Meeting Title: Data Team Planning Session Date: 2025-02-10 Meeting participants: Luke Daque, Nicolas Sucari, Uttam Kumaran, Payas Parab, Robert Tseng, Awaish Kumar, Bo Yoon
WEBVTT
1 00:06:29.450 ⇒ 00:06:30.599 Payas Parab: What up guys?
2 00:06:35.810 ⇒ 00:06:36.770 Payas Parab: Brian?
3 00:06:37.370 ⇒ 00:06:38.459 Bo Yoon: Hey! Morning!
4 00:06:38.705 ⇒ 00:06:39.930 Payas Parab: How are you guys doing.
5 00:06:40.710 ⇒ 00:06:41.289 Luke Daque: You’re doing well.
6 00:06:41.290 ⇒ 00:06:42.369 Bo Yoon: Good! How are you?
7 00:06:42.640 ⇒ 00:06:43.350 Awaish Kumar: Hello!
8 00:06:45.450 ⇒ 00:06:52.040 Payas Parab: Innovation. Bo, you guys overwhelmed yet, are you guys, you guys enjoying your 1st couple of weeks so far? How’s everything going.
9 00:06:52.996 ⇒ 00:06:57.800 Bo Yoon: It’s actually my second day. I just joined last Friday. So
10 00:06:57.970 ⇒ 00:07:00.697 Bo Yoon: I’m still trying to figure out what’s going on here.
11 00:07:00.970 ⇒ 00:07:02.769 Payas Parab: What it’s all about, man. Let us know how.
12 00:07:02.770 ⇒ 00:07:03.100 Bo Yoon: Like.
13 00:07:03.100 ⇒ 00:07:10.039 Payas Parab: Yeah, Ryan, and I’ve been in here for a while, Ryan, longer than me. Just if there’s anything we can do to help, please let us know.
14 00:07:12.048 ⇒ 00:07:13.961 Bo Yoon: Yeah, thank, you.
15 00:07:14.980 ⇒ 00:07:15.610 Payas Parab: Hi.
16 00:07:18.840 ⇒ 00:07:20.690 Nicolas Sucari: Hey, guys, how are you.
17 00:07:22.900 ⇒ 00:07:26.605 Luke Daque: Hi, Nicholas, are you with?
18 00:07:28.070 ⇒ 00:07:28.710 Nicolas Sucari: Yes.
19 00:07:29.090 ⇒ 00:07:30.120 Luke Daque: Are you with them now?
20 00:07:30.650 ⇒ 00:07:31.320 Luke Daque: Nice.
21 00:07:31.320 ⇒ 00:07:33.599 Nicolas Sucari: Yeah, he went for some coffee.
22 00:07:34.770 ⇒ 00:07:36.649 Nicolas Sucari: Yeah, I’m just gonna move it off.
23 00:07:39.300 ⇒ 00:07:41.390 Nicolas Sucari: Yeah, maybe we can wait for him like.
24 00:07:41.390 ⇒ 00:07:43.509 Payas Parab: Are you guys just meeting in like a coffee shop.
25 00:07:44.780 ⇒ 00:07:48.160 Nicolas Sucari: No very nice working space. It’s very nice.
26 00:07:48.520 ⇒ 00:07:49.650 Payas Parab: Sweet, yeah.
27 00:07:49.860 ⇒ 00:07:51.720 Nicolas Sucari: We came here to work there.
28 00:07:54.490 ⇒ 00:07:55.370 Luke Daque: That’s cool.
29 00:07:56.400 ⇒ 00:07:57.860 Robert Tseng: Argentina Office.
30 00:07:59.100 ⇒ 00:08:00.950 Nicolas Sucari: Argentina. Office. Yeah.
31 00:08:01.880 ⇒ 00:08:03.279 Nicolas Sucari: Really. Nice. Place.
32 00:08:12.430 ⇒ 00:08:15.759 Robert Tseng: Are you with time? Is he gonna join, or are we? Should we just jump into it.
33 00:08:15.950 ⇒ 00:08:22.990 Nicolas Sucari: Yeah, yeah, he’s there. It’s just joining for a copy.
34 00:08:35.750 ⇒ 00:08:40.740 Payas Parab: Rocking the Sc. Gear today, Robert, little school pride, nice.
35 00:08:40.740 ⇒ 00:08:42.009 Robert Tseng: Miss la, man.
36 00:08:42.770 ⇒ 00:08:47.579 Payas Parab: Yeah, I’m telling you we should all beau we. We just had a new addition to the Los Angeles office.
37 00:08:47.920 ⇒ 00:08:54.678 Robert Tseng: Now, yeah, now, I said, we have to have a Los Angeles office that might might make it happen at the end of q 1. That’s the goal.
38 00:08:55.610 ⇒ 00:08:59.525 Uttam Kumaran: I’m only Team Norcal. So yeah,
39 00:09:00.520 ⇒ 00:09:04.434 Uttam Kumaran: there’s that’ll have to be the sub satellite office.
40 00:09:04.870 ⇒ 00:09:05.280 Robert Tseng: I thought.
41 00:09:05.280 ⇒ 00:09:11.449 Uttam Kumaran: Or again, we meet in the middle, in Texas.
42 00:09:11.450 ⇒ 00:09:14.090 Robert Tseng: Not in the middle of the Council.
43 00:09:14.477 ⇒ 00:09:17.579 Uttam Kumaran: Oh, no, I mean like New York didn’t.
44 00:09:17.580 ⇒ 00:09:19.630 Robert Tseng: Oh, New York. And I, okay.
45 00:09:19.630 ⇒ 00:09:27.060 Uttam Kumaran: Yeah, we can meet, we can meet in like, somewhere in the middle of Central Central California. Yeah.
46 00:09:27.060 ⇒ 00:09:28.190 Robert Tseng: Hmm, yeah.
47 00:09:31.887 ⇒ 00:09:49.559 Uttam Kumaran: Cool. I we just went through like most of the open tickets. Let’s just pick a client, and maybe we jump right in. I mean, we were just talking about Javi. So maybe we just
48 00:09:50.300 ⇒ 00:09:52.410 Uttam Kumaran: let’s just start there.
49 00:09:52.410 ⇒ 00:09:58.010 Robert Tseng: Okay, dude, I’m not looking forward to this handoff. But
50 00:09:58.350 ⇒ 00:09:59.230 Payas Parab: It’s gonna be painful.
51 00:09:59.230 ⇒ 00:09:59.720 Robert Tseng: Well.
52 00:09:59.850 ⇒ 00:10:00.420 Payas Parab: I’m here.
53 00:10:00.420 ⇒ 00:10:00.750 Payas Parab: Okay.
54 00:10:00.750 ⇒ 00:10:09.280 Payas Parab: I promise. I’m just like I I just don’t like, I’ve been dropped like, just absolutely fumbling the bag here. So it’s like we need some. We need the big guns. Sorry, Robert. I know it’s a lot.
55 00:10:09.280 ⇒ 00:10:13.796 Payas Parab: No, you’re good shit being thrown your way, but there’s a point where we need the big guns.
56 00:10:14.330 ⇒ 00:10:26.210 Robert Tseng: I’m ready. Eden is in a better place now. So I’m good. Okay, well, let’s do this. So I mean, I’m just looking through all the messages there. So I mean.
57 00:10:28.170 ⇒ 00:10:33.390 Robert Tseng: yeah, I I understand there is a piece where, yeah, we just need a chase. We chase stakeholders is fine. I think
58 00:10:34.110 ⇒ 00:10:36.120 Robert Tseng: of things that I want to work on, that I’m
59 00:10:36.600 ⇒ 00:10:40.200 Robert Tseng: I I guess maybe it’d be helpful to talk through.
60 00:10:43.750 ⇒ 00:10:44.170 Robert Tseng: They kind of
61 00:10:44.580 ⇒ 00:10:52.819 Robert Tseng: what I think what what I think needs to be ready for the check in on Wednesday, when we resume meeting with them, and then we can. We can jump more details to the tickets. But
62 00:10:52.980 ⇒ 00:11:11.879 Robert Tseng: basically, I want to be able to communicate among. There’s this handoff going on. A lot of the same familiar faces, but just still letting them know. Not not to just be like, you know, looping pious into like chats without without anybody else, and reiterating that we can keep the communication in the in the channels that we’ve set up.
63 00:11:12.187 ⇒ 00:11:26.740 Robert Tseng: I understand that pies has been chasing a couple stakeholders on like their feedback. And so yeah, we just need a process where we’re literally just pinging them every day. And whether it’s coming from Nico, or if I’m gonna be hitting them like whatever it is like
64 00:11:27.490 ⇒ 00:11:36.150 Robert Tseng: to get them to respond. I think responsiveness has always been an issue with this client, so we need to make sure that that is clearly communicated to
65 00:11:37.005 ⇒ 00:11:42.710 Robert Tseng: I’m on Wednesday, and then I have like a queue of like things that I wanted to
66 00:11:43.630 ⇒ 00:11:46.560 Robert Tseng: to to talk about with him as like potential like
67 00:11:46.960 ⇒ 00:11:55.540 Robert Tseng: work. But I don’t really want to spend too much time on that today. I want to kind of like, figure out what needs to be tied up.
68 00:11:55.996 ⇒ 00:12:05.710 Robert Tseng: I feel like there’s still these 2 dashboards, gross margin and Amazon are like, kind of there, or like, yeah, what else do we need to like really
69 00:12:05.930 ⇒ 00:12:09.200 Robert Tseng: hand it off and see it be used? So.
70 00:12:10.050 ⇒ 00:12:12.050 Uttam Kumaran: Yeah, I think that’s where I would like to get.
71 00:12:12.555 ⇒ 00:12:14.270 Robert Tseng: Wanna get that figured out all right.
72 00:12:14.515 ⇒ 00:12:15.250 Robert Tseng: On this call.
