Meeting Title: Robert Tseng’s Personal Meeting Room Date: 2025-03-24 Meeting participants: Aakash Tandel, Annie Yu, Uttam Kumaran, Robert Tseng, Awaish Kumar, Caio Velasco


WEBVTT

1 00:15:43.840 00:15:44.760 Aakash Tandel: Here are

2 00:15:46.890 00:15:47.370 Robert Tseng: Hey! Gosh!

3 00:15:53.870 00:15:56.449 Aakash Tandel: My camera is not working. That’s weird.

4 00:15:57.360 00:15:58.410 Aakash Tandel: Oh, there it goes!

5 00:16:03.150 00:16:04.429 Aakash Tandel: How’s it going

6 00:16:05.450 00:16:11.979 Robert Tseng: Going. I’m pretty settled in, but I’m I’m back at my old building and the

7 00:16:12.180 00:16:16.460 Robert Tseng: business center again for hopefully. Only 2 more days

8 00:16:16.640 00:16:17.320 Aakash Tandel: Nice

9 00:16:17.520 00:16:21.329 Robert Tseng: Yeah, we just like have to return the keys and all that. So

10 00:16:21.770 00:16:22.639 Aakash Tandel: That’s fair.

11 00:16:22.640 00:16:23.010 Robert Tseng: Yeah.

12 00:16:23.010 00:16:29.760 Aakash Tandel: Are you planning on doing like a like a Co working building? I know you mentioned to Bobby you were thinking about that

13 00:16:30.720 00:16:39.848 Robert Tseng: Yeah, I might. I might do an office or at least like what Bobby does like a couple of days a week somewhere else.

14 00:16:41.270 00:16:41.630 Aakash Tandel: Nice

15 00:16:41.630 00:16:46.466 Robert Tseng: Yeah, I mean, I’m assuming you’ve you’ve been working from home for a while, so

16 00:16:47.050 00:16:49.540 Aakash Tandel: I go in the office like 3 days a week.

17 00:16:49.750 00:16:50.690 Robert Tseng: Oh, you do.

18 00:16:51.350 00:16:53.220 Robert Tseng: Oh, okay.

19 00:16:53.410 00:16:57.858 Aakash Tandel: Yup. I work from home Mondays and Fridays, and then we have to be in the office

20 00:16:58.290 00:17:00.350 Aakash Tandel: Tuesday, Wednesday, Thursday. So that’s

21 00:17:00.350 00:17:02.220 Robert Tseng: Dang, okay.

22 00:17:02.220 00:17:06.419 Aakash Tandel: But Charlottesville is pretty small, and I’d like live like 10 min from work. So it’s not that bad

23 00:17:06.849 00:17:08.599 Robert Tseng: Yeah, cool.

24 00:17:08.869 00:17:10.764 Aakash Tandel: Yep, alright.

25 00:17:12.559 00:17:18.559 Aakash Tandel: Yeah. So for this, stand up. I don’t know if you did you want to run it, or did you want me to kind of go ahead and take it

26 00:17:18.560 00:17:29.730 Robert Tseng: I can. I can run it today. And then you just get kinda get caught up on some kind of where we’re at with things. I know you haven’t really been too involved in the job. You side. So okay, yeah.

27 00:17:30.030 00:17:30.760 Aakash Tandel: Sounds good.

28 00:17:33.170 00:17:35.819 Aakash Tandel: I’m just taking a look at the linear. Make sure

29 00:17:36.630 00:17:39.150 Robert Tseng: Yeah, I’ve been going in and cleaning some of this off.

30 00:17:47.150 00:17:51.779 Robert Tseng: Really, the biggest blocker now is on the Amazon side. I feel like we’ve made no progress on that

31 00:17:52.760 00:17:54.191 Aakash Tandel: And is that a

32 00:17:56.020 00:17:57.709 Aakash Tandel: What! What’s blocking us there

33 00:17:58.480 00:18:01.240 Robert Tseng: I think there’s some outstanding like

34 00:18:01.750 00:18:09.250 Robert Tseng: a a d da work there on like figuring out what data? How do we get the right data that we want in there.

35 00:18:10.770 00:18:11.350 Robert Tseng: Yeah.

36 00:18:11.350 00:18:12.009 Aakash Tandel: Hey Kyle.

37 00:18:13.690 00:18:14.959 Caio Velasco: Hey, guys, how you doing

38 00:18:16.660 00:18:17.849 Aakash Tandel: Not bad. How are you doing

39 00:18:18.960 00:18:19.690 Caio Velasco: Meanwhile.

40 00:18:23.100 00:18:24.549 Aakash Tandel: Let’s see.

41 00:18:24.850 00:18:29.079 Caio Velasco: So for every meeting we have, we should use this link to zoom

42 00:18:31.176 00:18:36.870 Robert Tseng: No, we’re gonna change it. This is just my personal link. Yeah, we have to update it

43 00:18:37.160 00:18:39.980 Caio Velasco: But I think I guess the cost will probably handle that

44 00:18:43.170 00:18:44.936 Aakash Tandel: Yeah, I will send out

45 00:18:45.570 00:18:51.430 Aakash Tandel: actually, I’ll do that right now while we’re on this call. I’ll start the job. Stand ups

46 00:18:53.343 00:18:56.430 Aakash Tandel: I’ll start a new calendar invite for all those

47 00:18:56.970 00:18:57.580 Robert Tseng: Okay.

48 00:19:14.870 00:19:15.920 Annie Yu: Good morning!

49 00:19:17.360 00:19:18.110 Aakash Tandel: Morning.

