to join the meeting or something.

99 00:08:29.240 00:08:30.350 Robert Tseng: I think

100 00:08:36.770 00:08:41.569 Robert Tseng: he’s actually asking utam some questions, but I’m gonna just tell him to jump on this call.

101 00:08:42.210 00:08:42.880 Luke Daque: Okay.

102 00:08:43.669 00:08:45.629 Robert Tseng: Let me see if you can. Yeah.

103 00:08:53.569 00:08:54.729 Robert Tseng: oops. That’s not.

104 00:08:55.480 00:09:01.379 Luke Daque: Yeah, it looks like a wish has already created one for Eden, like the

105 00:09:01.630 00:09:06.060 Luke Daque: data architecture stuff. But there’s still things to update.

106 00:09:08.670 00:09:10.319 Luke Daque: I can show it real quick.

107 00:09:17.850 00:09:25.400 Luke Daque: So basically something like this, where it shows like our whole architecture from all the data sources

108 00:09:26.666 00:09:32.208 Luke Daque: what to we’re using to ingest. And we’ll be adding stuff here as well, like,

109 00:09:33.050 00:09:34.680 Luke Daque: like the details on that.

110 00:09:36.170 00:09:43.490 Luke Daque: Yeah, the data where else they’re using like the data models. And if there are any visualization tools

111 00:09:43.610 00:09:46.900 Luke Daque: that we’re using our like dashboards and stuff.

112 00:09:48.710 00:09:52.160 Luke Daque: and they’re still like Utah has, like some comments in here like

113 00:09:52.310 00:09:57.250 Luke Daque: how often the data is synced. We can add stuff. This is for poor Javi.

114 00:09:58.010 00:10:01.843 Luke Daque: And then, yeah, no, no.

115 00:10:03.030 00:10:08.200 Robert Tseng: Hey? Wish? Yeah. Sorry. The data team meeting link is not

116 00:10:08.400 00:10:11.390 Robert Tseng: Utah. I’m still using that meeting. So I opened a different link

117 00:10:12.289 00:10:19.280 Robert Tseng: I saw I saw you were asking some questions. Maybe maybe even I think maybe Luke can help you as well like, kind of deploy dbt stuff. But

118 00:10:20.260 00:10:23.479 Robert Tseng: yeah, we’re just going through the tickets right now is that if

119 00:10:23.620 00:10:25.609 Robert Tseng: you’re able, you’re able to join for this.

120 00:10:27.762 00:10:29.330 Awaish Kumar: Yeah. So actually, I

121 00:10:29.750 00:10:35.149 Awaish Kumar: pushed both the changes you asked for. So I just wanted to run that model again

122 00:10:35.460 00:10:36.949 Awaish Kumar: and see the result.

123 00:10:39.050 00:10:39.900 Robert Tseng: Okay.

124 00:10:41.084 00:10:47.580 Robert Tseng: Yeah, maybe we’ll we’ll chat about it towards the end. We’re kind of going through pool parts right now and then we’ll and then we’ll go to Eden joby

125 00:10:48.225 00:10:52.359 Robert Tseng: so I guess yeah, Luke, you wanna we’ll we’ll just kind of finish up here.

126 00:10:52.630 00:11:00.480 Luke Daque: I don’t think there’s any like data modeling happening on pool parts, at least like for for this week I have. There’s nothing assigned to me for this week.

127 00:11:00.810 00:11:04.859 Robert Tseng: Okay, it’s just an architecture diagram, and maybe I’ll just put that Monday as well.

128 00:11:04.860 00:11:05.940 Luke Daque: Yeah, yeah.

129 00:11:10.790 00:11:16.120 Robert Tseng: This is the same thing. This is not, for this is supposed to be for Joby, not bullhorns.

130 00:11:17.655 00:11:18.109 Luke Daque: Yeah.

131 00:11:20.740 00:11:22.060 Robert Tseng: Okay, cool.

132 00:11:22.360 00:11:23.760 Robert Tseng: And then.

133 00:11:27.030 00:11:32.219 Robert Tseng: yeah, I guess I don’t know if you want to give me any other like.