73 00:12:17.292 ⇒ 00:12:19.899 Uttam Kumaran: So yeah, I’m in the same boat.
74 00:12:20.335 ⇒ 00:12:23.379 Robert Tseng: Jacob’s not here, but I guess.
75 00:12:24.850 ⇒ 00:12:25.600 Robert Tseng: Yeah, I kind of.
76 00:12:27.240 ⇒ 00:12:31.140 Robert Tseng: I met with Jacob last week. I reviewed a couple I don’t know.
77 00:12:31.743 ⇒ 00:12:32.346 Uttam Kumaran: Thanks.
78 00:12:33.430 ⇒ 00:12:37.910 Robert Tseng: Yeah, like, what? What else? What else is outstanding, or or or where am I caught up like I? I saw where he was.
79 00:12:37.910 ⇒ 00:12:42.569 Uttam Kumaran: So let’s let’s talk about the let’s talk about the gross margin first, st because I think that’s is that like
80 00:12:42.940 ⇒ 00:12:49.029 Uttam Kumaran: we’ve already handed that to them bias like, what are we waiting on them to basically give us the green light? So that’s just like a hound.
81 00:12:49.030 ⇒ 00:12:49.910 Uttam Kumaran: So situation.
82 00:12:49.910 ⇒ 00:12:52.469 Payas Parab: There. There’s like some small edits. Basically, there’s 2 2.
83 00:12:52.470 ⇒ 00:12:52.790 Payas Parab: Yeah
84 00:12:52.790 ⇒ 00:13:13.979 Payas Parab: on shopify. The numbers are more or less aligned. We have, like some small, quick call outs from Justin, jared has, like Jared has like never ever reviewed it and given us like thoughtful feedback. So Justin actually just stepped in and did it. So now Justin has given us like a clear set of asks on like what needs to get done. I think it’s all in the ticket, but I can clarify anything in there. Justin.
85 00:13:13.980 ⇒ 00:13:19.629 Robert Tseng: Yeah, no, I I saw the adjustments there, so I guess nobody’s picked us up yet. Is that where we’re at?
86 00:13:19.630 ⇒ 00:13:49.279 Payas Parab: I think Jacob’s gonna do it this morning. I I like, thought I could get to it. But I it’s it’s clear that it just needs to be transitioned off my plate because I just didn’t get to it. So yeah, gross margin, I think he’s gonna take over. There’s just 2 things that I would call out there. One is that like we have an underlying data issue with Amazon, too. We got all the skews for shopify. We got the numbers aligned in a way that Justin confirmed to make sense for Amazon. We’re still missing quite a lot of skews, and we have to chase down, Jonathan, for that is like the one big call out.
87 00:13:49.806 ⇒ 00:13:51.590 Payas Parab: That is like all the.
88 00:13:51.590 ⇒ 00:13:52.780 Uttam Kumaran: Who’s.
89 00:13:53.970 ⇒ 00:13:54.469 Payas Parab: See you all.
90 00:13:56.430 ⇒ 00:14:17.599 Payas Parab: They don’t have any like. They don’t have any. So just to be clear like this whole gross margin dashboard like where we came full circle. For everyone’s context is that like they wanted the data pulled out from amplitude and shopify turned out all that data is wrong. It’s all just based on, like back of the envelope, assumptions that are done in excel spreadsheets. We then set up an infrastructure for them to be able to upload everything into spreadsheets.
91 00:14:17.600 ⇒ 00:14:22.909 Payas Parab: And and now we’re like the we’re like, halfway there. With that, we’re just missing the Amazon data.
92 00:14:23.570 ⇒ 00:14:29.219 Payas Parab: That’s like kind of the state does that make sense like it’s just core assumption. They don’t have like an Amazon cost.
93 00:14:29.220 ⇒ 00:14:29.710 Payas Parab: Yeah, yeah.
94 00:14:29.710 ⇒ 00:14:32.219 Payas Parab: Logistics, fulfillment source of truth at all.
95 00:14:35.170 ⇒ 00:14:43.840 Uttam Kumaran: Okay. So I mean, I for me, the clear thing is just we just need to get get Jacob to be like, this is gonna be done today. So
96 00:14:44.595 ⇒ 00:14:56.699 Uttam Kumaran: looked at the ticket, too. It’s just like, so if if he can’t do it today, then we should pick it up and just try to get it done among this group. And then.
97 00:14:56.700 ⇒ 00:14:57.090 Robert Tseng: No.
98 00:14:57.090 ⇒ 00:14:57.510 Uttam Kumaran: Exactly.
99 00:14:57.940 ⇒ 00:14:58.570 Uttam Kumaran: Yeah.
100 00:14:59.200 ⇒ 00:15:14.372 Robert Tseng: I’m looking at the new client page on notion, like I do not know how I would go and find the tools that we’ve built for them. Aman has always asked for like links to every report, to every to the spreadsheets and stuff, and
101 00:15:17.140 ⇒ 00:15:24.440 Nicolas Sucari: We can add, we can add all the links to different spreadsheets on the links to the reports that they’re building. But if you go to resources.
102 00:15:25.590 ⇒ 00:15:27.999 Nicolas Sucari: client Page, you should have like a section there.
103 00:15:29.160 ⇒ 00:15:32.239 Nicolas Sucari: I I shared that with the man already, but if.
104 00:15:34.223 ⇒ 00:15:38.599 Uttam Kumaran: Okay, like, we can add it. We’ll be sure.
105 00:15:38.920 ⇒ 00:15:42.079 Uttam Kumaran: Yeah. So this resources page, I think we should be able to.
106 00:15:42.080 ⇒ 00:15:46.989 Nicolas Sucari: To review tickets internally, as the idea is to go in the data page.
107 00:15:48.430 ⇒ 00:15:49.570 Nicolas Sucari: Yeah. Sorry.
108 00:15:50.633 ⇒ 00:15:51.939 Uttam Kumaran: Go ahead!
109 00:15:51.940 ⇒ 00:15:53.160 Nicolas Sucari: I’m sorry. I think mine.
110 00:15:53.160 ⇒ 00:15:53.899 Uttam Kumaran: Kind of going gone.
111 00:15:53.900 ⇒ 00:15:54.810 Nicolas Sucari: There is.
112 00:15:59.800 ⇒ 00:16:05.829 Uttam Kumaran: Yeah, if you go within Javi, and then there’s just a resources thing on the left, which basically shows.
113 00:16:06.598 ⇒ 00:16:13.923 Uttam Kumaran: yeah, I mean, we can. If we don’t wanna move into the yeah, go ahead.
114 00:16:16.120 ⇒ 00:16:41.089 Nicolas Sucari: In the client view. We have these resources with everything that we have created for them. Like all of the real dashboards that we have the tool access links for everything. We have these we can add here all of the different links for the the reports that we are creating and anything else that we want. This is already shared with the man. And Robert, would you ask for the roadmap and timeline we have here
115 00:16:41.150 ⇒ 00:16:50.930 Nicolas Sucari: the actual tasks that they’re working on with the with each of their projects. In the timeline. This is all shared with a man right.
116 00:16:51.730 ⇒ 00:16:53.930 Robert Tseng: Yeah. So I guess you just need to
117 00:16:54.303 ⇒ 00:16:56.919 Robert Tseng: the tasks into this view every day.
118 00:16:57.400 ⇒ 00:17:01.710 Robert Tseng: Then any like nesting into like.
119 00:17:01.710 ⇒ 00:17:02.340 Uttam Kumaran: Why?
120 00:17:03.180 ⇒ 00:17:10.060 Robert Tseng: Like, if I’m in the mapping. If I’m like nesting these tasks into objectives like that’s not gonna be duplicated into the timeline view right?
121 00:17:12.630 ⇒ 00:17:32.229 Nicolas Sucari: These that this is a. So we need to talk about that because this one is the one that is getting duplicated, but the one that we have inside here. This is not getting duplicated. This is the actual, our actual database that has all of our tasks. How I’m handling this is, I don’t do anything here. I just go to the data homepage
122 00:17:34.340 ⇒ 00:17:40.070 Nicolas Sucari: and every task or every there is a property that’s called Javi coffee.
123 00:17:40.620 ⇒ 00:17:42.269 Uttam Kumaran: Project. I think.
124 00:17:42.820 ⇒ 00:17:43.740 Nicolas Sucari: And that’s how I.
125 00:17:43.740 ⇒ 00:17:46.219 Robert Tseng: Okay, okay, wait, hold on. So we we
126 00:17:46.620 ⇒ 00:17:56.190 Robert Tseng: it because we we just we don’t want to give him access to our database and like he can see all our other clients. Is that why? Because, like this is like so funky. I don’t understand. Okay.
127 00:17:56.460 ⇒ 00:18:06.289 Uttam Kumaran: Yeah. So there’s just no, there’s no so there’s no inbuilt process in notion to share, because all of our AI and our engineering tasks are just in one database.
128 00:18:06.470 ⇒ 00:18:17.740 Uttam Kumaran: We can’t share a view of it without. There’s just no functionality to do so. We’ve tried a couple of alternatives the way the place we arrived at is, we just clone it once a day to new area.
129 00:18:17.740 ⇒ 00:18:18.060 Robert Tseng: Okay.
130 00:18:18.950 ⇒ 00:18:22.160 Robert Tseng: Yeah, but we clone it. It doesn’t like, well, yeah, anyway, like the.
131 00:18:22.160 ⇒ 00:18:22.630 Uttam Kumaran: That’s
132 00:18:23.150 ⇒ 00:18:32.480 Uttam Kumaran: yeah, yeah. But I don’t. But I believe that that should all be possible to like the role of.
133 00:18:32.480 ⇒ 00:18:32.839 Robert Tseng: Oh, God!
134 00:18:32.840 ⇒ 00:18:41.190 Uttam Kumaran: Online view. That’s just another view of the tickets. So I don’t see why that’s not possible, Nico. I guess I don’t know if this joby project.