50 00:19:18.110 00:19:19.030 Robert Tseng: Morning, Eddie

51 00:19:19.430 00:19:23.220 Annie Yu: Good. Good! I’m gonna stay off the camera for now

52 00:19:23.600 00:19:25.245 Robert Tseng: No worries. It’s early for you

53 00:19:25.520 00:19:28.379 Aakash Tandel: Yeah, all good. I know it’s really early for you guys

54 00:19:40.440 00:19:44.869 Robert Tseng: Probably. We’ll give it like another minute. Then I’ll then I’ll start.

55 00:20:08.890 00:20:13.450 Robert Tseng: I keep telling Aman to join these stand ups, and he never does. It’s like, Okay.

56 00:20:15.030 00:20:15.896 Aakash Tandel: Is he?

57 00:20:16.610 00:20:20.260 Aakash Tandel: Is he? Does he work like specific hours, like East coast or west Coast

58 00:20:20.260 00:20:22.159 Robert Tseng: Yeah. He’s he’s east coast hours.

59 00:20:22.160 00:20:22.860 Aakash Tandel: Okay. Yeah.

60 00:20:22.860 00:20:31.559 Robert Tseng: He’s always asking me to meet at like obscure time. So I’m trying to just like point him to like, Hey, you can actually reach me. If you just talk to me at a reasonable time.

61 00:20:31.560 00:20:32.110 Aakash Tandel: Yeah.

62 00:20:32.180 00:20:35.439 Robert Tseng: Theme, so I’ll put on my headphones.

63 00:20:51.810 00:20:53.599 Robert Tseng: Okay? Hello! Hello! Can you hear me?

64 00:20:54.380 00:20:55.100 Aakash Tandel: Yep.

65 00:20:55.100 00:21:01.769 Robert Tseng: Okay, cool. Alright. Well, maybe if you want to just ping a wish, but otherwise we can just get started

66 00:21:02.090 00:21:02.660 Aakash Tandel: Sure.

67 00:21:03.000 00:21:08.220 Robert Tseng: Yeah, hey? I’ll share my screen.

68 00:21:17.950 00:21:19.590 Robert Tseng: Okay.

69 00:21:28.520 00:21:42.779 Robert Tseng: alright. So I kind of spent some time this morning. Just kind of cleaning up some of these things. I think there were some duplicate issues, and then wanted to like kind of adjust some of the timelines on these projects as usual. I’ll start with the urgent projects first, st and after that we’ll go into the issues backlog

70 00:21:43.194 00:21:50.609 Robert Tseng: so on the shopify side. I guess this is more for a waste, since he’s not on this call. I’m not gonna talk about that right now.

71 00:21:51.121 00:21:54.736 Robert Tseng: But generally just for Akash’s. Oh, I guess easier.

72 00:21:55.710 00:22:10.029 Robert Tseng: sorry, just joined. But I’m talking about you right now. So we’re talking about the shopify gross margin dashboard, and the things that are in review. So I guess one question. Maybe this Kyle, did we get rid of the total product cost fields yet

73 00:22:10.640 00:22:12.800 Caio Velasco: Yes, I already pushed the Pr. But since

74 00:22:12.800 00:22:13.140 Robert Tseng: Okay.

75 00:22:13.140 00:22:33.220 Caio Velasco: It showed that it’s supposedly affecting 2 or 3 other tables that already had mentioned before we do them. I’m just waiting for a final answer from. He’s for some reason using this aggregated tables that are on the sales mark. But if not, I would just delete them. But the total project cost is already deleted from factor

76 00:22:33.220 00:22:33.760 Robert Tseng: Okay.

77 00:22:33.760 00:22:35.269 Caio Velasco: The Pr is in review.

78 00:22:35.880 00:22:41.380 Robert Tseng: Cool. Could you write just like link to the Pr in this linear ticket next time? And then also, just like.

79 00:22:41.920 00:22:50.240 Robert Tseng: like, say, okay, just like, leave a comment. Because, yeah, I’m not like, yeah, I think that would be helpful when I’m like, basically looking at the tickets

80 00:22:50.650 00:22:52.350 Caio Velasco: No question, perfect

81 00:22:52.350 00:22:58.869 Robert Tseng: Yeah, okay, I think this sub issue is pretty much the same

82 00:23:00.320 00:23:23.379 Robert Tseng: thing. Yeah, we already investigated the difference. So yeah, you’re just kind of giving an update there. Alright. And then on the funnel type. Yeah, we’re away for Block, because I didn’t understand Aman’s response. Like he, I, you’ve said it. See that throughout? I asked him some questions, but he didn’t really give a clear answer. So I feel like we’re just gonna wait for him to give an answer.

83 00:23:23.500 00:23:30.409 Robert Tseng: After that I should be able to add the 1st subscription, order like report to the dashboard, and then this should be ready to ship.

84 00:23:31.456 00:23:42.899 Robert Tseng: I know we have like this mer and product specific. P and L thing. Yeah. Still blocked. So no, no need to update there. But yeah, I think the idea is just to if you open up this.

85 00:23:45.940 00:23:51.840 Robert Tseng: can you? Do you see this random pop? Is it still stuck on like, do you see the Google Sheet? I just opened

86 00:23:51.840 00:23:52.570 Annie Yu: Yeah.

87 00:23:52.900 00:23:53.700 Robert Tseng: Okay, cool.

88 00:23:53.940 00:23:58.220 Robert Tseng: Yeah. So yeah, we’re basically and like

89 00:23:59.310 00:24:18.689 Robert Tseng: would end up creating a table kind of, I, I think this is not a great looking table. But at least it has these different metrics all in one, in one place. That’s basically what they wanted. So I just view it as like a month a pivot table by month with some of these metrics by product. So that’s kind of what the outstanding

90 00:24:18.840 00:24:20.320 Robert Tseng: thing is. There?

