Meeting Title: Data Team Planning Session Date: 2025-01-22 Meeting participants: Luke Daque, Nicolas Sucari, Uttam Kumaran, Payas Parab, Robert Tseng, Sahana Asokan
WEBVTT
1 00:04:04.640 ⇒ 00:04:05.720 Nicolas Sucari: Hi Robert!
2 00:04:09.470 ⇒ 00:04:10.420 Robert Tseng: And you go.
3 00:04:12.180 ⇒ 00:04:12.979 Nicolas Sucari: How are you?
4 00:04:14.160 ⇒ 00:04:15.270 Robert Tseng: Good! How are you?
5 00:04:17.040 ⇒ 00:04:17.910 Nicolas Sucari: I’m good.
6 00:04:45.340 ⇒ 00:05:03.163 Robert Tseng: Oh, I just saw your messages on cost. I’ll respond, yeah, I mean, generally, yeah, you’re right on Meta base. Meta base is pretty straightforward amplitude. It’s hard to estimate. We’re gonna have to just look at the client bills because it’s not as simple as just 61 per user per month.
7 00:05:05.080 ⇒ 00:05:15.990 Robert Tseng: yeah, it kind of it depends on what features they’re using. I mean, the starter plan is free. They have, like a scholarship tier as well. So startups in their 1st year, basically have have it for free
8 00:05:16.595 ⇒ 00:05:20.949 Robert Tseng: but yeah, plus and anything more than that, it’s pretty custom.
9 00:05:22.070 ⇒ 00:05:22.720 Nicolas Sucari: Okay?
10 00:05:32.240 ⇒ 00:05:37.189 Nicolas Sucari: And for metabase we always run, or usually run with the starter right?
11 00:05:37.590 ⇒ 00:05:45.059 Robert Tseng: Yeah, it’s been starter. I mean, Stella had more than 5 users, so they were paying more than 85
12 00:05:46.098 ⇒ 00:05:50.380 Robert Tseng: but Javi should be 85. And yeah, I mean.
13 00:05:50.380 ⇒ 00:05:50.970 Nicolas Sucari: Yeah, yeah.
14 00:05:51.980 ⇒ 00:05:54.469 Nicolas Sucari: Could be less. That’s the price for
15 00:05:54.994 ⇒ 00:05:58.540 Nicolas Sucari: like month to month. Contract right? Like not paying annually.
16 00:05:58.540 ⇒ 00:06:04.009 Robert Tseng: It could be less. And if we don’t use cloud, then we also save. But we’re using.
17 00:06:06.290 ⇒ 00:06:13.210 Robert Tseng: But yeah, I think the biggest cost center isn’t really in the analytics tool. It’s more in
18 00:06:13.920 ⇒ 00:06:24.229 Robert Tseng: the connectors. So the 5 tran or with each segment. So that’ll be expensive. I think they’re paying something like 40 KA year for that
19 00:06:24.861 ⇒ 00:06:30.999 Robert Tseng: but I guess we’ll have to get you to look at the bill to to see that.
20 00:06:31.940 ⇒ 00:06:32.590 Nicolas Sucari: Okay.
21 00:06:36.570 ⇒ 00:06:37.750 Robert Tseng: Hey, Tom!
22 00:06:37.750 ⇒ 00:06:43.790 Uttam Kumaran: Hey? Thank you. Guys, let’s get started. Nico.
23 00:06:44.960 ⇒ 00:06:51.719 Nicolas Sucari: Yeah. Okay. I don’t know if no bias is not here and how to. But let’s start maybe talking about
24 00:06:51.980 ⇒ 00:06:57.079 Nicolas Sucari: work on Stagley with them today as you. And look at here.
25 00:06:57.550 ⇒ 00:07:02.060 Uttam Kumaran: Cool. So on. Stacklets. Yesterday
26 00:07:02.936 ⇒ 00:07:08.400 Uttam Kumaran: set up snowflake. So made some healthy changes to our
27 00:07:09.011 ⇒ 00:07:20.160 Uttam Kumaran: snowflake script as well. So some updates, also about how to create users programmatically. So basically, whenever we create a new snowflake, you can basically run this whole script
28 00:07:20.350 ⇒ 00:07:26.509 Uttam Kumaran: to create everything and create users. And it makes everything really easy. We also
29 00:07:28.740 ⇒ 00:07:38.489 Uttam Kumaran: also, as part of this process, we’re using key pair off for everything for service accounts. So there’s instructions already there. Just nice thing of that. I run right through it again and have some cleanup.
30 00:07:38.660 ⇒ 00:07:46.769 Uttam Kumaran: So that’s done. Polytomic setup. The warehouse is done. So let’s just mark polytomic as done.
31 00:07:48.730 ⇒ 00:08:00.740 Uttam Kumaran: So I am currently in process of getting creds for segment and hubspot. So so segment is gonna happen via polytomic postgres gonna happen hubspot. They have a direct connector. So we’re gonna go direct
32 00:08:03.460 ⇒ 00:08:10.340 Uttam Kumaran: And then, yeah, I’ll basically probably hand off a lot of the initial modeling work to look
33 00:08:12.330 ⇒ 00:08:15.810 Robert Tseng: Sorry you said they use polytomic with segment.
34 00:08:16.170 ⇒ 00:08:17.790 Uttam Kumaran: Polytomic is like 5 tran.
35 00:08:18.980 ⇒ 00:08:24.019 Robert Tseng: Okay, yeah, so I mean, does that functionality? So what do they even use segment for.
36 00:08:24.020 ⇒ 00:08:27.470 Uttam Kumaran: I think they well, they use segment for all their event, tracking.
37 00:08:28.210 ⇒ 00:08:28.720 Robert Tseng: Okay.
38 00:08:29.030 ⇒ 00:08:36.130 Uttam Kumaran: And yeah, I think they they. We talked about how segment has like the ability to go native to the warehouse, but
39 00:08:36.240 ⇒ 00:08:38.409 Uttam Kumaran: I don’t think they paid for it, or there was.
40 00:08:39.110 ⇒ 00:08:40.914 Uttam Kumaran: I have to look back through my notes.
41 00:08:41.140 ⇒ 00:08:43.859 Robert Tseng: Yeah, they’re probably just using the unified product. Okay.
42 00:08:44.600 ⇒ 00:08:50.369 Robert Tseng: I’m assuming they use polytomic for reverse, Etl, too, then. But I don’t use segment, Etl at all.
43 00:08:51.050 ⇒ 00:08:51.660 Uttam Kumaran: Yeah.
44 00:08:51.990 ⇒ 00:08:52.660 Robert Tseng: Okay.
45 00:08:56.290 ⇒ 00:08:56.740 Nicolas Sucari: Cool.
46 00:08:57.034 ⇒ 00:09:05.280 Uttam Kumaran: So yeah, this should be. This should be good. Ideally, I wanna get our 1st model like a couple of models in by the end of the week.
47 00:09:05.990 ⇒ 00:09:10.960 Uttam Kumaran: These guys also, like we have a good opportunity to shape what bi tool they use.
48 00:09:12.350 ⇒ 00:09:12.940 Robert Tseng: Great.
49 00:09:13.130 ⇒ 00:09:25.049 Uttam Kumaran: So let’s see, I mean, I’m gonna I’m gonna just we’re gonna ship rail, as we usually do, and then kind of see what they what they want to do overall. The other thing is, these guys just raise like a ton of money. So.
50 00:09:25.050 ⇒ 00:09:30.780 Robert Tseng: Yeah, wait. Did they actually just raise their series? B, or is that okay?