135 00:18:41.190 ⇒ 00:18:42.249 Nicolas Sucari: No, it is possible.
136 00:18:42.566 ⇒ 00:18:44.149 Uttam Kumaran: Yeah, yeah, no, that’s all.
137 00:18:44.150 ⇒ 00:18:45.450 Uttam Kumaran: It is possible.
138 00:18:45.450 ⇒ 00:18:53.759 Uttam Kumaran: But but I guess, like, I don’t know whether this joby project was like the best route. Okay.
139 00:18:53.760 ⇒ 00:19:10.680 Nicolas Sucari: Yeah, I mean, we we can find something another way around. The only thing is that if you don’t need to like you don’t want to maintain this every day, like adding to each of the projects and stuff. We need to just keep everything in one database and then just duplicate. Or, yeah, just copy that. That’s why I created.
140 00:19:10.680 ⇒ 00:19:11.010 Uttam Kumaran: Robert.
141 00:19:11.010 ⇒ 00:19:14.289 Nicolas Sucari: Over to here, and and we were managing like that.
142 00:19:15.530 ⇒ 00:19:23.800 Uttam Kumaran: Robert, give me the like the what would be the ideal view, and then we’ll try to get something to review today.
143 00:19:24.010 ⇒ 00:19:27.289 Robert Tseng: Yeah, I mean, I I think it’s it’s just the fact, all right. As long as.
144 00:19:27.290 ⇒ 00:19:27.790 Uttam Kumaran: It’s.
145 00:19:27.790 ⇒ 00:19:32.009 Robert Tseng: I know where I’m editing tickets and stuff like, yeah, the view.
146 00:19:32.010 ⇒ 00:19:32.650 Uttam Kumaran: Okay.
147 00:19:32.650 ⇒ 00:19:55.489 Robert Tseng: The tickets to roll up to the objectives, for, like the projects, or whatever the project, timeline needs to be shown to them, like, because, yeah, I think if I meet with them on Wednesday, I’m gonna reference that these are. This is the timeline. This is where we’re at these projects. We have capacity to take on 2 more like projects or whatever. And then I I wanna be able to like, use this as a resource on on that call.
148 00:19:55.780 ⇒ 00:19:58.979 Uttam Kumaran: Okay, okay? So Nico, let’s go. We’ll go through it today.
149 00:19:58.980 ⇒ 00:19:59.909 Robert Tseng: So one set, yeah, okay.
150 00:19:59.910 ⇒ 00:20:01.730 Uttam Kumaran: And then we’ll, and then we’ll make. We’ll make something happen.
151 00:20:01.730 ⇒ 00:20:03.210 Nicolas Sucari: Yeah, let’s go after the meeting.
152 00:20:05.000 ⇒ 00:20:05.610 Robert Tseng: Okay.
153 00:20:06.255 ⇒ 00:20:22.219 Robert Tseng: Okay. So that clears up the the gross margin stuff. And then the Amazon dash. I gave Jacob feedback on that. I think he made some edits and reviewed if he kind of sent them back. But okay, I think that’s that to me is those are the 2 outstanding analysis things.
154 00:20:25.680 ⇒ 00:20:28.110 Robert Tseng: Alright, I love it. Am I missing anything else?
155 00:20:28.110 ⇒ 00:20:28.720 Uttam Kumaran: Sure.
156 00:20:29.660 ⇒ 00:20:37.629 Payas Parab: On the Amazon one. There is a de task like a ticket for a vaish that I sent, that that one will be critical if we don’t solve that earlier, it’s gonna be a problem.
157 00:20:37.630 ⇒ 00:20:38.799 Robert Tseng: The healthy meeting.
158 00:20:39.020 ⇒ 00:20:48.879 Payas Parab: The Ltv thing. But the it’s the customer hashing. The customer. Id hashing isn’t working properly. So I think we’re gonna lose data the same way. Amplitude that’s like the core of what Justin needs is like.
159 00:20:49.520 ⇒ 00:20:58.459 Payas Parab: Amplitude is showing him that, like Amazon customers are only coming 2 or 3 times. But we know from the raw data he shared with us, that, like they have some customers buying like 10 times from Amazon.
160 00:20:58.980 ⇒ 00:21:01.150 Uttam Kumaran: So something in that customer id.
161 00:21:01.650 ⇒ 00:21:02.170 Payas Parab: Gosh
162 00:21:02.170 ⇒ 00:21:15.859 Payas Parab: is like a little off that, and that will that will drive this as well, so that that is like a dependency that we need to resolve first.st nico, I just pinged you at that, and Avesh, I sent you a loom kind of walking through the issue, and the snowflake queries. I was looking at.
163 00:21:17.510 ⇒ 00:21:19.518 Uttam Kumaran: Can you put the loom in this ticket.
164 00:21:22.260 ⇒ 00:21:22.810 Payas Parab: Yeah.
165 00:21:22.810 ⇒ 00:21:26.535 Uttam Kumaran: And then we’ll move it to plan. And then.
166 00:21:28.540 ⇒ 00:21:30.700 Uttam Kumaran: yeah, we should get this going.
167 00:21:36.330 ⇒ 00:21:41.803 Uttam Kumaran: But this is the resolve customer. Ltv Issues ticket.
168 00:21:42.530 ⇒ 00:21:52.199 Payas Parab: So it’s it’s the it’s part of the same thing. So Justin’s problem is amplitude. He doesn’t see the correct customer. Ltv, if you look at the screenshot, he said. It’s like
169 00:21:52.660 ⇒ 00:22:14.699 Payas Parab: it basically only shows like second or 3rd order, or it just shows like no orders. And then order number 8 or 9, and my belief is that it’s a customer id like stitching issue on amplitude side. But when I when I look at Snowflake on our side. I think we have the same issue where we’re not capturing repeat orders. Because the partial matching we found repeat orders so like something is off in the hashing.
170 00:22:15.280 ⇒ 00:22:21.620 Payas Parab: There’s like, sort of this, like hashing code that I like, take, like, yeah.
171 00:22:21.830 ⇒ 00:22:26.100 Awaish Kumar: I don’t think it’s because of hatching is. The problem is
172 00:22:26.340 ⇒ 00:22:31.239 Awaish Kumar: that the the code existing code code is fine
173 00:22:31.240 ⇒ 00:22:42.969 Awaish Kumar: for the for the dimension customer. We are selecting the customer id the email as a customer, Id, or the name combination of name and email as a customer. Id. But when we go to the orders table.
174 00:22:43.130 ⇒ 00:22:48.569 Awaish Kumar: a seller order Amazon seller, Id is being used as a customer. Id
175 00:22:48.670 ⇒ 00:22:54.489 Awaish Kumar: so like it doesn’t make sense like the seller is being selected as a customer.
176 00:22:55.650 ⇒ 00:23:00.739 Payas Parab: Oh, so that that’s like it was just like a bug from taking from intermediate to prod basically.
177 00:23:01.990 ⇒ 00:23:18.029 Awaish Kumar: Yeah, it seems like it. So if we want to like and there’s no like defined customers. Customer id from Amazon. So like we have to select customer id in both at both places, the same one which could be the email id in both places.
178 00:23:19.870 ⇒ 00:23:24.850 Payas Parab: I think the email Id is a good identifier, just like there are like, repeat customers, even though it’s hashed.
179 00:23:25.040 ⇒ 00:23:28.229 Payas Parab: It is like the correct. Repeat one, if you, in the.
180 00:23:28.230 ⇒ 00:23:30.449 Uttam Kumaran: You’re talking about. You’re really talking about this.
181 00:23:30.450 ⇒ 00:23:30.880 Payas Parab: Yeah, see?
182 00:23:30.880 ⇒ 00:23:31.770 Awaish Kumar: Yeah, I used.
183 00:23:33.790 ⇒ 00:23:41.349 Uttam Kumaran: And so given this context, you’re telling me that like this is like, not always filled or okay. Sorry.
184 00:23:41.640 ⇒ 00:23:43.000 Payas Parab: Yeah, that’s okay.
185 00:23:43.000 ⇒ 00:23:43.859 Uttam Kumaran: So, yeah.
186 00:23:45.170 ⇒ 00:23:54.980 Awaish Kumar: He. The problem is that in if you go into intermediate Amazon order table noted, I think, the
187 00:23:55.540 ⇒ 00:23:59.040 Awaish Kumar: the final one, the mark fact orders table.
188 00:24:02.930 ⇒ 00:24:07.579 Awaish Kumar: and if you see customer Id, the seller order, Id is being selected as a customer. Id.
189 00:24:08.350 ⇒ 00:24:10.640 Awaish Kumar: When we try to match the customer id.
190 00:24:14.930 ⇒ 00:24:15.440 Uttam Kumaran: Hmm!
191 00:24:16.250 ⇒ 00:24:18.060 Uttam Kumaran: So then we should just swap we should, you know.
192 00:24:18.060 ⇒ 00:24:20.909 Payas Parab: Yeah, that’s all it is. Then that’s all it is. Yeah, I couldn’t figure that out. But that
193 00:24:20.910 ⇒ 00:24:22.429 Payas Parab: that’s exactly what it is. Yeah.
194 00:24:26.390 ⇒ 00:24:28.585 Uttam Kumaran: Okay, I wish you wanna just rip this.
195 00:24:29.240 ⇒ 00:24:30.839 Awaish Kumar: Yeah, yeah, I will. Just.
196 00:24:33.610 ⇒ 00:24:39.919 Uttam Kumaran: Okay, then, in this ticket the the ticket. There’s a lot of other stuff, though, as there’s like
197 00:24:41.380 ⇒ 00:24:45.180 Uttam Kumaran: we should leverage dim customer for the source of truth.
198 00:24:45.180 ⇒ 00:24:45.770 Payas Parab: Yeah.
199 00:24:45.770 ⇒ 00:24:47.700 Uttam Kumaran: Will that, can I?