91 00:24:21.900 00:24:40.159 Robert Tseng: okay, I’ll spend some time on the Amazon dashboard because I feel like we’ve been kind of stuck here for some time. So maybe we just kind of chat through. I mean, I don’t have to click into every ticket. I know, Kyle. Most of these are assigned to you, so kind of want to get an update on where? Where we at with these investigations and getting the data ready for us to push the next round of updates

92 00:24:41.160 00:24:42.690 Caio Velasco: So for these.

93 00:24:43.440 00:24:58.449 Caio Velasco: I posted today on the on the Channel that I needed help restructuring the whole thing behind Amazon, and I also talk with with you, Tom, but he told me to talk to Luke, so I’m gonna have a call with Luke so that he can kind of like, do some knowledge transfer

94 00:24:58.909 00:25:04.680 Caio Velasco: cause? I already I don’t knowledge. I have this because of the total product thing I did.

95 00:25:04.950 00:25:07.170 Caio Velasco: But it doesn’t even

96 00:25:07.350 00:25:32.570 Caio Velasco: it wasn’t even consuming directly from the Amazon selling partner rod database. So I still have to go through that I’m a bit lost in terms of like where I begin when receiving something in the other end like from the client. But then, not having any knowledge on the database, so it’s still like trying to figure out what’s the best way to to approach it. But I have been studying. And

97 00:25:32.750 00:25:37.360 Caio Velasco: and yeah, I don’t have like any specific

98 00:25:40.800 00:25:47.999 Caio Velasco: update for each one of them, because I I had to have to understand really like, what are the stuff in the database?

99 00:25:48.425 00:25:52.699 Caio Velasco: I thought it was in a week, but then you don’t. But now look what I’m trying to do

100 00:25:53.403 00:26:03.079 Caio Velasco: this this story. But then I think Luke will talk to me today, and I hope that I have more understanding like, where should I start with this?

101 00:26:03.570 00:26:07.299 Caio Velasco: They’ve been looking at the Amazon stuff, but still it’s too broad

102 00:26:10.710 00:26:30.850 Robert Tseng: Okay? Yeah. I mean, oh, cost for your visibility, I think. Just we have been kind of like stuck answering 3 questions for like about 2 weeks now. So we we definitely need to speed this up. So if we need to pull in like, yeah, I mean, we we just we need to. We need to. We need to get blocked here. So

103 00:26:31.070 00:26:48.399 Caio Velasco: And I haven’t. I haven’t been touching this for 2 weeks, for sure, but they exist for 2 weeks. I’ve touched them like started like last Thursday, or something, or or Wednesday. So yeah, cause I was still like part time, etcetera. Now, like you can told me to move a little bit more with this with more time.

104 00:26:48.640 00:26:51.149 Caio Velasco: But yeah, that’s how fire went

105 00:26:51.520 00:26:55.020 Aakash Tandel: Do you think we’ll be able to unblock us, or should we pull in, or something

106 00:26:56.520 00:27:10.870 Caio Velasco: I have to talk to him and see like. What does he know? And because in the model it says that you don’t created them. But then you come, told me that you create them. So maybe Luke has the knowledge and he can do some knowledge. Transfer with me

107 00:27:12.160 00:27:21.349 Aakash Tandel: Yeah, if you can get with Luke, maybe like after this call or something just to I just wanna know if he can unblock, because if he can’t, then we’ll just move right back to with them.

108 00:27:26.890 00:27:31.930 Robert Tseng: Okay, cool. Yeah. I mean, there’s a lot of issues. That are.

109 00:27:32.310 00:27:38.619 Robert Tseng: And then so hmm, later, as we

110 00:27:39.700 00:27:43.130 Robert Tseng: okay, now, we can jump to a waste

111 00:27:43.340 00:27:48.949 Robert Tseng: sent among a sample of attentive data? Or was it maybe

112 00:27:49.440 00:27:51.640 Robert Tseng: and then come on, said that he’s gonna look through it.

113 00:27:52.130 00:28:02.369 Robert Tseng: I I mean, I did mention 2 sources. So I think we only sent him one. So that’s why I left this interview. Yeah, we only send preview. So if we have attentive data, can we send that to him as well

114 00:28:07.930 00:28:10.119 Aakash Tandel: You kind of broke up there, Robert, for me, I don’t know.

115 00:28:10.780 00:28:11.649 Aakash Tandel: Okay, thank you.

116 00:28:11.650 00:28:14.310 Awaish Kumar: You want me to send the attentive data as well

117 00:28:14.580 00:28:15.310 Robert Tseng: Yeah.

118 00:28:15.990 00:28:18.570 Awaish Kumar: Okay, I sure I will. I’ll do it.

119 00:28:19.490 00:28:20.210 Robert Tseng: Thanks.

120 00:28:25.050 00:28:31.259 Awaish Kumar: Actually we. We are also blogged on Tiktok shop. Api. So I have some

121 00:28:32.120 00:28:35.620 Awaish Kumar: like bandwidth. If there is anything like

122 00:28:36.167 00:28:38.750 Awaish Kumar: something you want me to look at. I can.

123 00:28:38.910 00:28:40.349 Awaish Kumar: I can help you

124 00:28:40.590 00:28:47.749 Robert Tseng: Okay, yeah, we might try to. Once we get to the Amazon stuff, we’ll try to talk tactically on how we can get Kyle to support here.

125 00:28:48.439 00:29:15.529 Robert Tseng: Yeah, I think this is the Pr review. This is the funnel type. So we’re clear there. So Amazon being portable like, I don’t know why this stick to this severe, I feel like we already have this right? I mean, my my understanding is that we we pull. We. We had Amazon data coming in through 5 Tran, we switch it to portable after we switched it to Portable. I stopped looking at the source data that was coming in. If I need to go and look at the source data to find the 3 fields that I think I need in order to answer all the questions I will. But like.