51 00:09:32.990 ⇒ 00:09:37.389 Uttam Kumaran: So I don’t know. Maybe we could probably talk about this on a sales meeting, but, like
52 00:09:38.070 ⇒ 00:09:45.269 Uttam Kumaran: the I don’t know like I’m I don’t know. I feel like I’m very plugged in on the AI side like bolt is probably like
53 00:09:45.620 ⇒ 00:09:46.829 Uttam Kumaran: a top 10
54 00:09:46.950 ⇒ 00:09:51.769 Uttam Kumaran: company in on AI twitter right now. So like we should use it for more sales stuff.
55 00:09:54.479 ⇒ 00:09:59.870 Uttam Kumaran: they’re gonna be really big. So cool. Yeah. So I feel good about these guys so far.
56 00:10:00.710 ⇒ 00:10:01.690 Uttam Kumaran: pretty standard.
57 00:10:02.220 ⇒ 00:10:03.010 Robert Tseng: Nice.
58 00:10:03.010 ⇒ 00:10:03.630 Luke Daque: Cool.
59 00:10:04.799 ⇒ 00:10:09.080 Robert Tseng: Just a quick update on the Dbt core initialization as well. I already
60 00:10:09.910 ⇒ 00:10:16.090 Luke Daque: Created the Pr for that. Just a basic blank template for our Dbt project and stuff. But
61 00:10:16.220 ⇒ 00:10:19.810 Luke Daque: yeah, like, like Bhutan mentioned once, we should be able to like
62 00:10:19.980 ⇒ 00:10:21.899 Luke Daque: start working on the data models
63 00:10:22.060 ⇒ 00:10:24.330 Luke Daque: as soon as we get the sources and stuff.
64 00:10:28.250 ⇒ 00:10:29.479 Nicolas Sucari: Perfect. Okay, so.
65 00:10:29.480 ⇒ 00:10:34.939 Uttam Kumaran: Like. What do you? What do you think about timing for that, Luke? Is that today.
66 00:10:36.210 ⇒ 00:10:38.009 Luke Daque: The the data models. You mean.
67 00:10:38.010 ⇒ 00:10:41.570 Uttam Kumaran: Just for like setting up Dvc core profiles, and then like
68 00:10:42.770 ⇒ 00:10:45.470 Uttam Kumaran: getting some initial something to run.
69 00:10:48.960 ⇒ 00:10:53.770 Luke Daque: Yeah, sure, I can do that. Just I already have the template
70 00:10:53.970 ⇒ 00:11:01.320 Luke Daque: setup, or like the Pr, basically. And yeah, just need to set up the profiles, and then we should be good.
71 00:11:01.960 ⇒ 00:11:05.880 Uttam Kumaran: Yeah, you can set up profile. And then just yeah, just run like a select
72 00:11:06.070 ⇒ 00:11:08.439 Uttam Kumaran: one or something and create a model.
73 00:11:08.730 ⇒ 00:11:09.410 Luke Daque: Okay.
74 00:11:10.287 ⇒ 00:11:11.180 Luke Daque: I don’t know.
75 00:11:11.680 ⇒ 00:11:17.510 Uttam Kumaran: I’m not sure yet when these this stuff is gonna load in.
76 00:11:18.640 ⇒ 00:11:20.030 Luke Daque: Yeah, sure.
77 00:11:23.440 ⇒ 00:11:24.590 Nicolas Sucari: Okay, cool.
78 00:11:25.680 ⇒ 00:11:33.710 Nicolas Sucari: Thanks, guys, let’s go to Eden. Maybe as we have Sahana here. Oh, Payas is here, too.
79 00:11:36.530 ⇒ 00:11:38.579 Nicolas Sucari: Let’s go to even yeah.
80 00:11:51.250 ⇒ 00:11:53.910 Nicolas Sucari: Sorry. My computer is slow. I’m sharing.
81 00:12:04.730 ⇒ 00:12:06.190 Nicolas Sucari: Here. We go. Okay,
82 00:12:08.760 ⇒ 00:12:13.499 Nicolas Sucari: So Sahana, do you wanna give an update on what you’ve been working on for these ones?
83 00:12:14.040 ⇒ 00:12:31.850 Sahana Asokan: Yeah. So the tracking plan and the data model was done last week. So that’s ready for review. So for this week I was able to build out the v 1 of the daily snapshot dashboard and made the fixes that Robert had any of the feedback. That’s all
84 00:12:31.960 ⇒ 00:12:36.969 Sahana Asokan: changed. And then I was also able to get the marketing dashboard up and running
85 00:12:37.352 ⇒ 00:13:04.209 Sahana Asokan: and then I think there was a bunch of different tickets for the executive dashboard like breaking it out by like cogs, revenue, profit, etc. I didn’t realize we had created tickets for all of them. So I actually just went ahead and created all the different areas of the business, and like a specific template in that executive dashboard that I linked out in the revenue dash ticket, Robert. So.
86 00:13:04.210 ⇒ 00:13:05.000 Robert Tseng: He’s okay.
87 00:13:05.380 ⇒ 00:13:22.759 Sahana Asokan: Yeah, I didn’t realize we actually broke it up. So I kind of just spend a bunch of time and got it done. And then we can build on it as we go. But yeah, the the baseline templates are the baseline dashboards are essentially done. It’s just kind of like, the the next steps are like, how do we build on this?
88 00:13:22.870 ⇒ 00:13:25.799 Sahana Asokan: And yeah, so that’s kind of the updates for this week.
89 00:13:26.530 ⇒ 00:13:27.060 Robert Tseng: Okay.
90 00:13:27.060 ⇒ 00:13:31.489 Nicolas Sucari: Okay, so do you want me to move all of these ones to? In review, too.
91 00:13:32.420 ⇒ 00:13:48.099 Sahana Asokan: Yeah, I think. Let’s let’s do it because the cogs of the marketing are both done. I have 2 different versions of marketing just based on. I think, Robert, you had created a fake jam design for the marketing one. So that’s what I went off of. But I also created another one. So we can.
92 00:13:49.320 ⇒ 00:13:55.090 Robert Tseng: Yeah, I just put that one together because they wanted to talk about it. So I just like bumped it up to get it quick.
93 00:13:55.663 ⇒ 00:13:59.789 Robert Tseng: But yeah, I think like, as I posted in the Channel, like.
94 00:14:00.100 ⇒ 00:14:02.840 Robert Tseng: basically, I mean, I understand that.
95 00:14:03.453 ⇒ 00:14:20.746 Robert Tseng: Guess I haven’t reviewed like the full executive dash design that you want that you did. But I figured that that’s quite. I just tried to pick like the one thing that we needed to be able to show this week. And I think it’s just that on the mark for the marketing side. It’s just that product level.
96 00:14:21.740 ⇒ 00:14:29.859 Robert Tseng: it’s like product by membership type. And then a few of these metrics. So that’s the that’s the view that I shared with the with the team yesterday.
97 00:14:29.860 ⇒ 00:14:36.593 Sahana Asokan: Yeah. So I think that’s where we need to build out membership type. I think right. And then we also
98 00:14:37.080 ⇒ 00:14:47.270 Sahana Asokan: just based off what you build. That’s all done in that in the, in the link that is in the marketing dash ticket. I think the only next step is like we don’t have.
99 00:14:47.470 ⇒ 00:14:55.460 Sahana Asokan: We have data around campaign. But I’m not really seeing a lot of stuff, for I think, Channel. So we might want to confirm that.