200 00:24:48.040 ⇒ 00:24:48.930 Uttam Kumaran: Yeah, I got it.
201 00:24:49.090 ⇒ 00:25:15.360 Payas Parab: If we solve this issue, I think it should be fine. We just have to confirm. Basically, we just need a sanity check at the end of like when we group by customer. Id, are we getting some rows with at least like at least like 10 or 12 like something like that, like the biggest customers, have brought purchase more than 10 times. We just need when we group by that and count the number of rows. It needs to be above 10. That’s the only sanity. Check the rest like the dim customer. All that. We’re just like me brainstorming solutions to it. But it seems that this is the core thing.
202 00:25:16.860 ⇒ 00:25:22.299 Payas Parab: It’s the customer wrong customer pulled in. Yeah, thank you. Avesh, for looking into that.
203 00:25:22.300 ⇒ 00:25:23.359 Payas Parab: Appreciate it, man.
204 00:25:23.750 ⇒ 00:25:35.195 Uttam Kumaran: Yeah. And the easiest thing is like, yeah, nice thing is all just code. So I think popping up the github and being like where? Because we had a couple of these where it’s like, yeah, one column just needs to be changed. So
205 00:25:36.005 ⇒ 00:25:36.410 Uttam Kumaran: okay.
206 00:25:45.627 ⇒ 00:25:46.762 Uttam Kumaran: a sec.
207 00:25:48.349 ⇒ 00:25:52.890 Uttam Kumaran: We probably dodged like a 3 h meeting on this. So that’s great.
208 00:25:53.290 ⇒ 00:25:54.159 Uttam Kumaran: It’s cool.
209 00:25:54.160 ⇒ 00:26:01.800 Awaish Kumar: What should we be doing for the customers where it’s where we don’t have the email like it’s not. And it’s a lot of.
210 00:26:01.800 ⇒ 00:26:05.693 Uttam Kumaran: Yeah, what do you wanna do? Pies?
211 00:26:06.520 ⇒ 00:26:07.280 Uttam Kumaran: Okay.
212 00:26:07.280 ⇒ 00:26:07.900 Payas Parab: So are we.
213 00:26:07.900 ⇒ 00:26:10.531 Uttam Kumaran: For the folks that don’t have an email.
214 00:26:10.860 ⇒ 00:26:17.550 Payas Parab: When we don’t have an email, we can use we can use the address. I think we can just create a hash of the address itself.
215 00:26:17.993 ⇒ 00:26:25.780 Payas Parab: I think something like that will be the best one I can brainstorm on that. i. 1 thing I wanted to note is that full name is not a good one, because
216 00:26:26.590 ⇒ 00:26:34.860 Payas Parab: can be the same customer, and their names look slightly different in Amazon, and shopify, which is what we found through the partial matching. So like, we might need, yeah. Shipping address name
217 00:26:35.370 ⇒ 00:26:37.570 Payas Parab: might not be the one. It might be a dress and.
218 00:26:37.570 ⇒ 00:26:38.640 Uttam Kumaran: What’s it like.
219 00:26:38.640 ⇒ 00:26:40.349 Payas Parab: Street number plus zip code.
220 00:26:40.350 ⇒ 00:26:42.220 Uttam Kumaran: I think would be like a reasonable one.
221 00:26:42.220 ⇒ 00:26:43.699 Payas Parab: We we’d have to play around with that.
222 00:26:43.840 ⇒ 00:26:44.910 Uttam Kumaran: But for the.
223 00:26:45.210 ⇒ 00:26:47.930 Payas Parab: For the ones where there isn’t 1 for now, just put.
224 00:26:48.040 ⇒ 00:26:51.510 Payas Parab: I think address should be okay. Address and Zip.
225 00:26:52.636 ⇒ 00:26:53.353 Uttam Kumaran: Okay.
226 00:26:58.080 ⇒ 00:26:58.830 Awaish Kumar: Okay.
227 00:26:59.450 ⇒ 00:27:02.030 Payas Parab: And that should only occur on the Fba. Orders. Right.
228 00:27:04.017 ⇒ 00:27:13.863 Uttam Kumaran: Yeah, exactly. Okay, cool. Let’s do this. This will solve a bunch of problems. Seems pretty easy.
229 00:27:16.536 ⇒ 00:27:23.341 Uttam Kumaran: Oh, wait. I’m gonna put today. You can get into beyond.
230 00:27:27.900 ⇒ 00:27:36.096 Uttam Kumaran: If you, I’m gonna put today as a due date, if you can. If you try to give it a go, we can review it today later.
231 00:27:39.430 ⇒ 00:27:41.626 Uttam Kumaran: Okay, cool.
232 00:27:45.180 ⇒ 00:27:58.910 Uttam Kumaran: that’s really like, I mean, apart from that, those are like the main things, right? We have resolved customer where me and away. So working on Northeas, and gorgeous still like with portable Amazon and gross margin, so.
233 00:27:58.910 ⇒ 00:28:01.070 Payas Parab: 1 1 i see missing Tiktok
234 00:28:01.990 ⇒ 00:28:04.320 Payas Parab: Tiktok direct integration with Via Portable.
235 00:28:04.680 ⇒ 00:28:05.819 Payas Parab: We’re gonna follow up.
236 00:28:06.720 ⇒ 00:28:07.380 Uttam Kumaran: We.
237 00:28:07.380 ⇒ 00:28:12.979 Nicolas Sucari: We have that task there, but I don’t know. If that’s possible. We need to look into that one. I think.
238 00:28:14.230 ⇒ 00:28:21.420 Uttam Kumaran: Okay, let me. Yeah, I’m gonna move this into plan and we’ll get a timeline from port from portable.
239 00:28:21.420 ⇒ 00:28:41.949 Payas Parab: It’s just justin. Justin looked at like our Tiktok version from like our workaround. And he’s like that looks off. And we’re probably gonna need the true tick tock data. He’s like that. The Tiktok stuff looks a little off. I can’t remember off top my head exactly what he said, but he’s like some of this order, like the order, discounts and stuff applied isn’t accurately reflected in shopify data set.
240 00:28:41.950 ⇒ 00:28:42.500 Uttam Kumaran: Got it.
241 00:28:43.370 ⇒ 00:28:44.220 Payas Parab: So yeah.
242 00:28:44.750 ⇒ 00:28:54.620 Payas Parab: like, like, there’s like additional discounts that tick tock then applies with, like its own optimization that aren’t being captured. And what we see in the shopify like total line items minus total discounts.
243 00:29:00.290 ⇒ 00:29:00.990 Uttam Kumaran: Okay.
244 00:29:01.210 ⇒ 00:29:05.779 Robert Tseng: What else needs to be done for the handoff of the matching the Geo matching.
245 00:29:07.240 ⇒ 00:29:10.380 Payas Parab: Yeah, so we basically
246 00:29:10.480 ⇒ 00:29:32.710 Payas Parab: like we did it like on like a 1 time basis. But it seems that it’s a recurring task. And for Justin and Blake it would be a big help if we basically like deploy it to a stream. Lit. App is kind of my thought process is whatever matching code we have, he can upload like a Tplix export, or whatever the fuck that software is called that basically finds addresses for people once they order even when their identity and email is hidden.
247 00:29:32.790 ⇒ 00:29:44.770 Payas Parab: And you basically would upload it. And we would just give them an output of all the shopify matched email addresses. So there’s sort of like, that’s the main task there now. The next step is like we did on a 1 time basis. We need to do it on a
248 00:29:45.050 ⇒ 00:29:55.879 Payas Parab: like in an easy way for him to be able to repeatedly do that. And my thought process is a streamlit app connected to a snowflake database where he can upload a Csv and then get the outputs with the shopify emails.
249 00:29:57.360 ⇒ 00:29:59.880 Uttam Kumaran: Is there a ticket for that?
250 00:30:01.756 ⇒ 00:30:03.040 Uttam Kumaran: Okay? Okay, yeah. Just that.
251 00:30:03.040 ⇒ 00:30:04.050 Uttam Kumaran: The only you just put away.
252 00:30:04.050 ⇒ 00:30:19.450 Payas Parab: The only one. Yeah, that one. I I think if you know how to make a streamlit app, I can like quickly walk you through what we need to do there. But it’s also like, so the matching code is a little bit like all over the place. So I can also help transition that it’s like it’s like a giant Jupyter notebook with a bunch of like small cleanups.
253 00:30:19.880 ⇒ 00:30:21.439 Robert Tseng: I feel like Boca. Do this, too.
254 00:30:22.090 ⇒ 00:30:22.740 Payas Parab: Yeah.
255 00:30:22.740 ⇒ 00:30:23.479 Robert Tseng: What do you think?
256 00:30:24.460 ⇒ 00:30:34.937 Uttam Kumaran: Yeah. Yeah. Just put it into plan. And then let’s see. Okay, yeah.
257 00:30:37.200 ⇒ 00:30:45.590 Uttam Kumaran: I don’t think, okay. Okay, okay, cool. How do we feel?
258 00:30:46.460 ⇒ 00:30:46.850 Uttam Kumaran: Bye?
259 00:30:47.240 ⇒ 00:30:49.080 Uttam Kumaran: Better? Yeah, yeah, better.
260 00:30:51.320 ⇒ 00:30:52.099 Robert Tseng: Yeah, we can move on.
261 00:30:52.758 ⇒ 00:30:56.425 Uttam Kumaran: Okay, let’s look, okay.
262 00:31:05.890 ⇒ 00:31:06.825 Uttam Kumaran: yeah.
263 00:31:11.375 ⇒ 00:31:12.220 Uttam Kumaran: Okay.
264 00:31:16.240 ⇒ 00:31:21.007 Uttam Kumaran: okay, so let’s talk about Eden.