126 00:29:15.974 00:29:42.509 Robert Tseng: Yeah, I think just to summarize. Like all the lists of questions here regarding Amazon, one is like order statuses. How how are Amazon order statuses different from other order statuses? I think that’s really where all these like order cancellations kind of questions come in the subscribe and save that’s like a that’s like to me. That’s just like a label for a particular type of customer. They’re either a single single product

127 00:29:42.510 00:30:08.610 Robert Tseng: like buyer, or I don’t know. Maybe no label. I don’t. I don’t know how we label it, but it’s like you’re a subscription customer, or you’re not so like to me. That’s another flag. And then I mean, this is the same question as the 1st one. It’s really just, you know. Order statuses again, what’s a canceled order versus a order that has cleared, but hasn’t actually posted payment, or whatever and then this question is really more about like.

128 00:30:08.960 00:30:35.659 Robert Tseng: when there are multiple products like, are there multiple orders or like, how does Amazon? How does the Amazon scheme actually look like? Do they have one, a single order with multiple products nested into it like we do with shopify or not. So those are really the 3 main questions that we’re trying to answer. Here I feel like this is an outdated ticket, but maybe just correct me like, are we? Do we need anything here from here like I don’t know why this was assigned to which

129 00:30:37.630 00:30:40.149 Awaish Kumar: Okay, I’m not sure as well, because

130 00:30:42.380 00:30:49.720 Awaish Kumar: I will ask with them, like, what is this about? Because I’m also not sure, like what?

131 00:30:49.990 00:30:58.280 Awaish Kumar: Why we are moving to the portable or whatever I will get the context and update update you

132 00:30:58.610 00:31:02.669 Robert Tseng: Okay? So let’s do wish to connect

133 00:31:03.630 00:31:08.760 Robert Tseng: on the context for Amazon data.

134 00:31:13.100 00:31:16.475 Robert Tseng: Go to portable. Pick cool.

135 00:31:19.570 00:31:25.537 Robert Tseng: Yeah. You mentioned, we’re blocked here on the Tiktok stuff. I’ve been like somewhat monitoring the

136 00:31:28.684 00:31:33.809 Robert Tseng: the the channel with portable. But I guess where are we in this

137 00:31:34.840 00:31:40.800 Awaish Kumar: Yeah, we we are blocked by them, I think, Kutham replied to them.

138 00:31:41.050 00:31:48.652 Awaish Kumar: So I didn’t bother them. After that, maybe I can ask again today. What is the status

139 00:31:49.240 00:31:50.040 Robert Tseng: Okay.

140 00:31:50.920 00:31:53.750 Robert Tseng: And by the way, Akash, I think he’s

141 00:31:54.010 00:32:01.239 Robert Tseng: we could update the statuses on this tickets like, I don’t see a blocked here like, and just like a

142 00:32:01.730 00:32:06.140 Robert Tseng: analysis section or something. But it just looks a little bit inconsistent from other

143 00:32:06.801 00:32:09.869 Robert Tseng: clients. I’m a bit confused. There

144 00:32:10.000 00:32:12.220 Aakash Tandel: I’ll modify the statuses

145 00:32:12.460 00:32:13.300 Robert Tseng: Okay.

146 00:32:13.750 00:32:18.151 Robert Tseng: Alright, I’m not. I’m not. Gonna I think I’ll let you handle that

147 00:32:19.332 00:32:36.219 Caio Velasco: I have just a quick question regarding those tickets. I’ve been. I noticed that there are 2 fact order tables and Amazon orders, but both consume from the same places. So why isn’t so? I think Amazon are is modeled already.

148 00:32:37.990 00:32:38.679 Caio Velasco: so

149 00:32:41.770 00:32:44.970 Awaish Kumar: Yeah, that’s why we don’t have context in, because

150 00:32:46.290 00:32:55.570 Awaish Kumar: Amazon data, we we connected with 5 trend. And what I can guess from from this is that 5 trend is really expensive.

151 00:32:55.930 00:33:03.279 Awaish Kumar: And maybe that was one of the reason that maybe wanted to research on using different connector

152 00:33:04.010 00:33:11.880 Awaish Kumar: our task with and get the get all the data we need. So yeah, that’s I think that’s what it is.

153 00:33:12.280 00:33:28.329 Robert Tseng: Okay, we talked about the call actually, right now. So let me just like throw the question his way. So anytime, I think our biggest block around Joby is the Amazon stuff, like I feel like we haven’t had. We haven’t had any movement in a couple of weeks, so I think Kyle’s kind of a bit lost on, like the investigation on like how to catch up on the Amazon contacts.

154 00:33:28.786 00:33:54.569 Robert Tseng: and and stuff. So there’s like all these, all these kind of in progress tickets that are all pretty much asking like, What is the Amazon like? What is? How is Amazon order? Data different from shopify is really what, what? The what all these questions are, point to and then, I think, always has a bit of bandwidth. So he was gonna go and kind of help support there, but I think they both probably need you or or Luke to kind of help fill them in

155 00:33:55.210 00:34:11.609 Uttam Kumaran: That’s totally fine. I mean, I yeah. So Luke had. Luke and me both have full awareness of how Amazon is built. I’m pretty sure Luke did the Amazon stuff for Joby, so I would ask him 1st if it’s like a red alert, and you need me to take any of these, just

156 00:34:11.909 00:34:15.690 Uttam Kumaran: tell me which ones, but if it’s not at that point.

157 00:34:16.090 00:34:18.960 Uttam Kumaran: then I would. I would defer to asking Luke.

158 00:34:19.270 00:34:25.849 Uttam Kumaran: but frankly I would put a due date on all these, and I see that there is tomorrow. Is it actually tomorrow

159 00:34:26.090 00:34:34.749 Robert Tseng: They were all yesterday, like last week. But it was like the due date would probably be tomorrow. Because I I want to show something by Wednesday

160 00:34:34.969 00:34:38.849 Uttam Kumaran: Okay, then I feel like, can we all agree? This is like.