100 00:14:57.180 ⇒ 00:14:58.000 Robert Tseng: Yeah,
101 00:14:59.500 ⇒ 00:15:13.306 Robert Tseng: I’m not too worried about kind of getting the channel and campaign thing right for this right now. They’re using north beam reporting. And that seems to kind of do the job. I think we yeah, we need to inherit it in eventually. But
102 00:15:13.890 ⇒ 00:15:15.629 Robert Tseng: yeah, I think that’s
103 00:15:16.230 ⇒ 00:15:20.099 Robert Tseng: yeah. We? We may not, we might not be able to finish. That. This week is kind of my point.
104 00:15:20.100 ⇒ 00:15:22.950 Sahana Asokan: Okay, yeah. Then everything else is kind of
105 00:15:23.150 ⇒ 00:15:28.230 Sahana Asokan: done. And then, based on what you think, we can make changes. But the chunk of the work is done.
106 00:15:28.560 ⇒ 00:15:34.419 Robert Tseng: Okay, yeah, I’ll look into all this stuff in details. Thanks. Thanks for thanks for the update.
107 00:15:34.580 ⇒ 00:15:35.150 Sahana Asokan: Yeah.
108 00:15:38.370 ⇒ 00:15:43.780 Nicolas Sucari: Thank you. Okay. Luke, Uten, do you wanna update something about the product data mapping stuff.
109 00:15:46.220 ⇒ 00:15:52.425 Uttam Kumaran: Yes, I think last I mean, last, our update was is, we couldn’t push the Pr without
110 00:15:53.320 ⇒ 00:15:56.330 Uttam Kumaran: those values. I think we’re still blocked there.
111 00:15:57.320 ⇒ 00:16:02.299 Robert Tseng: I think we should be good now. I was on with Rob yesterday to kind of
112 00:16:02.590 ⇒ 00:16:12.569 Robert Tseng: finish it, so I can kind of walk you through what the mapping looks like now. But but yeah, we can. We can meet afterwards, too.
113 00:16:12.740 ⇒ 00:16:17.080 Uttam Kumaran: Yeah, maybe let’s let’s just go through everything. And then, yeah, that’s the only item
114 00:16:17.600 ⇒ 00:16:21.849 Uttam Kumaran: on our side. Is there, are there any other modeling items that we’re behind on.
115 00:16:23.680 ⇒ 00:16:42.400 Robert Tseng: Well, I’m assuming that once this product and mapping things in there, then we will be able to break out every product by membership type which will be helpful for the for the marketing view. We should be able to do product level like revenue. And I think they updated cogs. Yeah, they updated cogs, too. So
116 00:16:45.660 ⇒ 00:16:47.189 Robert Tseng: not every. Okay.
117 00:16:47.580 ⇒ 00:16:50.010 Robert Tseng: Yeah. So
118 00:16:50.960 ⇒ 00:17:09.599 Robert Tseng: yeah, we don’t have to make every report related to product. Well, segment. I just want to be able to demo the product segmentation like capability by like this week when I check in with them tomorrow. So I think whether we demo that on the revenue side or the marketing side doesn’t really matter. Whichever one we can get to first.st
119 00:17:11.160 ⇒ 00:17:15.539 Uttam Kumaran: Okay, so let’s just do product level revenue.
120 00:17:16.319 ⇒ 00:17:19.399 Uttam Kumaran: And now let’s just me, and we’ll we’ll get something out
121 00:17:20.609 ⇒ 00:17:24.430 Uttam Kumaran: by tomorrow so that you can see it as oh, you! You’re gonna present tomorrow.
122 00:17:25.270 ⇒ 00:17:28.339 Robert Tseng: Yeah, we have, like our one month check in tomorrow. So.
123 00:17:28.349 ⇒ 00:17:34.349 Uttam Kumaran: So let’s do it today. Then we’ll get something. Today we’ll check. Once we finish the product mapping, we’ll get something out for this today.
124 00:17:35.040 ⇒ 00:17:35.790 Robert Tseng: Okay.
125 00:17:36.490 ⇒ 00:17:44.309 Robert Tseng: yeah, the product level marketing stuff is pretty much like, I mean, it’d be great if we could get both. But yeah.
126 00:17:44.690 ⇒ 00:17:56.840 Robert Tseng: cause all the metrics should already be there. I just need to. I just need to look over. Make sure that the Ltv makes sense, because I think Sauna had some questions around that then for roast, but all the other like
127 00:17:58.690 ⇒ 00:18:06.420 Robert Tseng: like pack, and few of those other metrics, I think, should be
128 00:18:08.790 ⇒ 00:18:20.879 Robert Tseng: well, yeah. So like, if we yeah, well, so this, the product level product by membership revenue and then product by membership. And then a few of those like marketing costs. Otherwise the product by
129 00:18:21.180 ⇒ 00:18:29.330 Robert Tseng: product, by membership. Revenue is really just like one or 2 fields. Right? So I think we could do a little more than that.
130 00:18:29.700 ⇒ 00:18:30.420 Uttam Kumaran: Okay.
131 00:18:30.420 ⇒ 00:18:31.050 Robert Tseng: Yeah.
132 00:18:39.840 ⇒ 00:18:40.460 Nicolas Sucari: Great
133 00:18:40.460 ⇒ 00:18:48.640 Nicolas Sucari: cool. Anything else on Eden. We have the both app, but which I don’t know if you were able to meet with him to go through that.
134 00:18:48.640 ⇒ 00:18:51.780 Uttam Kumaran: Let’s keep. Yeah, let’s keep going. I don’t have time.
135 00:18:55.380 ⇒ 00:19:02.230 Nicolas Sucari: Perfect. Okay, cool. If nothing else on Eden, I think. That’s okay.
136 00:19:02.480 ⇒ 00:19:05.480 Nicolas Sucari: We can move to Javi or pull parts.
137 00:19:06.010 ⇒ 00:19:10.989 Nicolas Sucari: Okay, so it’s boulevard first.st
138 00:19:21.000 ⇒ 00:19:30.889 Nicolas Sucari: So for pool parts. I already send the update for you guys to to check so that we can send that by email to Ian. Sorry to Ben, and don
139 00:19:32.430 ⇒ 00:19:35.820 Uttam Kumaran: Can we go through that right now? It’s gonna take 1 min.
140 00:19:36.560 ⇒ 00:19:41.019 Nicolas Sucari: Yeah, yeah, of course, I have it here.
141 00:19:42.000 ⇒ 00:19:44.820 Nicolas Sucari: So the update is on the
142 00:19:44.940 ⇒ 00:20:02.970 Nicolas Sucari: marketing costs. Or so we need to finish up the investigation on. Why it we have that spike in the marketing costs, I know. Pay us is working on finding what is like the source there that is making that our costs don’t match with what we have in post pilot.
143 00:20:03.497 ⇒ 00:20:07.079 Nicolas Sucari: So that will be today. If I’m mistaken. Okay.
144 00:20:07.080 ⇒ 00:20:07.750 Uttam Kumaran: Okay.
145 00:20:07.860 ⇒ 00:20:08.600 Uttam Kumaran: Yeah.
146 00:20:09.390 ⇒ 00:20:37.909 Nicolas Sucari: Cool then. We have all of this queue project. We need to add all of the data that Ian sent out and then work on the top 20 skews to analyze that and send that prioritization to work on all of the platforms with those ones. So yeah, we need to edit the sheet that we already created so that we focus on that and on on those things. And we are aiming that for Thursday evening by us would be working on that
147 00:20:38.220 ⇒ 00:20:41.740 Uttam Kumaran: These 2 bullets seem like the same. Let’s just get rid of one.