134 00:11:32.960 00:11:43.229 Robert Tseng: what do you? Are you waiting on anything with with pious I know I’m not usually kind of like pushing on full parts. But let me just like let me know if there’s anything.

135 00:11:44.170 00:11:47.579 Luke Daque: At the moment. There’s nothing for for me like, for

136 00:11:47.750 00:11:50.439 Luke Daque: between by us and me, for pool parts. Yeah.

137 00:11:50.800 00:11:53.939 Luke Daque: Okay, I think. Yes, like, there’s still a lot of things that

138 00:11:55.128 00:11:57.040 Luke Daque: pay us is doing as well.

139 00:11:57.040 00:11:59.549 Robert Tseng: Yeah, I think he’s yeah. Got it.

140 00:11:59.860 00:12:09.850 Robert Tseng: Okay, cool? Well, that’s that’s clear. Thanks. Thanks, Luke. I mean, you feel free to stay on, or you don’t. You don’t have to. I can just move on to Javi and Eden with a wish.

141 00:12:10.260 00:12:11.560 Luke Daque: Sure I can stay.

142 00:12:11.560 00:12:12.330 Robert Tseng: Okay.

143 00:12:12.820 00:12:26.000 Robert Tseng: Alright wish I guess, since you were talking about Eden, let’s just talk about Eden. I know that these are not really relevant to the tickets themselves. But we you kind of mentioned you pushed a couple of changes. Let me. Just

144 00:12:26.280 00:12:33.060 Robert Tseng: I think one change was the ad spend thing, and then the other one was

145 00:12:33.440 00:12:39.000 Robert Tseng: cogs right? What? What was? What was the change on ad spend? How did we? How do we resolve that

146 00:12:44.750 00:12:47.080 Robert Tseng: sorry wish. Maybe you’re muted. I can’t hear you.

147 00:12:49.740 00:12:52.550 Awaish Kumar: So in the query in our rejects

148 00:12:52.670 00:12:55.369 Awaish Kumar: we were missing out on campaigns for some

149 00:12:55.893 00:13:02.049 Awaish Kumar: I don’t know, because of the ordering of our ax, so I just moved it on the top and added it

150 00:13:02.340 00:13:06.209 Awaish Kumar: another filter also. So now we are catching all 3.

151 00:13:06.800 00:13:09.719 Robert Tseng: Okay, did. Did you see the previous?

152 00:13:11.100 00:13:16.009 Robert Tseng: Did you see the previous Regex? And there’s like a hierarchy that it’s like, look at the ad.

153 00:13:16.170 00:13:24.460 Robert Tseng: and then, if it’s not in the ad, look at the ad set, if it’s not the ad set, look at campaign like. That’s how we had structured it before, did you? Did you? Did you? Did you see that.

154 00:13:26.410 00:13:33.250 Awaish Kumar: Oh, no, I mean for the like the campaign name, if it is us

155 00:13:33.550 00:13:39.439 Awaish Kumar: like the if the string contains Sirmoline, then it’s a summerline. Right? It’s not another. Any other product.

156 00:13:41.240 00:13:45.719 Robert Tseng: Alright. Let me share my screen.

157 00:13:51.190 00:13:54.990 Robert Tseng: Okay, alright, it’s like a lot going on here.

158 00:13:58.010 00:14:04.159 Robert Tseng: Yeah. So this is from the north beam export. This is like the the ad, like

159 00:14:05.980 00:14:14.940 Robert Tseng: the North B models, like the add data modeling that went through this like Regex hierarchy to associate

160 00:14:15.583 00:14:21.440 Robert Tseng: or like, yeah, it’s basically associate ads with

161 00:14:21.790 00:14:35.439 Robert Tseng: with a with product names. Right? So this is like, I, kinda this is what I meant by, like, I had checked this before, and so like I thought that we were catching some more Lynn, like in the same way. And so your change isn’t really.

162 00:14:35.440 00:14:41.539 Awaish Kumar: This is the okay. So we have not changed anything here in our summary query.

163 00:14:41.790 00:14:46.150 Awaish Kumar: where we are getting the product name from campaign name.