161 00:34:39.019 00:34:41.989 Uttam Kumaran: this is like a red, alert thing to do today.

162 00:34:43.090 00:34:47.755 Robert Tseng: Yeah, like, if we we should. Yeah, we should- we should get to the bottom of it.

163 00:34:48.030 00:34:48.530 Uttam Kumaran: Okay.

164 00:34:48.530 00:34:49.467 Robert Tseng: Right, mark, yeah.

165 00:34:50.418 00:34:55.939 Uttam Kumaran: So then, which are all of like just these 3 that I’m looking at here

166 00:35:06.370 00:35:26.940 Robert Tseng: yeah, I mean, that’s 1 of them is just the dashboard build and the other the others are all asking similar questions, like order statuses subscribe and save. And how do? How are multiple products? Handled across? If there’s a order with multiple products get split up into multiple orders, maybe those are the 3 questions

167 00:35:28.320 00:35:30.677 Uttam Kumaran: Okay, cool. So I can take.

168 00:35:33.680 00:35:38.799 Uttam Kumaran: yeah. I mean, I can take the subscribe and save that that we haven’t done on across any clients

169 00:35:40.890 00:35:47.729 Uttam Kumaran: cancelled, and that so I guess my question is going to be for Kyle and a waste. Do you guys see a

170 00:35:48.310 00:35:53.680 Uttam Kumaran: up certainty that we can get this these 2 done today. If not, then I’ll I’ll just have to take them

171 00:35:56.370 00:35:57.140 Caio Velasco: Go on, my

172 00:35:57.140 00:35:58.540 Awaish Kumar: I I haven’t.

173 00:35:58.710 00:36:07.359 Awaish Kumar: I haven’t looked at this yet, but I think we can take 1 1 each. Maybe that’s why

174 00:36:07.580 00:36:10.210 Awaish Kumar: that way we can finish all of them.

175 00:36:10.610 00:36:13.349 Awaish Kumar: maybe 98. You can assign it to me. Maybe

176 00:36:14.030 00:36:14.750 Robert Tseng: Okay.

177 00:36:15.010 00:36:18.050 Uttam Kumaran: Yeah, 98, I think. Always, maybe. Take that. And then.

178 00:36:19.019 00:36:23.690 Uttam Kumaran: yeah, I don’t. I? Yeah, if we can split it one by one

179 00:36:24.060 00:36:29.790 Uttam Kumaran: ultimately, like by today, I mean, basically by the time y’all are both off.

180 00:36:29.940 00:36:37.720 Uttam Kumaran: which is, whenever that is so, if that’s not possible, then I’d rather just assign it to me, and I’ll just take care of it this afternoon.

181 00:36:38.460 00:36:41.900 Awaish Kumar: Yeah, I will work on it. And when I was

182 00:36:41.900 00:36:42.340 Uttam Kumaran: Okay.

183 00:36:42.340 00:36:43.980 Awaish Kumar: When I will.

184 00:36:44.380 00:36:49.230 Awaish Kumar: If I. If I cannot finish it, then I will let you know, like what is the status

185 00:36:49.660 00:36:50.270 Uttam Kumaran: Okay.

186 00:36:51.050 00:36:57.189 Caio Velasco: Yeah. For example, let’s say that I would take the that one. What state is the cancelled order? 3 or 4 payment?

187 00:36:57.880 00:36:58.830 Caio Velasco: So

188 00:36:59.580 00:37:06.060 Caio Velasco: is that. What is the source for that? It’s like Amazon selling part and roth, and that’s it. And it starts there

189 00:37:08.210 00:37:10.040 Uttam Kumaran: I mean, you have to figure that like.

190 00:37:10.430 00:37:14.720 Uttam Kumaran: well, you have to start from all the Amazon data. So yeah, it’s you can trace.

191 00:37:15.290 00:37:19.510 Uttam Kumaran: You can trace all the fact Amazon data all the way down to the source tables.

192 00:37:22.200 00:37:29.210 Caio Velasco: They are. So the Sima, the data model is built. It’s not something new that we have to do from Amazon telling partner

193 00:37:29.560 00:37:32.170 Uttam Kumaran: The goal is to answer this question.

194 00:37:34.300 00:37:38.820 Uttam Kumaran: what? So? What? What stage is a canceled order

195 00:37:39.230 00:37:41.559 Uttam Kumaran: like? Is it pre or post payment?

196 00:37:42.850 00:37:45.050 Uttam Kumaran: That’s the that’s the ultimate

197 00:37:45.180 00:37:52.009 Uttam Kumaran: deliverable here. So the deliverable is not a dashboard, not an analysis, not a pr, it’s just answering this question

198 00:37:55.890 00:38:00.669 Caio Velasco: The payment comes from what’s dropped by recharge or

199 00:38:02.100 00:38:03.620 Uttam Kumaran: Payment comes through Amazon.

200 00:38:04.710 00:38:06.130 Uttam Kumaran: It is sold on Amazon.

201 00:38:12.237 00:38:22.709 Caio Velasco: See 2 fact tables, 2 fact orders, exact orders. In fact, Amazon orders that are different. That’s like one is related to like Amazon dashboard, and another one to something else.

202 00:38:23.940 00:38:24.430 Uttam Kumaran: But did you

203 00:38:24.430 00:38:24.810 Caio Velasco: That’s like.

204 00:38:24.810 00:38:29.140 Uttam Kumaran: Check out the tables and see if there’s a payment process. If there’s a payment status field

205 00:38:30.520 00:38:42.020 Caio Velasco: I quickly check. But when I was doing this last week that, those are the questions that I sent in the beginning, so that I get. I can, you know, get started in the thing.