148 00:20:43.590 ⇒ 00:20:44.430 Nicolas Sucari: Okay.
149 00:20:44.430 ⇒ 00:20:45.900 Uttam Kumaran: Sending it to Ben, and then finally.
150 00:20:45.900 ⇒ 00:20:46.520 Nicolas Sucari: Yeah, yeah.
151 00:20:46.520 ⇒ 00:20:49.979 Uttam Kumaran: Then, yeah, let’s just get rid of one. Is ben on the hook for that.
152 00:20:51.730 ⇒ 00:20:54.061 Uttam Kumaran: or like, what did they? What did they say?
153 00:20:55.770 ⇒ 00:20:56.430 Nicolas Sucari: Yeah, I mean.
154 00:20:56.430 ⇒ 00:20:58.700 Uttam Kumaran: And he’s like, don’t involve anybody. And then.
155 00:20:59.220 ⇒ 00:21:09.679 Nicolas Sucari: Okay, maybe we don’t need to involve them. But this is what we discussed with Dan. Do you remember? In that meeting where we go through all of the sheet. And this queues we talked about having at least 20 like
156 00:21:09.790 ⇒ 00:21:15.269 Nicolas Sucari: top skews by revenue. And like, yeah, focusing on that one.
157 00:21:15.270 ⇒ 00:21:18.209 Uttam Kumaran: Just send it in that. Just send it in that thread.
158 00:21:18.540 ⇒ 00:21:22.360 Uttam Kumaran: one email thread. Just send it to everybody. Tag everybody.
159 00:21:22.940 ⇒ 00:21:31.980 Uttam Kumaran: I don’t. I don’t want to get. I don’t know who’s gonna do what it’s up to, Dan. So sometimes he’s like don’t involve anyone. It’s gonna go too slow. Sometimes he’s like involve them so.
160 00:21:32.380 ⇒ 00:21:47.660 Payas Parab: And I and I just also, like quickly, just get some again, some more additional context on clarifying the 20 skews. It’s essentially like we’re the broader project is skew matching. Right? Is there like, what we need to do is like, get them cleaned up on a data and for. And they just really want to prioritize.
161 00:21:47.760 ⇒ 00:22:02.439 Payas Parab: Basically like, let’s make sure those 20 are the right ones, right? And we’re gonna use the Asia data, which really just means the accounting data, right? Which is, and the Asia data, which is what Ian sent us. And I got a chance to look through. It has for us. There’s there’s a couple of things in there. It has
162 00:22:02.960 ⇒ 00:22:17.039 Payas Parab: the actual revenue items, right? So we just need to like, that’s actually just like a quick filter, understand which are the top 20 skews, and then go back to Ryan’s sheet and make sure that we know the right skew mapping for those 20. It’s like top priority. We confirm that that’s in the system.
163 00:22:17.190 ⇒ 00:22:29.799 Payas Parab: Then there’s 1 additional sheet that Ian had sent that I wanted to clarify. Was he sent also like the costing sheet, but I also know, like I think Ben sent us that costing sheet where we did those like manipulations in excel right.
164 00:22:29.800 ⇒ 00:22:35.430 Uttam Kumaran: I think the new costing sheet is the accurate one.
165 00:22:36.300 ⇒ 00:22:48.750 Nicolas Sucari: I mean, I I think there are 2 different things, maybe because what Ian sent is the cost that they have when when they buy the product. But the what what Dan shared with us is because the pool parts has, like.
166 00:22:48.750 ⇒ 00:22:50.140 Uttam Kumaran: Oh, okay. Yeah. Yeah.
167 00:22:50.140 ⇒ 00:22:59.060 Nicolas Sucari: E-commerce has when they when they sell all of that. So I think we need to focus on the cost that that we have on the sheet, the one the calculations that we already did.
168 00:22:59.500 ⇒ 00:23:07.140 Uttam Kumaran: So the so the Asia cost is their true cause. Full parts cost. They’re buying, basically from information. Yeah.
169 00:23:07.140 ⇒ 00:23:09.340 Uttam Kumaran: And they put a little bit of a markup on it.
170 00:23:09.630 ⇒ 00:23:14.340 Uttam Kumaran: So pool parts cost is just the e-commerce division of their larger business.
171 00:23:14.440 ⇒ 00:23:18.870 Uttam Kumaran: They sell to the pool, call to the pool parts business with a markup.
172 00:23:19.100 ⇒ 00:23:33.100 Uttam Kumaran: So it’s dependent on that cost. Initial cost being accurate. The problem is, they never updated what the actual cost of goods sold was for Asia which meant the the reliant calculations were also not up to date.
173 00:23:33.320 ⇒ 00:23:40.709 Payas Parab: I see I see so in the sheet that we have right right now, with, like the landed cost. There’s a cogs column in there. If I recall correctly, right.
174 00:23:40.710 ⇒ 00:23:41.569 Uttam Kumaran: Not right.
175 00:23:41.800 ⇒ 00:23:52.950 Payas Parab: There’s also tariff. So we we have to assume that those aren’t right. What came from Asia, where it’s like we’ll have to do like a group by by the skew, then group by like the amount of units, and then divide to figure out the accurate tariff.
176 00:23:53.520 ⇒ 00:24:22.889 Uttam Kumaran: Yeah, so what? While you’re going through this, I would say, the best part to work with these guys is to try it. First.st Document, how we did it, and then be like, give us comment if we go in and ask how to do it. It’s gonna it’s not gonna work. So make a fair bit of assumptions and then do it that way. And then, yeah, basically I, what? This will be a pro one. The whole goal here again is like they want one document that has all their skews across all their platforms with each of the different components related to costs.
177 00:24:23.579 ⇒ 00:24:31.240 Uttam Kumaran: So that’s the big goal. And so, yeah, I would say, exactly. We want to get to the tariffs and cogs first, st and then that’ll represent.
178 00:24:31.240 ⇒ 00:24:41.609 Payas Parab: So we we do actually need to like dive into that data that Ian sent and make sure that that we’re not assuming that the one on the costing sheet that we currently have is accurate. I I just wanna make sure that. Okay, helpful.
179 00:24:41.800 ⇒ 00:24:42.670 Payas Parab: Thank you.
180 00:24:45.720 ⇒ 00:24:57.381 Nicolas Sucari: Okay, and then we have the new shipping provider costs. That. I think Luke already created the role there. We need to.
181 00:24:58.210 ⇒ 00:25:26.440 Nicolas Sucari: to to yeah. Add 2,200. Sorry for the for the shipping costs. The rule is there. I don’t know if the pull request has already been approved, Luke.
182 00:25:26.440 ⇒ 00:25:39.460 Uttam Kumaran: No, I’m gonna I’m reviewing it, and I’ll push it. So this one’s good. Yeah, I’ll review and push it but just consider it good. And then for the second one, yeah. So I guess, like, our.
183 00:25:39.750 ⇒ 00:25:45.830 Uttam Kumaran: So is this, is this in are the experiments on our side? Or are you talking like the Kim, like Kim running experiments.