164 00:14:49.650 00:14:50.360 Robert Tseng: Yep.

165 00:14:51.730 00:14:54.790 Robert Tseng: Well, okay, yeah. So some more, Lynn, if you’re here.

166 00:14:56.670 00:14:58.349 Robert Tseng: maybe I didn’t update this. But

167 00:14:59.530 00:15:02.609 Robert Tseng: like we, we were missing something here. Is that what you’re saying?

168 00:15:03.490 00:15:05.550 Awaish Kumar: No, no. If you open the

169 00:15:07.740 00:15:12.060 Awaish Kumar: summary product sales summary. Yeah.

170 00:15:12.430 00:15:13.660 Awaish Kumar: In here.

171 00:15:15.600 00:15:16.310 Robert Tseng: Yeah.

172 00:15:17.980 00:15:19.730 Awaish Kumar: If you go to campaign.

173 00:15:22.830 00:15:26.460 Awaish Kumar: These are product name. Now that let’s go to campaign names.

174 00:15:27.720 00:15:29.100 Robert Tseng: Campaign, name.

175 00:15:29.100 00:15:30.390 Awaish Kumar: Scroll down.

176 00:15:30.950 00:15:36.270 Robert Tseng: Keep scrolling like here, final metrics. Nope, these are product names.

177 00:15:37.060 00:15:41.050 Awaish Kumar: But we have a man. I’m same names.

178 00:15:41.340 00:15:45.340 Robert Tseng: Oh, this is prod, and we’re this is, we’re still talking about staging. Huh?

179 00:15:46.000 00:15:49.899 Robert Tseng: Damn it! Okay, da da da da.

180 00:15:55.390 00:15:59.200 Awaish Kumar: Yeah, not in the main branch. We are

181 00:16:00.010 00:16:02.680 Awaish Kumar: that these changes are not merged yet. Right.

182 00:16:03.250 00:16:10.669 Robert Tseng: Yeah. Okay. Well, then, I guess I I was. I was trying to like visualize like what you’re talking about. But I’m not. I’m not.

183 00:16:10.670 00:16:11.909 Awaish Kumar: Can show you what.

184 00:16:11.910 00:16:12.560 Robert Tseng: Okay.

185 00:16:20.180 00:16:23.720 Awaish Kumar: Yep, you you can like. These changes are pushed in the

186 00:16:24.790 00:16:27.850 Awaish Kumar: sales summary branch, which is open by utham.

187 00:16:28.290 00:16:29.550 Robert Tseng: Yep, I see that.

188 00:16:29.550 00:16:30.490 Awaish Kumar: On video.

189 00:16:30.730 00:16:34.240 Awaish Kumar: So if we if we see that we are

190 00:16:34.750 00:16:37.159 Awaish Kumar: and we can see the changes made.

191 00:16:38.940 00:16:40.150 Robert Tseng: Okay.

192 00:16:43.240 00:16:48.940 Robert Tseng: yeah. Okay. See it, fixed campaign names.

193 00:16:51.030 00:16:53.570 Awaish Kumar: Last commit I have made.

194 00:16:54.860 00:16:56.230 Robert Tseng: Yeah, we’re talking about this.

195 00:16:56.730 00:16:59.500 Robert Tseng: So yeah.

196 00:17:11.750 00:17:21.670 Robert Tseng: interesting. So in our date spine, we were not capturing the product name. We only had campaign name.

197 00:17:23.440 00:17:28.120 Robert Tseng: And then we added this to this one, okay, got it.

198 00:17:30.790 00:17:35.569 Robert Tseng: Wouldn’t that mean we would need to do this for every other product name as well

199 00:17:38.350 00:17:43.590 Robert Tseng: like. I see you did it for Sema, for Tours, for cerm, but like also.

200 00:17:43.940 00:17:53.919 Awaish Kumar: It. It was like that for others. So I added, so it was already happening for campaign names. So I just added them for product name as well.

201 00:17:56.520 00:18:05.139 Robert Tseng: Okay. But I’m saying like, if that’s the case, then wouldn’t we need to do it across all of the pro. I mean, I’m just trying to understand, like, when we need to do this for all products.