206 00:38:43.420 00:38:48.520 Caio Velasco: for example, I put over there ordering cancellation is that from financial status or something else, I don’t have

207 00:38:48.520 00:38:52.799 Uttam Kumaran: But like this is something that that Robert is not gonna know

208 00:38:53.990 00:38:55.929 Caio Velasco: Doesn’t this come from the client?

209 00:38:56.920 00:38:59.879 Uttam Kumaran: No, the tape, whether the table names.

210 00:39:00.650 00:39:06.419 Uttam Kumaran: No, we’re not. The client isn’t. Gonna tell us what source table this data is in.

211 00:39:08.390 00:39:09.590 Uttam Kumaran: Right? They’re just

212 00:39:09.590 00:39:10.420 Caio Velasco: But they had

213 00:39:10.420 00:39:12.810 Uttam Kumaran: If I ask the top question.

214 00:39:13.110 00:39:19.060 Uttam Kumaran: when a when a stage, when a order isn’t a canceled state, is this pre or post payment, that’s all.

215 00:39:19.610 00:39:24.930 Uttam Kumaran: that’s all they know, like they’re not in Snowflake, looking at the tables.

216 00:39:26.160 00:39:36.989 Uttam Kumaran: you know. But this is again, if you go to Luke, and you just ask him this. He’s gonna tell you exactly where it is. So it’s not. I don’t think it’s relevant to go through this with Akash or Robert.

217 00:39:37.430 00:39:42.080 Uttam Kumaran: It’s probably relevant to take these questions. And we should discuss this as a data team.

218 00:39:42.230 00:39:47.919 Uttam Kumaran: I don’t think, Robert, you’re gonna know whether it’s which table it is, and I don’t think it’s really his concern.

219 00:39:48.090 00:39:49.799 Uttam Kumaran: I think we should.

220 00:39:50.460 00:40:03.430 Uttam Kumaran: I think if you go select on both of these tables, you’re gonna see the cancelled statuses, and then you should sort of trace that back. But again, if you go talk to Luke for 10 min, I’m sure he’s gonna just he can work on this with you.

221 00:40:03.917 00:40:08.039 Uttam Kumaran: So I don’t like. I don’t think it’s fair to ask right now

222 00:40:09.160 00:40:14.874 Uttam Kumaran: which exact table and everything, because by the time we saw answer all these questions we’ll probably find the answer

223 00:40:16.460 00:40:34.129 Caio Velasco: Oh, okay, because I was thinking when I saw this this question, for example, although I don’t know, I don’t know what is a stage or whatever like. I always assume that I have 0 knowledge in each variable here, so that I can start from somewhere. And when I was doing that I thought that I will have to build a data model at

224 00:40:34.220 00:40:57.710 Caio Velasco: to answer this question at some point, you know, like, then, like all the tables, everything. So that at some point, okay, okay, this is where payment comes from. These are the. These are the facts. Maybe the factors is not using that. And the fact order has, like 1,000 of lines. So I was spending literally the whole time trying to understand, like how to build the data model so that I could answer this question, didn’t know that it would be just going to the table. See

225 00:40:57.710 00:41:03.159 Uttam Kumaran: Even if you have to build a data model, you. Still, even if you build a data model, you still need to know

226 00:41:03.690 00:41:05.899 Uttam Kumaran: where this is right.

227 00:41:06.190 00:41:10.550 Uttam Kumaran: So all that work you did we still so yeah.

228 00:41:10.830 00:41:13.740 Uttam Kumaran: no, I hear you. But I guess what I’m saying

229 00:41:13.740 00:41:18.430 Caio Velasco: The documentation for that, for example, gorgeous, that there was a documentation or the Api

230 00:41:18.430 00:41:21.779 Uttam Kumaran: You have to ask. You have to ask the team. You have to ask the team

231 00:41:22.340 00:41:24.989 Caio Velasco: That’s why I put it here on the comment

232 00:41:26.940 00:41:30.249 Uttam Kumaran: No, I hear you, but we’re we’re we’re here right now.

233 00:41:30.640 00:41:33.270 Uttam Kumaran: We have to try to get this out by this afternoon.

234 00:41:33.880 00:41:45.319 Uttam Kumaran: There is, like, I know, in the data model where this is. So does Luke. So there is knowledge on our team. If you go run a select on these tables. You’re gonna see the financial status

235 00:41:45.440 00:41:46.550 Uttam Kumaran: canceled

236 00:41:47.110 00:41:56.220 Uttam Kumaran: an order. But again, these are questions that we have to answer on as analytics engineering team like the client doesn’t know we don’t. Robert or Akash don’t know

237 00:41:56.570 00:42:02.859 Uttam Kumaran: these answers right? And it’s by the time we they would answer these they would have figured the ticket out

238 00:42:05.490 00:42:09.559 Caio Velasco: Okay, no, no. I was literally trying. I I really thought that

239 00:42:09.700 00:42:24.759 Caio Velasco: this would come more detailed from the client in terms of like, hey, we have these types of cancellation. We have this type of free or post payments. That’s how they work. This is the documentation on the Amazon website, where you start your work and model the data

240 00:42:25.140 00:42:34.069 Uttam Kumaran: If they knew the answer they wouldn’t have asked the question. I guess that’s my. That’s my point is that the question indicates that they have no idea

241 00:42:35.110 00:42:35.720 Caio Velasco: Alright.

242 00:42:36.337 00:42:42.370 Caio Velasco: Okay, no, I didn’t. I didn’t really know that. But it was just product owner sending tasks to the the engineers

243 00:42:42.670 00:42:44.070 Uttam Kumaran: No, no, no, no, no.