184 00:25:46.080 ⇒ 00:26:03.089 Payas Parab: Kim will run the experiment. But we need to send like a list of like a target email list. So for example, like, like, yeah, it’s like, Pull them the ones we’ve already Zip code matched. Here’s Group A, here’s group B of like different weather patterns. Let’s run an email, marketing campaign. And like a B test that right? And if we’re like, okay, the weather one
185 00:26:03.190 ⇒ 00:26:13.729 Payas Parab: did actually have a 30% more open rate. Then we’re like, okay, this is something. If it’s not, then it’s like cool. It’s just a random correlation within the random pattern of orders. Right?
186 00:26:14.053 ⇒ 00:26:17.940 Uttam Kumaran: Is Tuesday aggressive. For this the skew stuff is like number one.
187 00:26:18.510 ⇒ 00:26:24.489 Payas Parab: I I don’t think I have to. I think I said Tuesday. Sorry I meant next Tuesday. It’s next Tuesday.
188 00:26:24.780 ⇒ 00:26:26.610 Uttam Kumaran: Well, it’s Wednesday right now. So what do you mean next?
189 00:26:26.610 ⇒ 00:26:27.320 Nicolas Sucari: Yeah.
190 00:26:28.500 ⇒ 00:26:29.864 Uttam Kumaran: You mean? Yesterday.
191 00:26:30.320 ⇒ 00:26:32.890 Payas Parab: That’s what I meant, like. No, no, no like next like.
192 00:26:32.890 ⇒ 00:26:42.010 Uttam Kumaran: Like, yeah, I guess that’s what I’m asking is, I mean, that’s not. That’s like, what? 3 days, 4 days. Yeah, it’s like, that’s almost just 5 days too aggressive.
193 00:26:42.010 ⇒ 00:26:46.759 Payas Parab: Oh, I see. Okay, okay. Maybe like, maybe we could put, should we up that a little bit to like.
194 00:26:46.760 ⇒ 00:26:54.329 Uttam Kumaran: Put. Just put Wednesday. Put Wednesday for it, cause I wanna make sure if skew, if we get stuff back on skew, that’s the number one.
195 00:26:54.790 ⇒ 00:26:55.520 Payas Parab: Got it. Okay.
196 00:26:55.520 ⇒ 00:26:59.029 Uttam Kumaran: So let’s just put Wednesday, and then we’re good. And then.
197 00:26:59.320 ⇒ 00:27:02.840 Uttam Kumaran: Nico, can we make sure all these dates end up in the board?
198 00:27:03.730 ⇒ 00:27:06.980 Nicolas Sucari: Yeah. Okay, of course.
199 00:27:08.730 ⇒ 00:27:13.820 Nicolas Sucari: Cool. Yeah. So that’s for pool parts. Don’t know if we have anything else.
200 00:27:14.440 ⇒ 00:27:25.300 Uttam Kumaran: I think that’s the big, the biggest thing I would. I want to see after we. Now that pricing after this iteration, you’ll basically have a good grasp of like, 80% of the skew work. I want to start building out what the next
201 00:27:25.550 ⇒ 00:27:41.599 Uttam Kumaran: month is gonna look like for this sort of work. There’s a process where we need to. We need them to update for the top 20, then update for the rest. And then this needs to get permeated into systems. And there needs to be like probably some sort of monthly review process. All that
202 00:27:42.140 ⇒ 00:27:47.018 Uttam Kumaran: we need to put in like a like a flow chart or something, so that they can review
203 00:27:47.520 ⇒ 00:27:49.190 Uttam Kumaran: and then so we can execute.
204 00:27:50.230 ⇒ 00:27:52.209 Uttam Kumaran: So yeah, go ahead.
205 00:27:52.210 ⇒ 00:27:55.099 Payas Parab: What are what are the offshoot things that come out of like?
206 00:27:55.240 ⇒ 00:28:02.830 Payas Parab: We give them this mapping. Right? You’re saying like what we do with that mapping essentially, is sort of the next steps, and that we still haven’t planned out with them.
207 00:28:02.830 ⇒ 00:28:12.359 Uttam Kumaran: Yeah. So basically, right now, every source system has its own, like internal skew database. All those need to be sourced from this.
208 00:28:13.178 ⇒ 00:28:19.160 Uttam Kumaran: Second thing is when the biggest thing that this is gonna solve is updating costing
209 00:28:19.690 ⇒ 00:28:31.290 Uttam Kumaran: when costing updates the prices of the product update and there and therefore profit updates. So we need to this document. And this process is gonna help them keep track of what those costs are
210 00:28:31.792 ⇒ 00:28:34.149 Uttam Kumaran: as they change month over month.
211 00:28:34.300 ⇒ 00:28:43.360 Uttam Kumaran: And then the relative pricing changes that happen with the products will be relative to this, because they have some formulation for how they charge as well.
212 00:28:43.360 ⇒ 00:28:43.970 Payas Parab: Yeah.
213 00:28:44.470 ⇒ 00:29:09.949 Uttam Kumaran: So right now, there’s products where they’re not. They haven’t updated the cost, which means their profit. Calculations are on their analytics side are not right because we’re using all their costs from the system, and that’s not the cost from the accounting, which is a real source of truth. The last thing Dan is like Dan was interested in creating like a little retool app, or some sort of app for them to do this I was like, don’t worry about any of that. Just like make sure it’s in a spreadsheet that we can get first.st
214 00:29:10.080 ⇒ 00:29:10.815 Uttam Kumaran: But
215 00:29:11.790 ⇒ 00:29:14.230 Payas Parab: So, for example, like this data dump from Ian.
216 00:29:14.400 ⇒ 00:29:31.109 Payas Parab: we have to build in for to be able to process that in the future, too. So it’s kind of like, Hey, there’s gonna be new data dumped in. We’re gonna have to process it. Clean it up. Once I figure out in the next couple of hours of working time, like what that like, you know, it’s whatever you aggregate here, group by. And then this is how we calculate that.
217 00:29:31.110 ⇒ 00:29:31.530 Uttam Kumaran: Yeah.
218 00:29:31.530 ⇒ 00:29:41.230 Payas Parab: Then we’re gonna have to create a process to kind of do that on a repeated basis. So we’re like somewhat real time. And that will be just like relying on a data dump from Ian is like the future state.
219 00:29:41.230 ⇒ 00:30:04.390 Uttam Kumaran: Yeah, that seems like it, basically. Yeah. And then also this, not only for updated for existing products. When they ship new products, this will, there’ll be a process for, like okay, as as part of the checklist, one of this will be, make sure the skew ends up here. The cost ends up here. It could that get permeated? It’s basically all the metadata associated with skews. So the the names, the Ids
220 00:30:04.850 ⇒ 00:30:05.819 Uttam Kumaran: things like that.
221 00:30:06.810 ⇒ 00:30:15.269 Nicolas Sucari: Yeah, once we have that, we need to go to every platform and try to have everything like equal between the different platforms, shopify Amazon. Everything they are using.
222 00:30:15.670 ⇒ 00:30:16.180 Payas Parab: Got it.
223 00:30:18.190 ⇒ 00:30:18.850 Nicolas Sucari: Cool.
224 00:30:19.190 ⇒ 00:30:19.710 Uttam Kumaran: Thank you.
225 00:30:21.240 ⇒ 00:30:23.359 Nicolas Sucari: Okay. So let’s go to Javi.
226 00:30:29.860 ⇒ 00:30:38.319 Payas Parab: Our boy, Jay Kemp, ripping in Chat Gpt, trying to solve this data stuff himself. So funny when I saw that
227 00:30:38.940 ⇒ 00:30:44.859 Payas Parab: I’ve heard Justin’s a really cool guy like I. I don’t know, Robert. If you have a sense like I feel like Justin, I would like love to hang out with Justin.