202 00:18:05.140 00:18:08.920 Awaish Kumar: 3 right now, right now, we don’t have any example

203 00:18:09.502 00:18:16.289 Awaish Kumar: which we can use right? So we don’t know the what is the term. Which will you uniquely identify? So for us? For some

204 00:18:16.390 00:18:23.729 Awaish Kumar: I can see that, like the in the campaign. If there’s a sum, then it is attributed to some it’s correctly attributing.

205 00:18:23.980 00:18:25.089 Awaish Kumar: So it’s okay

206 00:18:25.520 00:18:31.260 Awaish Kumar: for the all the products. We don’t have any such examples right now. So we can like add

207 00:18:31.820 00:18:36.539 Awaish Kumar: can incrementally update it whenever we see use cases, right?

208 00:18:38.900 00:18:39.780 Robert Tseng: I see.

209 00:18:41.400 00:18:54.100 Robert Tseng: Okay? Well, I mean, I just, I feel like we should go and figure out what those use cases are like. We should, we should know, like every possible product name that comes in. And if it’s not being caught by our rejects, then we need to have something like that like

210 00:18:54.330 00:18:56.380 Robert Tseng: I don’t like. I don’t wanna be.

211 00:18:56.380 00:19:01.930 Awaish Kumar: Yeah. But in in our table, right? You know, we have to have the data in our table

212 00:19:02.060 00:19:05.519 Awaish Kumar: to verify what we are writing in the code.

213 00:19:07.120 00:19:17.249 Robert Tseng: Yeah, okay, so you’re saying, just for the current data that we do have, this is like what we’ve got. We’ve we’ve covered right? Cause. Like I basically, I went. I I showed the new like, dash

214 00:19:17.400 00:19:31.990 Robert Tseng: forward to the team, and they’re like some more lens off. And I I can’t just like I mean, I don’t want to keep showing things. And then people like point out like this is wrong or whatever. And so I’m trying to be more thorough and like

215 00:19:32.300 00:19:40.779 Robert Tseng: making sure that we’re not going to get called out for like random random things like we need to do our own Qa. And not like have the stakeholders pointed out.

216 00:19:42.200 00:19:45.099 Awaish Kumar: And then, like we might spend some more time on

217 00:19:45.360 00:19:50.330 Awaish Kumar: doing these Qa. Maybe on campaign names, and figure out

218 00:19:51.070 00:19:54.099 Awaish Kumar: if there is something off in our rejects. But yeah.

219 00:19:55.570 00:19:58.680 Awaish Kumar: but at least but at least this right now it sold over

220 00:19:58.810 00:20:02.539 Awaish Kumar: problem with some, and also add add the cogs.

221 00:20:03.620 00:20:15.690 Robert Tseng: Okay. Yeah. Well, I mean, I’m gonna update the I’ll update the the dashboard and I’ll look at it. And if I see anything else I’ll let you know. But hopefully, we’re just like one or 2 changes away, like I think we should be pretty close.

222 00:20:18.750 00:20:21.900 Robert Tseng: I guess, like feedback that I got from the team.

223 00:20:22.370 00:20:26.700 Robert Tseng: I told, I I kind of already shared about the product matching thing.

224 00:20:26.990 00:20:32.640 Robert Tseng: Yeah, I think they were just as an as anticipated, some questions around the uncategorized

225 00:20:33.324 00:20:35.650 Robert Tseng: so like the order counts.

226 00:20:36.360 00:20:37.970 Robert Tseng: Now we are showing.

227 00:20:38.260 00:20:45.080 Robert Tseng: does it include that? It’s all? It only includes orders that have been assigned to paid campaigns.

228 00:20:45.750 00:20:59.589 Robert Tseng: Is that correct? And so we we’re we are not showing organic orders, or like other orders that didn’t get attributed to like a like a like a camp like A.

229 00:20:59.900 00:21:03.389 Robert Tseng: But that didn’t have like a campaign product. Name.

230 00:21:03.700 00:21:04.880 Robert Tseng: Does that make sense.