265 00:31:23.383 ⇒ 00:31:36.680 Uttam Kumaran: there’s there’s 2 things. One is he? There were some tickets on here, Robert, that were marked as blocked on the business reporting and the the scheduled product report
266 00:31:37.351 ⇒ 00:31:42.589 Uttam Kumaran: are those up for review, or they is this still? Is this like isn’t on?
267 00:31:43.880 ⇒ 00:31:44.380 Uttam Kumaran: Let’s see.
268 00:31:47.540 ⇒ 00:31:55.439 Robert Tseng: we’re basically just like not continuing with those because we’re moving into into tableau. So maybe like, yeah, I can update this. But
269 00:31:56.100 ⇒ 00:32:00.569 Robert Tseng: like we’re not. I’m not. Gonna we’re not gonna keep building more reports until we finish that. Well.
270 00:32:02.320 ⇒ 00:32:07.660 Uttam Kumaran: Okay. Then I’m just gonna I’ll just move it to. Won’t do.
271 00:32:08.660 ⇒ 00:32:09.040 Robert Tseng: Okay.
272 00:32:10.220 ⇒ 00:32:12.602 Uttam Kumaran: This is off the the table.
273 00:32:19.080 ⇒ 00:32:24.800 Uttam Kumaran: This one, I mean. I guess we have the we, only we’re only powering the one view right.
274 00:32:25.180 ⇒ 00:32:25.810 Robert Tseng: Yep.
275 00:32:26.161 ⇒ 00:32:35.119 Uttam Kumaran: Do we want to consider this done, or how do you like you still wanna go? I mean, I guess this is where I want to talk.
276 00:32:35.640 ⇒ 00:32:36.180 Uttam Kumaran: Yeah.
277 00:32:36.180 ⇒ 00:32:44.513 Robert Tseng: We’ve pushed it to staging we need to update it to like their nor their like, their their production. One
278 00:32:47.610 ⇒ 00:32:48.803 Robert Tseng: I guess.
279 00:32:50.700 ⇒ 00:33:00.319 Robert Tseng: I mean, I was just gonna ask Zack to do it, but I guess. But we mean if we want to maintain we want. I don’t know if I want to maintain this dashboard moving forward. But
280 00:33:01.880 ⇒ 00:33:09.690 Uttam Kumaran: I think so. I think I think 2 things, one on the on the data inside. We want to push that Pr to prod, and then
281 00:33:10.950 ⇒ 00:33:18.852 Uttam Kumaran: basically be like product sales. Summary and fraud is good to use.
282 00:33:22.645 ⇒ 00:33:27.679 Uttam Kumaran: I mean, yeah, I guess, like, I mean, I would just throw it to Zack.
283 00:33:30.500 ⇒ 00:33:56.549 Robert Tseng: Yeah, what I didn’t like about last time was that when he updated it with the product sales summary, he like messed up a bunch of stuff like he just like just like lazily did it. And then we got all the flack for it, so part of me would prefer to take it on but we’re also moving away from this dashboard. So I don’t want us to go and like update like everything, and like to see they have like 5 tabs on this dashboard. We just have to update, maybe the main one and then be able to field some questions there.
284 00:33:58.480 ⇒ 00:34:13.379 Uttam Kumaran: I think we should, I think. Well, maybe you can take that on. And then because, yeah, basically like, but like, why can’t we? Just why can’t we just clone the one in staging and just replace the data source
285 00:34:13.870 ⇒ 00:34:15.834 Uttam Kumaran: record studio. Now.
286 00:34:19.330 ⇒ 00:34:23.149 Robert Tseng: But yeah, I don’t. I don’t know how that works. I had to. I had to rebuild it manually pretty much.
287 00:34:23.904 ⇒ 00:34:24.460 Uttam Kumaran: Well.
288 00:34:24.469 ⇒ 00:34:29.749 Robert Tseng: Like I I did clone this. I cloned the original one, and then I like stripped out some stuff to create that view and staging.
289 00:34:32.010 ⇒ 00:34:32.905 Uttam Kumaran: Okay.
290 00:34:33.800 ⇒ 00:34:38.420 Bo Yoon: So is this marketing dashboard, the one that is on Looker studio that we’re talking about.
291 00:34:38.780 ⇒ 00:34:39.755 Uttam Kumaran: Performance.
292 00:34:40.739 ⇒ 00:34:44.399 Robert Tseng: Yeah, you know what we we should. We should own it because of if both is gonna answer
293 00:34:44.400 ⇒ 00:34:48.859 Robert Tseng: same question questions on marketing like we should. It’s just all gonna come out of there, anyway. So.
294 00:34:51.520 ⇒ 00:34:54.044 Uttam Kumaran: Okay. So then, how about for this one?
295 00:34:56.870 ⇒ 00:34:57.635 Uttam Kumaran: There you go.
296 00:34:58.180 ⇒ 00:35:02.809 Uttam Kumaran: But if you go into off well, I’ll push this Pr.
297 00:35:02.960 ⇒ 00:35:06.729 Uttam Kumaran: And then I’ll tell you where the table is, and then.
298 00:35:06.730 ⇒ 00:35:07.130 Bo Yoon: Okay.
299 00:35:07.130 ⇒ 00:35:09.858 Uttam Kumaran: Basically the goal, the goal will be to.
300 00:35:11.620 ⇒ 00:35:18.460 Uttam Kumaran: yeah, basically migrate. I mean, I guess there’s 2 options, one, you can migrate the existing. Or you can like, clone the staging
301 00:35:18.920 ⇒ 00:35:23.457 Uttam Kumaran: and replace. I don’t really know what’s like, hard or not.
302 00:35:28.440 ⇒ 00:35:38.056 Uttam Kumaran: yeah, I don’t know. Maybe Robert, like you guys should meet and like to see what’s the easiest, because I don’t know. I know you created a bunch of new measures and stuff, so maybe easier to just.
303 00:35:39.003 ⇒ 00:35:46.560 Uttam Kumaran: It may be easier to just clone what you did. If there’s an option to clone that whole asset and swap the data source because the columns will be the same.
304 00:35:46.870 ⇒ 00:35:47.930 Robert Tseng: Yeah.
305 00:35:49.300 ⇒ 00:35:49.845 Bo Yoon: Okay.
306 00:36:03.880 ⇒ 00:36:05.189 Uttam Kumaran: Okay, cool.
307 00:36:05.530 ⇒ 00:36:06.240 Uttam Kumaran: Good.
308 00:36:07.500 ⇒ 00:36:10.770 Uttam Kumaran: Yeah. This would be great to just like, put a wrap on.
309 00:36:20.270 ⇒ 00:36:29.559 Robert Tseng: Well, you guys keep like changing the the planning board on this in Eden. And like, I want all the groups shown like I I just. I like the timeline view.
310 00:36:29.670 ⇒ 00:36:33.540 Robert Tseng: like I literally just went through all this like 30 min ago, and then, now wait, wait, wait!
311 00:36:33.540 ⇒ 00:36:34.150 Robert Tseng: Selected again.
312 00:36:35.830 ⇒ 00:36:36.750 Uttam Kumaran: Wait! What?
313 00:36:37.440 ⇒ 00:36:39.050 Uttam Kumaran: What do you mean? No, this is this is.
314 00:36:39.050 ⇒ 00:36:39.810 Nicolas Sucari: Nothing changed.
315 00:36:39.810 ⇒ 00:36:40.500 Uttam Kumaran: Data.
316 00:36:43.790 ⇒ 00:36:47.339 Robert Tseng: This is like, yeah, yeah. Why.
317 00:36:48.530 ⇒ 00:37:17.180 Robert Tseng: yeah, I know you’re using the data homepage. But like, I’m in the Eden. q 1 like page. And like, 30 min ago I had all of my groups visible and then, now it’s all like hidden again. And it’s okay. It’s fine. It’s like, if you didn’t. If no one touched anything, it’s not a big deal, but I just I I’m just saying like I don’t use your project management dashboard. I pop into every client, and I like the timeline view, for, like the the Kanban view, so that’s how I go in and move tickets around.
318 00:37:21.491 ⇒ 00:37:35.389 Uttam Kumaran: Is there anything else on even like there’s the key dashboards. I think I want to talk about the Geolift Project.
319 00:37:35.540 ⇒ 00:37:36.233 Uttam Kumaran: I know.
320 00:37:36.580 ⇒ 00:37:41.200 Robert Tseng: Yeah, there’s a there’s a ton of. There’s a ton of stuff. I.
321 00:37:41.200 ⇒ 00:37:42.080 Uttam Kumaran: Cool.
322 00:37:42.590 ⇒ 00:37:46.049 Robert Tseng: I want to show. Okay? Well, I
323 00:37:46.230 ⇒ 00:37:50.130 Robert Tseng: oh, oh, I’m gonna I wanna take over so.
324 00:37:50.130 ⇒ 00:37:50.850 Uttam Kumaran: Yeah.
325 00:37:51.130 ⇒ 00:37:51.710 Robert Tseng: Yeah.
326 00:37:52.230 ⇒ 00:37:53.550 Robert Tseng: Okay. So
327 00:37:56.590 ⇒ 00:38:12.059 Robert Tseng: urgent things to me. One, we need to push that marketing campaign labeling strategy out to cutter’s team. Based on what we got from your buddy, Ben. I’m gonna go rework that spreadsheet. Send that over to Cutter. Tell him like this is how you need to push the the teams to implement ads in the future.
328 00:38:12.150 ⇒ 00:38:30.130 Robert Tseng: and then we need to kick off the segment event implementation. They don’t have an engineer who’s doing event tracking, so it’ll likely be me who’s like, gonna be instrumenting the events, or at least I’m gonna go into segment and and at least get that started. And if it’s easy to hand off, I’ll probably hand that off. Otherwise, like I may have to be the one to just do that
329 00:38:30.792 ⇒ 00:38:47.817 Robert Tseng: couple of things that we were reviewing. We have this like, when I meet. I meet with them weekly on Thursday. And by Thursday, I wanna have like that data strategy view where I show them the architecture diagram. I’m kind of calling it
330 00:38:50.025 ⇒ 00:38:51.290 Robert Tseng: like
331 00:38:51.460 ⇒ 00:39:09.633 Robert Tseng: the Dfd to visualize data movement kind of thing where we have some new artifact and figma, or something that’s like this, with the the spreadsheet of costs so that we can break down every tool cost to for and and to forecast that cost out.