228 00:30:44.860 ⇒ 00:30:51.500 Robert Tseng: Yeah, totally dude. Just keep keep messaging him. Let’s just like, you know, whatever ignore the Jared character, just like.
229 00:30:51.814 ⇒ 00:31:01.569 Uttam Kumaran: Like Jared Dude I get. I enjoy talking to the the people that are very like tense, because feel like there’s once once they start to like us smooth everything out.
230 00:31:01.800 ⇒ 00:31:04.029 Uttam Kumaran: I’m not saying you guys haven’t tried, but.
231 00:31:04.730 ⇒ 00:31:11.799 Payas Parab: Dude we’ve we’ve and he he’s dude. He changes, though, like there’s been days where we like hopped off the call, and we’re like, wow! Jared likes us now and then. He’s just like
232 00:31:11.910 ⇒ 00:31:13.369 Payas Parab: couple days later. He’s like.
233 00:31:13.540 ⇒ 00:31:14.130 Uttam Kumaran: Oh, yeah.
234 00:31:14.130 ⇒ 00:31:15.929 Payas Parab: You know, like, it’s just like.
235 00:31:16.070 ⇒ 00:31:18.899 Uttam Kumaran: I’m familiar. I’m familiar with the type.
236 00:31:24.350 ⇒ 00:31:25.070 Uttam Kumaran: cool.
237 00:31:25.547 ⇒ 00:31:34.730 Nicolas Sucari: Okay, so everything on portable. I think it’s already connected. So we have recharge gorgeous. So can do. I can move all of these.
238 00:31:34.730 ⇒ 00:31:39.910 Uttam Kumaran: Can you move all this in progress? Yeah. Anything related to Portable just moved in progress.
239 00:31:40.120 ⇒ 00:31:41.030 Nicolas Sucari: Okay.
240 00:31:42.189 ⇒ 00:31:46.280 Uttam Kumaran: I’m working with them, and that should be done soon.
241 00:31:46.800 ⇒ 00:31:50.109 Uttam Kumaran: 5 transit portable migration is next.
242 00:31:51.286 ⇒ 00:31:53.150 Uttam Kumaran: What else? Oh, shop.
243 00:31:53.150 ⇒ 00:31:53.510 Nicolas Sucari: Okay.
244 00:31:53.510 ⇒ 00:31:56.730 Uttam Kumaran: Shopify through portable, you can move that to in progress.
245 00:31:58.210 ⇒ 00:31:58.980 Nicolas Sucari: Yeah, yeah.
246 00:31:58.980 ⇒ 00:32:01.999 Uttam Kumaran: Google sheets supportable. You can move them. Progress as well.
247 00:32:06.220 ⇒ 00:32:07.390 Uttam Kumaran: Be logging.
248 00:32:08.510 ⇒ 00:32:16.689 Nicolas Sucari: Yeah, my computer is kind of slow. I don’t know what’s happening Google sheets supportable to. Okay, there.
249 00:32:17.190 ⇒ 00:32:22.240 Uttam Kumaran: Okay, can you put all the dates for this as today?
250 00:32:23.360 ⇒ 00:32:24.590 Nicolas Sucari: Okay. Yes.
251 00:32:34.470 ⇒ 00:32:36.440 Uttam Kumaran: I’ll pull these posts out.
252 00:32:46.760 ⇒ 00:32:48.219 Nicolas Sucari: Okay, here we go. Right?
253 00:32:48.510 ⇒ 00:32:48.950 Uttam Kumaran: Great.
254 00:32:48.950 ⇒ 00:32:49.760 Nicolas Sucari: Like 22.
255 00:32:51.270 ⇒ 00:32:54.909 Robert Tseng: The main thing that needs to stay in 5 trim right now is just it’s Amazon.
256 00:32:55.790 ⇒ 00:32:58.117 Uttam Kumaran: Yeah, they’re building the connector for us.
257 00:32:58.450 ⇒ 00:33:01.409 Robert Tseng: So Amazon. And then also Tiktok, because they don’t have Tiktok.
258 00:33:02.040 ⇒ 00:33:05.359 Robert Tseng: We don’t. Yeah, like the Tiktok has been coming from Amazon right?
259 00:33:05.400 ⇒ 00:33:06.600 Uttam Kumaran: It’s been coming through, shopify.
260 00:33:07.004 ⇒ 00:33:08.219 Robert Tseng: Sorry. Shopify. Okay.
261 00:33:08.220 ⇒ 00:33:14.980 Uttam Kumaran: So that’s good. That’s gonna be covered the Amazon stuff. I’m gonna try to get it below the 500 K limit.
262 00:33:16.562 ⇒ 00:33:18.659 Uttam Kumaran: So that we should get it for free.
263 00:33:19.410 ⇒ 00:33:22.030 Uttam Kumaran: So let’s see if I can make that happen.
264 00:33:22.600 ⇒ 00:33:23.340 Robert Tseng: Okay.
265 00:33:24.690 ⇒ 00:33:28.499 Uttam Kumaran: And then there, there’s a ticket up on the
266 00:33:28.690 ⇒ 00:33:32.890 Uttam Kumaran: do we have the can you get? Can you bring the Ids into this view? The ticket ids.
267 00:33:34.750 ⇒ 00:33:40.609 Nicolas Sucari: Yes, I know you’re lagging. I’m asking to do some a little bit complicated stuff, but.
268 00:33:40.900 ⇒ 00:33:48.829 Uttam Kumaran: There’s just 2 Amazon tickets connecting Amazon and moving. Oh, connecting Amazon is a portable. Okay? Actually, it’s that’s fine, whatever.
269 00:33:49.190 ⇒ 00:33:50.789 Uttam Kumaran: Okay, that’s on me, too.
270 00:33:51.110 ⇒ 00:33:52.989 Nicolas Sucari: Have the ticket. Id here.
271 00:33:53.710 ⇒ 00:33:54.680 Nicolas Sucari: Okay.
272 00:33:57.880 ⇒ 00:34:01.490 Uttam Kumaran: The boards are getting better still, a couple of things that I’m like
273 00:34:02.810 ⇒ 00:34:07.900 Uttam Kumaran: little annoyed with the views. But they’re getting this getting a lot better than it was a month ago.
274 00:34:08.090 ⇒ 00:34:13.979 Uttam Kumaran: Okay, so connecting Amazon, yeah, that’s portable. So I’ll have that. Okay, that’s I think that that’s it for me.
275 00:34:14.090 ⇒ 00:34:16.759 Uttam Kumaran: And then what happened with real Luke
276 00:34:17.929 ⇒ 00:34:21.100 Uttam Kumaran: like? What does he? What did he mean? It wasn’t active or something.
277 00:34:22.340 ⇒ 00:34:27.030 Nicolas Sucari: It’s yeah. The project was kind of like hibernating. That was what real.
278 00:34:27.420 ⇒ 00:34:27.919 Uttam Kumaran: I think maybe.
279 00:34:27.929 ⇒ 00:34:28.679 Nicolas Sucari: When they
280 00:34:28.919 ⇒ 00:34:42.249 Nicolas Sucari: the when I when I went into rail I saw that, and I kind of woke up the project it was just clicking woke up, and it everything went live again. But there were some issues on the sources that look.
281 00:34:42.579 ⇒ 00:34:45.539 Nicolas Sucari: I think he he figured it out.
282 00:34:46.610 ⇒ 00:34:53.387 Luke Daque: Yeah, I don’t really know what the root cause was. So all I did was run it locally and update the
283 00:34:54.440 ⇒ 00:34:55.440 Luke Daque: I deployed.