231 00:21:06.990 00:21:10.189 Awaish Kumar: Yeah. But I don’t think so. That’s the that’s correct. Right?

232 00:21:11.560 00:21:17.150 Robert Tseng: Yeah, like they were saying, like, Okay, look like 3,600 here. This is only

233 00:21:17.991 00:21:21.720 Robert Tseng: orders that are tied to like

234 00:21:22.870 00:21:29.980 Robert Tseng: like this isn’t all the orders. There’s probably like 10% that’s not

235 00:21:30.440 00:21:35.530 Robert Tseng: attributed to product categories here. That’s just not being shown here.

236 00:21:36.058 00:21:44.849 Robert Tseng: That. That’s what they think and I’m not sure. I I think that makes sense, because the way that we did these joins, because is

237 00:21:45.540 00:21:47.859 Robert Tseng: there had to be a

238 00:21:47.960 00:21:57.059 Robert Tseng: campaign that we were able to map them to. Or we just left the ad spend as uncategorized. And so maybe we are. Yeah, yeah.

239 00:21:57.190 00:22:05.859 Robert Tseng: which is fine. We don’t have to show the organic orders here or whatever. But I just I would want to be able to tell them like, Okay, like, we’re missing 10, or whatever it is.

240 00:22:12.930 00:22:24.439 Robert Tseng: Yeah. So once, once you’re, I refresh this with your changes. I think, like, yeah, I’ll I’ll just review this one more time. But yeah, I think that’s that just calling all the different limitations we have here. So

241 00:22:25.310 00:22:26.190 Robert Tseng: okay.

242 00:22:26.640 00:22:33.230 Awaish Kumar: Yeah, that that count is going to be around one. If you if we are using staging tables.

243 00:22:33.530 00:22:38.509 Awaish Kumar: then the adjustment for thermal line becomes around 1, 94 k.

244 00:22:38.780 00:22:40.529 Awaish Kumar: Not just 1 50 k.

245 00:22:45.300 00:22:46.910 Robert Tseng: In the past 30 days.

246 00:22:48.000 00:22:50.950 Awaish Kumar: Yes, in the past 30 days, even if I just

247 00:22:51.110 00:22:59.930 Awaish Kumar: select the table from North Beam without any joins. And I verified it. So the data coming in, it becomes 194 k.

248 00:23:00.390 00:23:17.730 Robert Tseng: Okay, yeah, I mean, I I’m I’m not saying that I trust the 1 50 number I was given. So if that’s what you’re saying then, like, I think we have a reason to to stand by it. But but yeah, I think, yeah. The the 20 K was was too low. So we did have to make a change.

249 00:23:18.350 00:23:30.579 Robert Tseng: Okay? Yeah, no. Thanks for being on top of this. I mean, this is law. One thing that they have been hounding us for for weeks. So like, it’s still the highest priority. But we’re gonna we’re gonna get there.

250 00:23:31.800 00:24:00.459 Robert Tseng: I guess, like other things that we kind of teed up. So once we move on past this oops, we wanna start bringing in like more data into the data warehouse. Right? I think maybe for a wish, like one thing that’s on the roadmap is yeah. The the Zendesk data model. I don’t think Sahana’s on to like really talk through this yet. But just putting that on your roadmap that like, I’ll probably review this and then gonna assign this to you, and we’ll probably start adding that in next week.

251 00:24:01.149 00:24:05.040 Robert Tseng: So that’s a that’s that’s a new data source that we’re gonna be pulling in.

252 00:24:07.890 00:24:09.789 Robert Tseng: Yeah other than that.

253 00:24:10.745 00:24:18.659 Robert Tseng: I saw your architecture diagram. I know you’re probably still in progress there, and we’re still working through the marketing data, mark. But I think that should be it, for Eden.

254 00:24:19.020 00:24:20.450 Robert Tseng: Does that sound about right.

255 00:24:21.260 00:24:22.410 Awaish Kumar: Yeah, okay.