332 00:39:10.020 ⇒ 00:39:33.830 Robert Tseng: yeah, I think that to me is like the key strategy thing that I want to present on by Thursday, and then on the engineering side, I don’t really know what this product data. dB, is. I think it’s related to the march that you guys are kind of thinking about. So it seems like, there’s some data mark thing that you have to do. And then also, we want to start getting zendesk data in so Sahana can start using it by next week.
333 00:39:33.960 ⇒ 00:39:34.960 Robert Tseng: Ideally.
334 00:39:35.906 ⇒ 00:39:56.390 Robert Tseng: so yeah. And then there’s some more hipaa hipaa stuff that I’m pushing along. We’re like 30% of the way to hipaa compliance. And I’ve I’ve that timeline is like a whole a whole quarter. So yeah, I think. Yeah, there’s a lot of stuff that I’ve kind of put into plan for the week. And I’m yeah. This is kind of where we’re at right now.
335 00:39:58.430 ⇒ 00:40:09.009 Uttam Kumaran: So for the Zendesk, yeah, I created, there’s 2 tickets. There’s 1 for the ingestion. There’s 1 for the data modeling. We didn’t talk about like what we’re gonna use for, Etl, like, what do you want us
336 00:40:10.890 ⇒ 00:40:14.276 Uttam Kumaran: like? What what they were using airbite before.
337 00:40:14.700 ⇒ 00:40:15.220 Robert Tseng: Oh! So!
338 00:40:15.220 ⇒ 00:40:17.609 Uttam Kumaran: I’d rather not. Yeah.
339 00:40:17.610 ⇒ 00:40:20.010 Robert Tseng: They were using airbite to Etl for what.
340 00:40:20.800 ⇒ 00:40:32.030 Uttam Kumaran: It seems like well, I I don’t know. It seems like there’s some air bites in there, so I assume they tried to. Someone just tried to rip air by free. I don’t know, Bo. Do you know, like what they were using for Etl before?
341 00:40:32.200 ⇒ 00:40:33.200 Uttam Kumaran: For each.
342 00:40:33.680 ⇒ 00:40:35.600 Bo Yoon: I have no idea.
343 00:40:36.070 ⇒ 00:40:37.729 Bo Yoon: Think that will be a question for.
344 00:40:37.730 ⇒ 00:40:40.560 Robert Tseng: Everybody thinks actually being used. Yeah.
345 00:40:40.950 ⇒ 00:40:45.590 Uttam Kumaran: So then we need. So we need to make a decision on you like. So our options are.
346 00:40:46.020 ⇒ 00:40:50.142 Uttam Kumaran: I mean, I would just rather just go with portable and just kind of call it.
347 00:40:52.170 ⇒ 00:41:02.859 Robert Tseng: Yeah, I mean, I, I kind of saw this as like, this is what we did for Stella. We just need to get all Zendesk data in, and then just apply the same kind of modeling so that we can build a similar kind of support dashboard for them.
348 00:41:04.070 ⇒ 00:41:13.710 Uttam Kumaran: Okay, I guess. Do you have any restrictions on? If we go if we go with portable? And that’s gonna be, that’s gonna I mean they’re gonna have to pay. It’s not that bad, but.
349 00:41:15.616 ⇒ 00:41:19.870 Robert Tseng: Do they do the trial thing like we did with Zendesk?
350 00:41:20.260 ⇒ 00:41:22.079 Robert Tseng: Or do we have to just pay out the gate.
351 00:41:22.470 ⇒ 00:41:27.900 Uttam Kumaran: Well, yeah, yeah, no. They’ll they’ll start. They’ll start and get us the data first.st
352 00:41:28.250 ⇒ 00:41:28.590 Robert Tseng: Okay.
353 00:41:28.590 ⇒ 00:41:29.440 Uttam Kumaran: A decision.
354 00:41:30.630 ⇒ 00:41:40.740 Robert Tseng: Yeah, I feel like, let’s just do that. I also don’t know. I have to show them like how much they’re. They don’t know how much they’re spending on data tools right now. They think it’s a lot. And that’s why I need that breakdown for them.
355 00:41:41.319 ⇒ 00:41:52.049 Uttam Kumaran: Okay. Okay. So then I’m gonna kick off. So we’re gonna let’s kick off I’ll meet with the portable guys we’ll kick off ingestion of I also.
356 00:41:53.240 ⇒ 00:42:00.989 Uttam Kumaran: yeah, I mean, we we should do the same north beam, because I don’t. Where the I don’t know where the coming from right now.
357 00:42:04.010 ⇒ 00:42:05.000 Robert Tseng: I?
358 00:42:06.130 ⇒ 00:42:07.329 Robert Tseng: Yeah, I don’t know. You can’t.
359 00:42:07.330 ⇒ 00:42:08.552 Uttam Kumaran: I don’t know.
360 00:42:08.960 ⇒ 00:42:10.029 Robert Tseng: Yeah, I feel like.
361 00:42:10.030 ⇒ 00:42:10.660 Uttam Kumaran: Okay.
362 00:42:10.660 ⇒ 00:42:13.080 Robert Tseng: This is this is your domain. I have no idea how.
363 00:42:13.080 ⇒ 00:42:29.079 Uttam Kumaran: Sorry. Sorry. Yeah, okay, great. So we’ll we’ll just move everything to portable. Yeah, I’m sort of like, you know that me where it’s like, it’s a 2 Indian guys are like no longer friends, you know. That’s how I am with 5 grand
364 00:42:29.880 ⇒ 00:42:49.090 Uttam Kumaran: so we are team portable these days. And in about 6 months we won’t use anything. We’ll be writing all this stuff. Cool. We’ll we’ll get started on on that picked up this week, and then, yeah, they’ll let us run for free until we
365 00:42:49.488 ⇒ 00:42:51.581 Uttam Kumaran: can get the check signed so
366 00:42:52.190 ⇒ 00:43:04.750 Uttam Kumaran: and then, can I? Can I? We just spend like one second reviewing the architecture, diagram, and like what you would what you would need, Robert, for this to actually be like
367 00:43:05.620 ⇒ 00:43:07.015 Uttam Kumaran: and useful.
368 00:43:12.040 ⇒ 00:43:12.830 Uttam Kumaran: okay.
369 00:43:12.830 ⇒ 00:43:15.769 Robert Tseng: Oh, yeah, I guess I could reshare screen here.
370 00:43:15.890 ⇒ 00:43:17.110 Robert Tseng: Oh, you got it okay.
371 00:43:17.110 ⇒ 00:43:24.669 Uttam Kumaran: Oh, yeah, yeah, like from you. Tell me what you need from your side. I left some comments.
372 00:43:25.020 ⇒ 00:43:30.560 Uttam Kumaran: I mean, I left a bunch of comments basically being like so.
373 00:43:30.560 ⇒ 00:43:32.130 Awaish Kumar: Actually, it’s rather portable than 5.
374 00:43:32.480 ⇒ 00:43:35.439 Awaish Kumar: We don’t know what is the sync frequencies. Right?
375 00:43:38.850 ⇒ 00:43:40.280 Uttam Kumaran: Yeah, yeah, but I guess.
376 00:43:40.280 ⇒ 00:43:47.345 Robert Tseng: What a wish is saying is necessary, like, we need to know like data freshness, like, how often the the data is coming in.
377 00:43:48.560 ⇒ 00:43:50.910 Robert Tseng: alright hey? Guess like.
378 00:43:50.910 ⇒ 00:43:58.379 Uttam Kumaran: I guess, like this is, this is sort of like, I think this is getting better. But basically, I was like, I want to put down the department.
379 00:43:58.680 ⇒ 00:44:12.689 Uttam Kumaran: Gorgeous reviews, recharge subscriptions. I then also want the data model separated by like the domain, because they’re not gonna really understand what like factor them, or whatever is basically, it’s like
380 00:44:12.920 ⇒ 00:44:15.830 Uttam Kumaran: we have tables in these categories.
381 00:44:16.354 ⇒ 00:44:25.675 Uttam Kumaran: Otherwise, I think this is pretty good. And then what I’m gonna do, Robert is. As soon as we go to place, I’ll ship it to design to be like. Make it look nicer.
382 00:44:26.200 ⇒ 00:44:31.819 Robert Tseng: Cool. Yeah, no, I mean, I I agree with you being able to break it down by department or function will be helpful.
383 00:44:32.290 ⇒ 00:44:34.639 Robert Tseng: because then on a weekly basis.
384 00:44:34.980 ⇒ 00:44:35.320 Uttam Kumaran: Like.
385 00:44:35.320 ⇒ 00:44:51.760 Robert Tseng: On Wednesdays. We have like leadership team, every team, every department head kind of talks about like how they’re training. And I want to be able to show them the available data. They have to be able to measure their stuff. So if I can as well, sales is talking, and I can flash them like this is all the sales data you have.
386 00:44:52.570 ⇒ 00:44:59.589 Robert Tseng: I. I don’t think sales is the right term, because this is not really b 2 b saas, but but anyway, like, yeah, just being able to.
387 00:44:59.880 ⇒ 00:45:05.080 Robert Tseng: I can give you what those different departments are. I.
388 00:45:05.860 ⇒ 00:45:12.110 Uttam Kumaran: And do you think like these table names like are helpful? Do you think we should just put like
389 00:45:13.557 ⇒ 00:45:17.712 Uttam Kumaran: more like descriptive name? Which is, it would be like orders.