284 00:34:55.449 ⇒ 00:34:55.979 Nicolas Sucari: The bill.
285 00:34:55.980 ⇒ 00:34:57.340 Luke Daque: Yeah builds.
286 00:34:57.340 ⇒ 00:34:59.945 Uttam Kumaran: They’re not on contract with real.
287 00:35:00.540 ⇒ 00:35:03.209 Uttam Kumaran: I don’t know, Robert, what are we gonna do about that? Like.
288 00:35:04.600 ⇒ 00:35:06.169 Robert Tseng: Are they billing us now?
289 00:35:06.170 ⇒ 00:35:07.460 Uttam Kumaran: No, no, they’re not.
290 00:35:07.960 ⇒ 00:35:10.879 Uttam Kumaran: It’s it’s most likely that they just haven’t seen it.
291 00:35:11.615 ⇒ 00:35:15.165 Uttam Kumaran: But like they’ll, I’ll get a ping at some point.
292 00:35:15.920 ⇒ 00:35:16.570 Robert Tseng: Yeah.
293 00:35:18.520 ⇒ 00:35:20.399 Uttam Kumaran: It’s cheap. It’s 2 50 a month.
294 00:35:21.000 ⇒ 00:35:21.889 Robert Tseng: Yeah, yeah.
295 00:35:23.420 ⇒ 00:35:28.040 Uttam Kumaran: I mean, we could just keep running and and like, keep keep going and ticket.
296 00:35:32.400 ⇒ 00:35:58.670 Robert Tseng: Yeah. Well, I mean, so there’s a couple of things from my account management perspective. I want to do. I’m gonna like, straight up. Just Tag Brandon. Try to get him like involve us involved on the lifecycle reporting stuff soon, and then also, like, I don’t know if I should just even just spend like a little bit of my time every week, and just like share, loom videos of me, like like doing a bit of like analysis and real to try to drop some nuggets on Justin’s plate.
297 00:35:58.800 ⇒ 00:35:59.860 Robert Tseng: So.
298 00:36:00.210 ⇒ 00:36:17.029 Uttam Kumaran: Yeah, I think I think you should get you should get them in real and send this stuff, and then it’ll make that conversation 10 times easier. Yeah, if if they if they ping me, I can tell them like, leave it for a little bit. But then I’m gonna have to give Sid on their team
299 00:36:17.160 ⇒ 00:36:27.150 Uttam Kumaran: like some idea again, they’re most likely they just haven’t seen it. And like we’re kind of small beans. So in terms of our usage, so they probably haven’t seen it.
300 00:36:27.670 ⇒ 00:36:47.200 Robert Tseng: Okay, what I what I can do is an amplitude. I can see the reports that Justin’s looking at. I know what he, he continues, he’s still active there. He built some stuff, anything that he’s trying to do there. I’m gonna replic. Try to replicate in a real analysis, like if I if I can find some gaps and be like, Okay, well, he maybe that’ll be a good good way to like demo stuff that I know that he’s already looking at.
301 00:36:47.950 ⇒ 00:36:48.840 Uttam Kumaran: Cool. Okay.
302 00:36:49.040 ⇒ 00:36:49.630 Robert Tseng: Yeah.
303 00:36:51.290 ⇒ 00:36:58.700 Nicolas Sucari: One thing that we will need to do with the rail if we are going to still use it, use it is we need to change all of these sources to
304 00:36:58.890 ⇒ 00:37:03.729 Nicolas Sucari: to come from portable right? Because right now we have everything already built from.
305 00:37:03.730 ⇒ 00:37:07.529 Uttam Kumaran: It’ll all come from the it’ll all come from the Dbt.
306 00:37:07.530 ⇒ 00:37:08.110 Nicolas Sucari: I know.
307 00:37:08.110 ⇒ 00:37:09.200 Uttam Kumaran: There shouldn’t be.
308 00:37:09.780 ⇒ 00:37:25.510 Nicolas Sucari: Okay, that’s fine. If we have the analytics that if the yeah, if we don’t change the name of any analytics database and the tables that we already have with that data that will be fine. We just need to yeah, update those tables with the new data. I think from portable right.
309 00:37:25.510 ⇒ 00:37:28.050 Uttam Kumaran: Okay, yeah, yeah, yeah.
310 00:37:29.950 ⇒ 00:37:30.836 Nicolas Sucari: Perfect. Okay.
311 00:37:31.490 ⇒ 00:37:39.019 Nicolas Sucari: cool. So on engineering. I think that’s it. And then, we have the gross margin. Dashboard B, 2.
312 00:37:40.970 ⇒ 00:37:44.179 Nicolas Sucari: We are still waiting for the cogs stuff.
313 00:37:46.930 ⇒ 00:37:50.139 Nicolas Sucari: Okay, what’s what we need to do to unblock this one.
314 00:37:51.420 ⇒ 00:37:55.549 Uttam Kumaran: The cogs model is, it relies on.
315 00:37:55.550 ⇒ 00:37:56.550 Payas Parab: Care of that right.
316 00:37:56.730 ⇒ 00:37:58.439 Uttam Kumaran: Yeah, it’s relying the Google sheets.
317 00:37:59.370 ⇒ 00:38:02.120 Payas Parab: And that that’s flowing right now right to snowflake or no.
318 00:38:02.510 ⇒ 00:38:03.150 Uttam Kumaran: No.
319 00:38:03.790 ⇒ 00:38:04.210 Payas Parab: That.
320 00:38:04.210 ⇒ 00:38:05.370 Uttam Kumaran: Like it’s I’m.
321 00:38:05.370 ⇒ 00:38:12.659 Payas Parab: Yeah, that that one I’m I’m not planning to like, like, basically the the analytics work. I’m planning to tackle like Saturday, you know, like my new kind of.
322 00:38:12.660 ⇒ 00:38:16.260 Uttam Kumaran: How often are those things gonna change bias, those sheets.
323 00:38:18.790 ⇒ 00:38:19.670 Payas Parab: I.
324 00:38:19.900 ⇒ 00:38:25.700 Payas Parab: I don’t anticipate that frequently, but what I do anticipate is that.
325 00:38:25.810 ⇒ 00:38:34.559 Payas Parab: like J. Money like like from like a Cfo perspective, he reports like last month’s financials. And then they change, and we change the entire sheet like
326 00:38:34.910 ⇒ 00:38:38.839 Payas Parab: that’s an like. The the sheet will need to update, probably, and
327 00:38:39.380 ⇒ 00:38:45.770 Payas Parab: he wants it to be dynamic, connected to the sheets like he, he’s like, that’s important. And we also need to track like when we update it. Because
328 00:38:45.770 ⇒ 00:38:46.550 Payas Parab: if you report
329 00:38:46.550 ⇒ 00:38:51.960 Payas Parab: the previous month. So I think that that he hasn’t said that explicitly. But I’m I know that will come up. We’ll be like.
330 00:38:51.960 ⇒ 00:38:52.279 Uttam Kumaran: All right.
331 00:38:52.280 ⇒ 00:38:57.819 Payas Parab: Reported last month, and it didn’t. We changed it. And now all my previous reporting was technically wrong.
332 00:38:57.820 ⇒ 00:38:59.971 Uttam Kumaran: Okay, I’ll have it done today.
333 00:39:00.910 ⇒ 00:39:02.100 Payas Parab: One way or another.