256 00:24:23.090 00:24:31.590 Robert Tseng: Okay. So I’m gonna hope that we can close out this marketing data mark by tomorrow. And then this thing, I think, you know, seems like you’re almost done. So I’ll just put it there.

257 00:24:33.620 00:24:35.490 Robert Tseng: Yeah. Okay, then, let’s let’s.

258 00:24:35.490 00:24:39.870 Awaish Kumar: Data model. I haven’t even started on it yet, so I don’t know.

259 00:24:41.150 00:24:45.220 Robert Tseng: Oh, isn’t that just what this is like? This is the marketing data mark, right?

260 00:24:46.280 00:24:49.270 Awaish Kumar: I’m not sure this is because.

261 00:24:50.350 00:24:52.820 Robert Tseng: Yeah, this is, this is the same thing that you’ve been working on.

262 00:24:56.440 00:25:01.870 Awaish Kumar: Okay? No, but I don’t know. Is, does it have the north beam data.

263 00:25:03.600 00:25:08.050 Robert Tseng: Data mart with several tables leading to marketing. Oh, okay. So

264 00:25:09.380 00:25:17.860 Robert Tseng: you jumped in and create something for this. Okay, no. The date, the north beam data isn’t here. Okay? Maybe we’ll just review this really quick. It is. Yeah, it does have Northeas.

265 00:25:17.860 00:25:18.759 Awaish Kumar: God runs me!

266 00:25:19.410 00:25:26.250 Robert Tseng: Yep, for north beam. Ltv, Ross. Yeah. Okay, yeah. So this is just like turning the north beam data into data. Mark, okay.

267 00:25:30.770 00:25:36.389 Awaish Kumar: Yeah, this, the task which I’m working on right now wasn’t even assigned. It was just.

268 00:25:37.140 00:25:41.030 Robert Tseng: Yeah, I I realized that it wasn’t even yeah.

269 00:25:42.920 00:25:48.300 Robert Tseng: okay, I’ll I’ll I’ll find the existing one that he was on, and I’ll I’ll add you to it, I think.

270 00:25:50.120 00:25:51.342 Robert Tseng: Where is it?

271 00:25:55.870 00:26:05.880 Robert Tseng: okay, whatever that’s on me, I’ll I’ll I’ll go find the ticket that I assigned to Utam. Then I’ll just put you on that. That’s why that’s what you’ve been working on.

272 00:26:06.150 00:26:10.290 Robert Tseng: Okay. And then let me leave with the remaining.

273 00:26:10.480 00:26:14.119 Robert Tseng: We could. Ruby really quick. Let’s just talk through the Javi piece.

274 00:26:15.735 00:26:16.540 Robert Tseng: Yeah.

275 00:26:16.710 00:26:21.339 Robert Tseng: Anything that I can like chat with you about Anjabi

276 00:26:21.440 00:26:25.069 Robert Tseng: is, see that you have this on, or like.

277 00:26:25.070 00:26:28.539 Awaish Kumar: Yeah. So right now for Jolly, there’s no

278 00:26:29.290 00:26:33.039 Awaish Kumar: there are. There were a few things which Kutham says, said he will

279 00:26:33.610 00:26:37.940 Awaish Kumar: add more description for it, and then we can discuss kind of.

280 00:26:38.960 00:26:39.430 Robert Tseng: Yes.

281 00:26:39.430 00:26:43.719 Awaish Kumar: I I don’t think there is any task which has all the information.

282 00:26:44.380 00:26:46.090 Robert Tseng: Okay, that’s fine.

283 00:26:47.546 00:26:53.430 Robert Tseng: Okay, I’m yeah. I’m gonna I’m gonna press him to go and add, add those details in. We’ll probably fill it in by end of day.

284 00:26:54.362 00:27:08.340 Robert Tseng: Okay, cool. So sounds like, we’ll just kinda yeah, Weish and I will be kind of back and forth trying to finish this Eden model thing, and then I’ll update some of the tickets here. But alright, that sounds good. Thanks, guys.

285 00:27:09.270 00:27:10.030 Awaish Kumar: Okay. Thank you.

286 00:27:10.030 00:27:11.039 Luke Daque: Thanks. See you.