244 00:42:44.380 00:42:52.979 Uttam Kumaran: yeah, this is. I mean, this is a this is a thing across. Clients is like, we’re never gonna get like? If I was to go answer these questions, I would have solved this ticket

245 00:42:53.870 00:43:11.819 Uttam Kumaran: right? And so the the goal of this ticket is to just answer the question for the business. What stage is a canceled order at when you cancel an order on Amazon? Is it? Does the payment go through, or is this, after the payment? That’s all we know, right? And that’s the challenge. That’s if if we got all the details.

246 00:43:12.340 00:43:22.720 Uttam Kumaran: yeah, it’d be easy. It’d be yeah, there wouldn’t be a ticket, you know. So that’s what I’m saying is that I get that there are questions about which metrics is this a data model. But even

247 00:43:22.900 00:43:50.549 Uttam Kumaran: even before answering any of that, you should run some selects on these tables, and and then sort of talk to the anybody on the team that knows Amazon right? Like, I think, putting the comment here and then waiting for for this meeting is not. It’s just not enough, because we’re a team. We have to get this out right. We’re here now on the due date, and there’s no progress. It’s not your. It’s not. This isn’t ownership on you, but it’s ownership on us to still still find a way to get this done right? So

248 00:43:50.610 00:43:55.239 Uttam Kumaran: I’m putting my time on the line by saying, I’ll take it if I need to take it.

249 00:43:55.430 00:44:03.830 Uttam Kumaran: But between now and whenever you’re off today, if you have a moment to go, speak with Luke and identify this. I think we should try to get this out

250 00:44:04.630 00:44:20.439 Caio Velasco: I already messaged him earlier. I’m just waiting on him to see when we can talk, and then, just since you’re here, do open the or whoever has the screen, the investigation one. Just so that I have a verify one thing from from what posted there

251 00:44:23.165 00:44:28.819 Robert Tseng: Is that necessary to do? Can you do it? Offline? Because I feel like we spent the entire time talking about just those 3

252 00:44:28.820 00:44:32.060 Uttam Kumaran: Yeah, we probably have 3 min. Yeah, just okay.

253 00:44:32.060 00:44:34.670 Uttam Kumaran: could just ping me in the in the slack channel. Yeah.

254 00:44:34.670 00:44:35.240 Caio Velasco: Okay. Cool.

255 00:44:35.240 00:44:35.850 Uttam Kumaran: Make sure.

256 00:44:36.525 00:44:46.910 Robert Tseng: Yeah. So okay, we just, we just reassigned that recharge. Yeah, I don’t. Really. It’s just really in progress. Like, what what else are we doing on Recharge here

257 00:44:49.220 00:45:09.220 Caio Velasco: So this is something else as well that was doing, but on the portable side. So I, talking to Etan and answering a month via email as well. With regarding like ingestion issues that we might have since recharge changes something. I took that because I I received an email about it, and then it started.

258 00:45:09.775 00:45:13.749 Caio Velasco: And now we are waiting for some less answer, so that we can

259 00:45:13.950 00:45:23.620 Caio Velasco: choose between moving to incremental models or staying as it is that we are doing for just data.

260 00:45:25.800 00:45:27.959 Caio Velasco: And I just updated it as beautiful

261 00:45:29.580 00:45:30.290 Robert Tseng: Got it

262 00:45:30.290 00:45:33.470 Uttam Kumaran: Okay? So can we, what’s a like, what’s a good due date for this

263 00:45:41.510 00:45:46.540 Robert Tseng: Like I. It sounds like you’re proactively asked for it. I I feel like joby has no idea this is this issue.

264 00:45:46.540 00:45:50.129 Uttam Kumaran: No, no, I’m on. I’m on email. I’m on emailed us about this

265 00:45:50.130 00:45:50.549 Robert Tseng: Oh! Did you

266 00:45:50.550 00:45:55.690 Uttam Kumaran: Update. But the problem with this is, it’s going on for now a week.

267 00:45:55.910 00:46:03.460 Uttam Kumaran: So I guess what I’m asking is like, when can we consider this like close out, Kyle.

268 00:46:04.900 00:46:07.850 Uttam Kumaran: or is it clear like what next steps there are

269 00:46:09.070 00:46:18.069 Caio Velasco: No, I think we still have. I still ask the questions we’ve done regarding how he uses the updated at column to to do the

270 00:46:18.320 00:46:25.660 Caio Velasco: the refresh they do. But again, this is ingestion stuff that I said before, I don’t have a lot of knowledge, so I’m always also asking a wish.

271 00:46:25.770 00:46:42.600 Caio Velasco: and he’s been helping as well. So as I see, we need the last answer from Etan, and then the next step would be to ask to do the incrementation and change how we usually ingest. This is the the what I see for next steps, or stay with the status quo.

272 00:46:42.720 00:46:49.780 Caio Velasco: But it, I don’t know. Like, maybe someone with more knowledge on ingestion, since it’s a very, very important step.

273 00:46:50.130 00:46:51.210 Caio Velasco: would also

274 00:46:51.990 00:46:54.640 Uttam Kumaran: Is this a high? Is this really a high priority ticket?

275 00:46:57.300 00:46:57.790 Caio Velasco: I agree.

276 00:46:57.790 00:47:01.309 Robert Tseng: Maybe not. I mean, these are just legacy tickets. I’m updating as well

277 00:47:01.310 00:47:07.970 Uttam Kumaran: I I mean, yeah, a waste. Do you want to take this one, too? And then can we just put like Wednesday for this

278 00:47:07.970 00:47:08.540 Robert Tseng: Yes.

279 00:47:09.365 00:47:11.799 Awaish Kumar: Yeah, sure. But like, it’s not

280 00:47:12.210 00:47:19.059 Awaish Kumar: something we are doing. It’s like we are waiting on the portable team. Right? They

281 00:47:19.060 00:47:19.550 Uttam Kumaran: Yeah.