390 00:45:19.550 ⇒ 00:45:27.009 Robert Tseng: Well, I guess this is also this doubles as a resource for us. So like, I’m fine with just keeping it like this. And like, yeah. So
391 00:45:27.770 ⇒ 00:45:31.730 Robert Tseng: we should do whatever makes the most sense that’s most helpful for us. Yeah.
392 00:45:32.050 ⇒ 00:45:41.446 Uttam Kumaran: I wanna land in the middle. Because again, this goes to our thing of like for the mid engagement meetings. We create these assets, but then it helps us with docs like,
393 00:45:42.750 ⇒ 00:46:02.940 Uttam Kumaran: But our our repo is already organized, basically in this way, with like the different domains. So it’s not that bad. But yeah, basically, I want us to just have the business use cases for for each of these tools. And then, yeah, the models are more descriptive. So yeah, I think the way you have, you have what’s remaining here? And so that meetings on went on
394 00:46:03.230 ⇒ 00:46:03.900 Uttam Kumaran: Thursday.
395 00:46:05.280 ⇒ 00:46:28.830 Robert Tseng: Yeah, I mean by Thursday would be ideal. I mean, if we could get it by Wednesday, like, I can show it to the teams at the offsite right now, I’m sure we’ll kinda be great. Have by Wednesday. But yeah, so every department head should be able to see like what data they have available to them. And then I think what the leadership will care about most is like how the data is being pushed into the bi tools that they’re using because they have so many different things downstream.
396 00:46:28.950 ⇒ 00:46:39.420 Robert Tseng: And we’re trying to like push them towards consolidation or like, show them like which tools use for what like? I don’t think they care so much about what’s happening, like, you know, from
397 00:46:39.600 ⇒ 00:46:43.480 Robert Tseng: raw to the data warehouse like nobody will really pay attention to that.
398 00:46:44.310 ⇒ 00:46:44.880 Uttam Kumaran: Okay.
399 00:46:45.220 ⇒ 00:46:45.790 Robert Tseng: Yeah.
400 00:46:46.790 ⇒ 00:46:54.269 Uttam Kumaran: Okay, cool. So I think as you’re going in and looking at the data marks, if you can just work on that, and then we can plan on looking at that before Thursday.
401 00:46:55.890 ⇒ 00:46:56.930 Uttam Kumaran: I don’t know. It’s.
402 00:46:57.215 ⇒ 00:46:57.500 Awaish Kumar: Yeah.
403 00:46:59.050 ⇒ 00:46:59.640 Robert Tseng: Okay.
404 00:47:03.850 ⇒ 00:47:04.559 Nicolas Sucari: Who’s all over that?
405 00:47:07.000 ⇒ 00:47:14.489 Nicolas Sucari: Sorry? Yeah, on on that same architecture diagram for Javi, we have to set up this, the like, the recurring syncing
406 00:47:14.680 ⇒ 00:47:19.660 Nicolas Sucari: from portable. Because we right now, we just have, like an initial sync right.
407 00:47:20.330 ⇒ 00:47:27.530 Uttam Kumaran: Well, it’s a well, we haven’t finished the like bringing all the data in, so I can’t have them pay for it like, it’s the same problem.
408 00:47:27.830 ⇒ 00:47:34.260 Uttam Kumaran: So we had on. We don’t have north beam yet, and we’re still waiting on gorgeous. So I’m not gonna pay for it until they can accomplish that.
409 00:47:35.120 ⇒ 00:47:39.790 Uttam Kumaran: Yeah. So, yes, thank you.
410 00:47:40.840 ⇒ 00:47:52.140 Robert Tseng: Okay, yeah, we’re talking. I mean, rob is officially paused now. So I don’t know if you needed to ask him any questions about like stuff. You could probably still shoot him a message. But just letting you know he’s not really around anymore. So.
411 00:47:52.140 ⇒ 00:47:54.330 Uttam Kumaran: Okay, yeah, that’s fine.
412 00:47:54.590 ⇒ 00:47:57.730 Uttam Kumaran: Yeah. Now that oasis here, I feel a lot more comfortable.
413 00:47:58.360 ⇒ 00:47:59.040 Robert Tseng: Okay.
414 00:48:00.125 ⇒ 00:48:00.890 Robert Tseng: I guess. Like.
415 00:48:00.890 ⇒ 00:48:01.240 Uttam Kumaran: Okay, so.
416 00:48:01.240 ⇒ 00:48:06.270 Robert Tseng: Boe has. This has the the marketing dashboard kind of getting that
417 00:48:06.620 ⇒ 00:48:19.530 Robert Tseng: production wise. So like we already have the staging stuff that we shared out, it’d be good for him to familiarize himself with the product sales summary model and like the data that’s there. Then he also has his geolift analysis study I still like don’t really know.
418 00:48:19.530 ⇒ 00:48:19.850 Uttam Kumaran: Yeah.
419 00:48:19.850 ⇒ 00:48:24.330 Robert Tseng: Really slot that into like the priorities. So okay, bye.
420 00:48:24.330 ⇒ 00:48:37.834 Robert Tseng: frankly, like, I I mean, why, anyway. So I I think maybe I can meet with Bo later on this. But I don’t really think that I mean, we’ll we’ll see. I think there’s a lot of stuff that’s gonna that’s going off this week already. But
421 00:48:38.110 ⇒ 00:48:38.440 Bo Yoon: Yeah.
422 00:48:38.440 ⇒ 00:48:40.340 Robert Tseng: Yeah, we’ll we’ll have to. We’ll see. There.
423 00:48:41.650 ⇒ 00:48:44.730 Uttam Kumaran: I think definitely getting, yeah, go ahead.
424 00:48:45.903 ⇒ 00:48:51.919 Bo Yoon: I’m not even really sure if they still want it or not, because it was Stuart and Carter who wanted it in
425 00:48:53.140 ⇒ 00:48:53.730 Bo Yoon: it. Really.
426 00:48:53.730 ⇒ 00:48:58.050 Robert Tseng: Yeah, I mean, I would probably pause it. Then, yeah, okay.
427 00:48:58.430 ⇒ 00:49:02.820 Uttam Kumaran: Yeah, so thanks stuff. And then I think the tableau stuff is next basically.
428 00:49:02.930 ⇒ 00:49:03.490 Robert Tseng: Yeah.
429 00:49:04.050 ⇒ 00:49:04.390 Bo Yoon: Okay.
430 00:49:04.855 ⇒ 00:49:05.320 Uttam Kumaran: Alright.
431 00:49:06.968 ⇒ 00:49:16.220 Uttam Kumaran: but I do think it’s probably best rather than you guys meet for like 30 today, there’s there’s like a ton of stuff. But again, ideally, we slot Boeing on.
432 00:49:16.640 ⇒ 00:49:24.240 Uttam Kumaran: We have the farm Ops, analytics, and all the stuff that Sahan is taking everything on the marketing side. And then a wish will basically build the marts.
433 00:49:24.580 ⇒ 00:49:27.807 Uttam Kumaran: and that puts us in a good mood. I think.
434 00:49:30.510 ⇒ 00:49:33.800 Robert Tseng: Yeah, there’s definitely more marketing stuff that we can queue up. And so I think.
435 00:49:33.800 ⇒ 00:49:35.159 Uttam Kumaran: Yeah, there’s a ton of market.
436 00:49:35.160 ⇒ 00:49:48.625 Robert Tseng: I want to get. I want I want to. I want Bo and I to spend time with like Mattesh and Cutter. Mattesh is their Cmo, so I think I wanna like I kind of know what’s on their roadmap, and I have some ideas for them. But
437 00:49:49.020 ⇒ 00:49:53.290 Robert Tseng: yeah, anyway, we’ll we’ll we’ll kind of try to figure that out.
438 00:49:54.120 ⇒ 00:49:54.810 Uttam Kumaran: Okay.
439 00:49:55.060 ⇒ 00:49:55.870 Bo Yoon: Yeah, sure.
440 00:49:56.182 ⇒ 00:50:03.687 Uttam Kumaran: I I know we’re coming up on time. I just wanted to spend time with Paul Pie, sister on pool parts sack Blitz, and
441 00:50:04.551 ⇒ 00:50:18.680 Uttam Kumaran: I feel comfortable with we already kind of covered this morning. But can we talk to Nico any other? Any questions you had on cool parts for what needs to be done, and that involves cool part that involves Bo as well. So I wanna try to hand off execution to those.
442 00:50:20.149 ⇒ 00:50:20.849 Uttam Kumaran: Yeah.
443 00:50:21.930 ⇒ 00:50:23.719 Nicolas Sucari: Let me bring that up again.
444 00:50:25.493 ⇒ 00:50:28.079 Nicolas Sucari: But yeah, on pool parts. We have
445 00:50:28.540 ⇒ 00:50:34.660 Nicolas Sucari: this queue analysis stuff yet. There, I asked. Maybe you can give an update there. We already
446 00:50:35.230 ⇒ 00:50:35.700 Nicolas Sucari: got it.
447 00:50:35.700 ⇒ 00:50:36.080 Payas Parab: Yeah, we.
448 00:50:36.080 ⇒ 00:50:38.120 Nicolas Sucari: 20 skews, but we need to share that out right.
449 00:50:38.980 ⇒ 00:50:43.420 Payas Parab: Yeah, we need to share that out. And then our discussion with Ian, we sort of had like a
450 00:50:43.820 ⇒ 00:50:52.040 Payas Parab: like, basically like on the data they have. There’s just like some hard limitations that even Ian has tried to play around with, that we sort of need to voice to Dan as well.
451 00:50:52.533 ⇒ 00:51:01.509 Payas Parab: I think the the top 20 identifying the top, 20 skews filling in the costs we’ve done, and then we did do the
452 00:51:01.850 ⇒ 00:51:13.110 Payas Parab: like. All the stuff from the spreadsheet cleaned up to their master skew list. So those 2 things are done. I do have to double check what that sales data integration is. So I can take a double click at that right now, and just make sure
453 00:51:13.180 ⇒ 00:51:24.910 Payas Parab: that’s on track or what it is. But yeah, the other thing is is like launching. Now that we have Bo on board as well, we’re gonna have sort of like a collaborative effort to do some exploratory data analysis, and like a very like.