334 00:39:03.690 ⇒ 00:39:21.509 Payas Parab: It doesn’t have to be today. By the way, those longer like those longer does what I was saying like friday, and Saturday is sort of my time slated for those. That’s why I set the Sunday deadline so it’s no like it’s just if Friday I see it, and it’s not there. Then I’ll just flag to you guys that it’s blocked because I I can’t do it without those tables.
335 00:39:21.730 ⇒ 00:39:22.360 Uttam Kumaran: Okay.
336 00:39:28.360 ⇒ 00:39:28.990 Nicolas Sucari: Okay.
337 00:39:29.952 ⇒ 00:39:38.720 Nicolas Sucari: apart from that, we have, we have the task of address matching by us. I think that one. We are also aiming for Sunday to deliver something about that.
338 00:39:38.720 ⇒ 00:39:40.429 Payas Parab: Yep, all good. There.
339 00:39:40.950 ⇒ 00:39:43.690 Uttam Kumaran: What is a 5 version control? What is that?
340 00:39:45.210 ⇒ 00:39:49.110 Nicolas Sucari: This was a task that we have in the previous dashboard.
341 00:39:49.110 ⇒ 00:39:51.769 Payas Parab: It’s the thing I just mentioned, Tom, like when when that.
342 00:39:51.770 ⇒ 00:39:52.470 Uttam Kumaran: She updates.
343 00:39:52.470 ⇒ 00:39:54.649 Payas Parab: We need like an as of date, so that we know.
344 00:39:54.650 ⇒ 00:39:56.850 Uttam Kumaran: Can you change this to
345 00:39:59.750 ⇒ 00:40:06.210 Uttam Kumaran: Google sheets cogs. Google sheets slowly changing dimension.
346 00:40:08.920 ⇒ 00:40:17.919 Payas Parab: Yeah, it’s it’s also a Github issue. There’s a Github issue. And I like, explain what that is who, Tom. So if you like, when you get to there. Just look through the issue on Github, and you’ll see what what needs to be there.
347 00:40:18.370 ⇒ 00:40:21.969 Uttam Kumaran: Okay. And this is just a you can just assign this to Ryan and then, Ryan
348 00:40:22.200 ⇒ 00:40:30.000 Uttam Kumaran: we’ll use. We’ll use. I’ll show you how to do scd table and dbt, so we’ll track history for these
349 00:40:32.250 ⇒ 00:40:36.270 Uttam Kumaran: table. SEDS, O, yeah, yeah.
350 00:40:36.942 ⇒ 00:40:39.270 Luke Daque: It’s yeah, yeah. I got it cool.
351 00:40:42.990 ⇒ 00:40:43.830 Uttam Kumaran: Okay. Cool.
352 00:40:43.830 ⇒ 00:40:48.110 Nicolas Sucari: Okay, I think that’s it. Anything else? Guys.
353 00:40:50.900 ⇒ 00:40:52.670 Uttam Kumaran: What else is that it? That’s a good meeting.
354 00:40:54.980 ⇒ 00:41:02.210 Nicolas Sucari: Yeah, we didn’t discuss art helper, but I don’t know if there is anything there, Robert, maybe you.
355 00:41:02.960 ⇒ 00:41:13.150 Robert Tseng: Yeah. I mean, they’re they’re just they’re not. They’re not ready. I mean, that’s what happens. Now, this is what happens when we don’t do the engineering they’re just. We’re just kind of at the whim of, however long it takes them to implement stuff.
356 00:41:14.115 ⇒ 00:41:18.280 Robert Tseng: But yeah, I don’t think they’re done yet. They haven’t handed them back to us.
357 00:41:18.850 ⇒ 00:41:26.641 Robert Tseng: I guess my question would be for this call. Is it productive to also like talk about stuff? I know we’re only just reviewing stuff that’s in flight.
358 00:41:27.290 ⇒ 00:41:38.220 Robert Tseng: I don’t know if we really have like a check in for me to kind of for us to like. Talk about stuff that’s coming down the pipeline. Maybe that’s not that important. And it’s just like the folks here only want to talk about the things that are like
359 00:41:38.320 ⇒ 00:41:40.579 Robert Tseng: we’re on the on the hook for like.
360 00:41:40.580 ⇒ 00:41:50.939 Uttam Kumaran: No, I mean I I would say we should talk about it like for me. This meeting is one like, I don’t want to talk, spend too much time on stuff that’s going. Well, I basically only want to spend time on stuff where we need help.
361 00:41:51.440 ⇒ 00:41:59.369 Uttam Kumaran: There’s some of these small things that I think it does well to talk through. And then for me, the biggest thing is like, I want to see what the next month of work is
362 00:41:59.859 ⇒ 00:42:14.730 Uttam Kumaran: for 2 reasons, one, like we need to look at across all of us that are working on data, what our capacity is, and second, on the recruiting side that helps as well. So we have 5 more minutes. Let’s just yeah. Whatever we want to talk about.
363 00:42:15.440 ⇒ 00:42:36.679 Robert Tseng: Okay, well, I’m just thinking we’re not necessarily doing today, but like, maybe in the future, like, if we have 45 min set apart. I don’t know. How does that have we have like 45 min set, you know, the 1st chunk can just be going through. We should time box it. We have to get through everything that’s implied, and then we save like 1015 min at the end, and we can try to like tee up some of the stuff that’s coming, because
364 00:42:36.680 ⇒ 00:42:49.980 Robert Tseng: at least from the Eden side, like, because I’m like talking to all the state a lot of stakeholders like, yeah, like, I’m there’s like new stuff that’s coming down. That’s not. I haven’t really shared about yet, but I I think it’d be great to kind of give the team some context. And
365 00:42:50.615 ⇒ 00:42:57.950 Robert Tseng: yeah, I I can. I can always just prepare other like loom videos or something as well. So I don’t know whatever is helpful.
366 00:42:58.240 ⇒ 00:43:00.480 Uttam Kumaran: We can do that on Friday as well.
367 00:43:01.610 ⇒ 00:43:04.399 Uttam Kumaran: But then, yeah, I agree. I think we should just spend 30 min
368 00:43:04.580 ⇒ 00:43:13.700 Uttam Kumaran: on active stuff anything where we’re like. Like, if anything goes over like couple of minutes we can kick off line, and then we’ll spend 15 min on the future stuff.
369 00:43:14.010 ⇒ 00:43:15.870 Robert Tseng: Okay, let’s do that. Moving forward.
370 00:43:19.490 ⇒ 00:43:22.918 Luke Daque: Oh, and just one more thing utam for stack Blitz
371 00:43:23.670 ⇒ 00:43:27.279 Luke Daque: Should I create like the the warehouse in Snowflake as well.
372 00:43:27.280 ⇒ 00:43:27.780 Uttam Kumaran: Well done!
373 00:43:29.010 ⇒ 00:43:38.520 Luke Daque: Oh, so like I can see, like the role transform and stuff like that like warehouse.
374 00:43:38.520 ⇒ 00:43:41.649 Uttam Kumaran: Oh, I’ll give you! I’ll give you. I’ll give you admin.
375 00:43:42.210 ⇒ 00:43:44.189 Luke Daque: Cool sounds, good thanks.
376 00:43:45.950 ⇒ 00:43:47.350 Uttam Kumaran: Okay, thanks guys.
377 00:43:48.590 ⇒ 00:43:50.340 Nicolas Sucari: Thanks, guys. Bye-bye.
378 00:43:50.930 ⇒ 00:43:51.999 Luke Daque: Thanks, bye, bye.