282 00:47:19.550 00:47:29.229 Awaish Kumar: Change it to the incremental or fully fish. So we have asked the question, if they clarify, we can just make a decision

283 00:47:29.230 00:47:33.630 Uttam Kumaran: Wednesday, and then it can. Can we put like blocks here by like

284 00:47:34.430 00:47:38.109 Uttam Kumaran: I’ll update it. I’ll update it. But I’ll just put Wednesday, and I’ll put it’s blocked by

285 00:47:38.110 00:47:49.340 Robert Tseng: Oh, okay, sorry. I just wanted to. I don’t know. We ran a bit longer. But yeah, I we haven’t heard from you yet, so wanted to get a couple of checks on on the gorgeous desk specifically.

286 00:47:52.060 00:47:58.780 Robert Tseng: yeah. Did you get a chance to look at this yet? Last time we chatted I sent you an amplitude, reports

287 00:47:59.491 00:48:04.480 Robert Tseng: and then, just like samples of what they currently do on how they filter by macros.

288 00:48:05.520 00:48:06.440 Robert Tseng: Yeah.

289 00:48:06.440 00:48:20.400 Annie Yu: Yeah, I have some visualizations in the dashboard already, and I believe we can answer all the questions above. But I would love to grab some time with you, just to go through if we need more edits. But I think

290 00:48:20.670 00:48:23.009 Annie Yu: we are able to answer these questions

291 00:48:23.220 00:48:35.829 Robert Tseng: Okay? Great. Yeah. I mean, just throw time on my calendar. If you just you can, you could probably find where gaps are. But yeah, if you just if you just try to schedule time with me, you’ll probably see where my availability is.

292 00:48:36.110 00:48:36.990 Uttam Kumaran: Okay, Andy, can you help

293 00:48:36.990 00:48:40.929 Uttam Kumaran: also add the the dashboard link to that ticket, and then I can take a look too.

294 00:48:41.350 00:48:42.180 Annie Yu: Good.

295 00:48:42.670 00:48:43.280 Robert Tseng: Cool

296 00:48:44.216 00:48:53.389 Robert Tseng: and then the address matching thing. I know this has kind of been passed around a lot. Somehow. It’s gonna been passed to Annie at this point. So

297 00:48:53.620 00:48:56.699 Robert Tseng: I guess the ask is still to basically take

298 00:48:57.030 00:49:16.760 Robert Tseng: the python script the bias and wrote, and to get it to a place where we can hand it off to a month team so they can go build their own like Ui to go in and upload it. Otherwise every Monday we’re gonna get hit with 2 or 3 of those files, and then they’re gonna want, like, same day or next day turnaround on running the script and sending them back the matching. So

299 00:49:17.511 00:49:23.780 Annie Yu: One quick question is, who do I expect to get the file from each week?

300 00:49:25.011 00:49:26.818 Robert Tseng: The guy named Shake

301 00:49:27.680 00:49:34.649 Uttam Kumaran: But we can put it. We’ll just have it in a in a ticket. I guess my question is like it looks like it looks like

302 00:49:34.650 00:49:35.220 Robert Tseng: Time.

303 00:49:35.400 00:49:41.919 Uttam Kumaran: It looks like pies, responded to the one that’s on the 17.th So I think we’re good. We should expect one today, right? So

304 00:49:42.560 00:49:48.650 Uttam Kumaran: we’ll create a ticket like, are these like same day turnarounds? Or can we like set some like.

305 00:49:49.430 00:49:52.010 Uttam Kumaran: can we have this by like Wednesday every week?

306 00:49:52.150 00:49:53.960 Uttam Kumaran: You think they’ll be okay with that

307 00:49:53.960 00:50:03.739 Robert Tseng: Yeah, okay, I mean, I think a model just probably be like, why, why can’t you just send us a script and we can just go and build our own like Ui, where we press a button and upload Csv feature

308 00:50:03.740 00:50:07.969 Uttam Kumaran: Well, he can do that, or we can do it. But then we have a hundred other things to do, so

309 00:50:07.970 00:50:08.350 Robert Tseng: Okay.

310 00:50:08.350 00:50:11.155 Uttam Kumaran: He can get in line. He’s only one in line. So

311 00:50:12.085 00:50:19.109 Uttam Kumaran: yeah, it’s just like we can’t do. All we can’t do. This is like so much to do in day to day. So

312 00:50:20.320 00:50:21.720 Uttam Kumaran: okay, cool

313 00:50:23.230 00:50:32.080 Robert Tseng: Alright, yeah, I know we’re over. So I mean, we didn’t really talk about the 2 days, but on the in progress stuff as much as we can clear this out, we definitely have more stuff to see up tomorrow onwards

314 00:50:32.660 00:50:36.760 Uttam Kumaran: So I’ll send a I’ll send a message around one central.

315 00:50:36.950 00:50:41.720 Uttam Kumaran: just saying Hi! To the channel. Just let me know where everyone’s at.

316 00:50:42.210 00:50:45.880 Uttam Kumaran: and then whatever we need to do to get stuff out. After that, you know, I can help on

317 00:50:47.370 00:51:16.139 Aakash Tandel: Cool. And one last thing I’ll add, before we hop off. Let’s just try to over communicate right now, just because, like I’m new. Annie’s new. Kyle’s new like. We’re all kind of new. We don’t know like what stage things are in. So if you just over communicate and you over. Ask in slack. I think that’s that’s a good way to move forward, and then I’ll make it to do of mine, just to groom what we’re talking about and put those into the tickets so that we make sure we’re kind of tracking everything. But yeah, let’s try to over communicate as we can

318 00:51:18.950 00:51:20.770 Robert Tseng: Okay. Sounds. Good. Thanks. Everyone.

319 00:51:21.100 00:51:22.250 Aakash Tandel: Thank you, Jill.

320 00:51:22.250 00:51:22.680 Aakash Tandel: Bye, bye.