454 00:51:24.910 ⇒ 00:51:45.170 Payas Parab: like a more methodical way, and also giving time to both like Bo is staffed on a lot of new projects as well, so he’ll he’ll have some breathing room around like these 2 week sprints to do some Eda. So that’s sort of yeah, everything, is there. I just got to double check the sales data integration. I like just blanking. So let me offline. Do that and send a ping right after this.
455 00:51:45.870 ⇒ 00:51:46.470 Uttam Kumaran: Okay.
456 00:51:46.470 ⇒ 00:51:50.989 Payas Parab: 20 skews is done. Yeah, top 20 skews is done, and the the integration is done.
457 00:51:53.730 ⇒ 00:51:58.999 Uttam Kumaran: Okay? And then, so, Nico, are you? Gonna are you gonna email them back? Are you gonna take that.
458 00:51:59.150 ⇒ 00:52:01.216 Uttam Kumaran: What’s that communication for those.
459 00:52:01.630 ⇒ 00:52:14.810 Nicolas Sucari: I think, apart from email them back, I asked the spreadsheet that we have with all of the information we should get some time with Ian and Dan in a meeting, and go through what will be like the next steps on the skew cleanup. What do you think.
460 00:52:15.730 ⇒ 00:52:34.540 Payas Parab: Yeah, let’s do that. Let’s nico, let’s let’s chat like me. And you today, just like on. And Bo, actually as well, just to like get on the same page. Because I I just haven’t touched that since. I like rebalance to Javi. So let’s just like maybe rally today at some point midday Pacific, and just quickly cash through without taking everyone’s time here.
461 00:52:36.010 ⇒ 00:52:44.420 Luke Daque: That also being said, can we like, maybe? Or do we still need the Sq data cleanup that’s in the backlog that’s still assigned to me
462 00:52:45.020 ⇒ 00:52:45.940 Luke Daque: cause that’s the related.
463 00:52:45.940 ⇒ 00:52:56.449 Nicolas Sucari: Yeah, yeah, we should change this. Yeah, this is the old one, like the one that have that we were going to review with these snowflake functions. How to clean that up
464 00:52:56.900 ⇒ 00:53:02.200 Nicolas Sucari: I don’t know. If this is already. It’s also needed now, or which you can just like delete it.
465 00:53:02.570 ⇒ 00:53:05.070 Payas Parab: I I think you should. I think we should like deprioritize that.
466 00:53:05.070 ⇒ 00:53:05.560 Uttam Kumaran: And Domain.
467 00:53:05.560 ⇒ 00:53:17.779 Payas Parab: One thing I would focus on is the that, like the data issue, like it is, I, I confirmed. It’s like definitely between 5 Tran and our snowflake, whatever is putting it in Snowflake. So like, we need to figure out that one, because.
468 00:53:18.450 ⇒ 00:53:22.800 Payas Parab: yeah, that one’s probably the top priority, because I think that one impacts the net profit margin. Dash.
469 00:53:23.490 ⇒ 00:53:24.230 Payas Parab: That’s it. For.
470 00:53:24.230 ⇒ 00:53:24.940 Nicolas Sucari: Hey? Man.
471 00:53:25.980 ⇒ 00:53:26.510 Nicolas Sucari: Okay.
472 00:53:26.510 ⇒ 00:53:29.809 Uttam Kumaran: Yes, let’s just close the sku cleanup one
473 00:53:29.930 ⇒ 00:53:34.289 Uttam Kumaran: and then just move this one to plan the the data discrepancy.
474 00:53:35.830 ⇒ 00:53:44.500 Uttam Kumaran: I mean, yeah, I think. Let’s just get movement on this this week. Let’s leave any of the Eda stuff, for as soon as we like. Feel good about cogs
475 00:53:45.070 ⇒ 00:53:48.809 Uttam Kumaran: like that’s the number. One thing I want to clear before we try to take on more stuff.
476 00:53:52.720 ⇒ 00:53:57.680 Uttam Kumaran: Okay, cool. So stack splits. I think we’re. I’m pretty comfortable with. And then urban stems will kick off next week.
477 00:53:57.900 ⇒ 00:53:59.850 Uttam Kumaran: I think we’re pretty good for today.
478 00:54:02.733 ⇒ 00:54:06.279 Uttam Kumaran: Anything else we want to to chat about.
479 00:54:07.750 ⇒ 00:54:13.989 Uttam Kumaran: Ohish! How do you feel there’s a lot on your plate for Eden and Javi. But just checking. If you’re okay.
480 00:54:14.971 ⇒ 00:54:19.219 Awaish Kumar: Yeah, it’s I’m just working on Edin right now.
481 00:54:22.930 ⇒ 00:54:31.270 Awaish Kumar: and yeah, it’s it’s okay. I think, I will need some context, and I may be ping you or the.
482 00:54:32.470 ⇒ 00:54:36.939 Uttam Kumaran: That’s ping ping me, ping, ping me in the in the client channel.
483 00:54:38.860 ⇒ 00:54:44.140 Uttam Kumaran: anything on the data modeling side. It’s a really messy right now their warehouse. So we just need to like.
484 00:54:44.540 ⇒ 00:54:54.570 Uttam Kumaran: basically get everything into our stuff and then just start like archiving and cycling and put their stuff in another area and sort of dropping data sets because there’s super messy. Ideally, we end up with, just like
485 00:54:54.710 ⇒ 00:55:00.851 Uttam Kumaran: our schemas prod staging dev Martz intermediate.
486 00:55:02.360 ⇒ 00:55:11.490 Awaish Kumar: Okay, and like the the right. Now, the Dbt, the repository we have cause this
487 00:55:12.192 ⇒ 00:55:16.729 Awaish Kumar: like the taken from the client? Or is it like the.
488 00:55:16.730 ⇒ 00:55:17.250 Uttam Kumaran: It’s ours.
489 00:55:17.250 ⇒ 00:55:19.359 Awaish Kumar: The enforce team, built it from scratch.
490 00:55:19.820 ⇒ 00:55:21.260 Uttam Kumaran: Rebuilt different structures.
491 00:55:22.250 ⇒ 00:55:27.589 Awaish Kumar: Okay, so the all the models are there right now. These are built by the by Us. Right.
492 00:55:27.590 ⇒ 00:55:32.725 Uttam Kumaran: No. So the that’s a good question. So the models that are in
493 00:55:35.820 ⇒ 00:55:40.599 Uttam Kumaran: So the models that are let me show you.
494 00:55:45.010 ⇒ 00:55:52.739 Luke Daque: Like over 90% of those are like was just copy pasted from their views, and like scheduled queries.
495 00:55:53.460 ⇒ 00:55:53.860 Awaish Kumar: Okay.
496 00:55:55.070 ⇒ 00:56:00.431 Uttam Kumaran: But there’s like, I think there’s a few March models that we created there. Utah, right? Like the product.
497 00:56:00.700 ⇒ 00:56:21.139 Uttam Kumaran: This is just. It’s just like we should have, we should just put this in. It’s just not clear for a wish which one of these are ours. So which I’m gonna send you which one are ours, and then, if you can just like move their stuff to like a different, you could leave it in March, but, like, put it into a subfolder. Basically, we inherited like
498 00:56:21.930 ⇒ 00:56:27.130 Uttam Kumaran: 15 or 20 of these, the biggest thing that we worked on is orders.
499 00:56:27.620 ⇒ 00:56:32.999 Uttam Kumaran: transactions, and the product sales summary, which are all in Pr, basically.
500 00:56:33.813 ⇒ 00:56:37.640 Uttam Kumaran: I’ll tell. So I’ll tell you. It’s basically if you look at this. VR,
501 00:56:38.540 ⇒ 00:56:44.978 Uttam Kumaran: anything that touches this is ours. Now, like I worked. I worked our way all the way back to transactions
502 00:56:45.850 ⇒ 00:56:51.370 Uttam Kumaran: to the raw basketor, completed the raw Google sheets and then created orders. Now.
503 00:56:51.780 ⇒ 00:56:56.370 Uttam Kumaran: I haven’t deleted their their stuff because they’re still pulling from it, so I can’t.
504 00:56:56.690 ⇒ 00:57:02.692 Uttam Kumaran: I don’t know yet whether I can get rid of their old orders, so we have some
505 00:57:03.610 ⇒ 00:57:13.785 Uttam Kumaran: that’s some stuff for you to figure out like I don’t know where you can look at Bigquery and see if the orders is getting queried before we can archive it. But ideally, this replaces their orders.
506 00:57:20.480 ⇒ 00:57:23.020 Uttam Kumaran: Okay, let’s lock me today. Yeah, I’m on.
507 00:57:23.300 ⇒ 00:57:24.189 Uttam Kumaran: Thank you.
508 00:57:25.060 ⇒ 00:57:30.349 Uttam Kumaran: Okay, cool guys. Well, yeah, let’s keep talking slack. I’ll be online
509 00:57:30.660 ⇒ 00:57:32.630 Uttam Kumaran: rest of the day. And then, yeah, I guess
510 00:57:33.557 ⇒ 00:57:37.420 Uttam Kumaran: for even stuff. I guess both you and Robert just let me know if I can help.
511 00:57:40.460 ⇒ 00:57:43.060 Uttam Kumaran: Alright, guys, thank you.
512 00:57:43.710 ⇒ 00:57:44.040 Robert Tseng: Yep.
513 00:57:44.040 ⇒ 00:57:45.550 Uttam Kumaran: Yeah, it’s a lot of other people.
514 00:57:46.270 ⇒ 00:57:46.776 Bo Yoon: Thank you.