Meeting Title: US x BF | Sprint Kickoff Date: 2025-08-05 Meeting participants: Caio Velasco, Demilade Agboola, Amber Lin, Uttam Kumaran
WEBVTT
1 00:00:26.220 ⇒ 00:00:27.310 Demilade Agboola: Hi Kyle.
2 00:00:32.290 ⇒ 00:00:33.520 Caio Velasco: How you doing, Andy?
3 00:00:35.040 ⇒ 00:00:35.940 Caio Velasco: All good.
4 00:00:36.770 ⇒ 00:00:38.630 Demilade Agboola: Yeah, I’m doing well, how are you doing.
5 00:00:39.270 ⇒ 00:00:45.940 Caio Velasco: Good as well, waiting for more more news from revenue.
6 00:00:46.740 ⇒ 00:00:47.830 Demilade Agboola: Yeah.
7 00:00:54.030 ⇒ 00:00:55.259 Amber Lin: Good morning!
8 00:00:55.430 ⇒ 00:00:56.230 Demilade Agboola: Hi amba.
9 00:00:56.650 ⇒ 00:01:05.239 Amber Lin: Hi! I’m waiting for Otam to join cause I need him to help the new tickets.
10 00:05:36.390 ⇒ 00:05:37.640 Amber Lin: Hello.
11 00:05:38.600 ⇒ 00:05:39.460 Uttam Kumaran: Hey!
12 00:05:41.210 ⇒ 00:05:52.480 Amber Lin: Alright, so wanted to spend the 1st 20 to 30 min to check. If the new tickets are correct, and then we’ll pull whatever we need into the current cycle.
13 00:05:53.100 ⇒ 00:05:55.530 Amber Lin: Oh, yeah.
14 00:06:08.890 ⇒ 00:06:13.350 Amber Lin: So this is the
15 00:06:13.870 ⇒ 00:06:29.299 Amber Lin: revenue project. And I made a few milestones. 1st one, I said, is to finish off. Any definitions modeling plan. I don’t know if we really need these 3 tickets because they could be part of
16 00:06:29.410 ⇒ 00:06:45.316 Amber Lin: the actual modeling tickets. And then the second milestone is about ingestion. Because it does block milestone 3 and 4, which would be the stage and intermediate models, and then
17 00:06:46.230 ⇒ 00:06:51.730 Amber Lin: Then, after that it would be the fact and dimension tables.
18 00:06:52.320 ⇒ 00:06:56.879 Amber Lin: Then, later it would be any additional ones that we talked about
19 00:06:57.801 ⇒ 00:07:02.849 Amber Lin: and looker, and then handing things over.
20 00:07:03.623 ⇒ 00:07:12.329 Amber Lin: I sorted these by milestones, and I wanted to check with you all. If these are valid tickets.
21 00:07:13.430 ⇒ 00:07:16.949 Uttam Kumaran: Okay, maybe we can take a sec to just read through them all. I.
22 00:07:16.950 ⇒ 00:07:17.610 Amber Lin: Appreciate it.
23 00:07:46.220 ⇒ 00:07:48.990 Amber Lin: I sent the project link in the chat.
24 00:07:50.040 ⇒ 00:07:52.009 Uttam Kumaran: Yeah, I’m I’m looking at it.
25 00:09:59.400 ⇒ 00:10:04.170 Uttam Kumaran: So the looker ones are those all? Can the analyst team like handle those.
26 00:10:06.340 ⇒ 00:10:11.249 Amber Lin: Yeah, I believe so. I’m just putting them so that we remember to book sessions.
27 00:10:11.540 ⇒ 00:10:16.930 Uttam Kumaran: Yeah. But like updating, look, Ml, explore, like, I feel like they can take that on right.
28 00:10:18.350 ⇒ 00:10:29.960 Demilade Agboola: Yeah, I I believe the arrangements with them is that they handle looker, but obviously just having tickets. So we can keep track of what’s going on, and if you have done will be helpful from our end.
29 00:10:31.065 ⇒ 00:10:31.530 Uttam Kumaran: Okay.
30 00:10:32.280 ⇒ 00:10:34.179 Uttam Kumaran: And here let me, I can share this.
31 00:10:40.170 ⇒ 00:10:49.649 Uttam Kumaran: So kind of like what I’m looking through. I’ll just kind of walk through it. So. I saw all the existing like audit related stuff. That’s fine.
32 00:10:53.030 ⇒ 00:10:57.760 Uttam Kumaran: I think this is probably something that
33 00:10:57.930 ⇒ 00:11:03.060 Uttam Kumaran: them a lot of like you and I can work on, although I don’t know. I feel like we. We already have
34 00:11:03.320 ⇒ 00:11:04.959 Uttam Kumaran: sort of what the core.
35 00:11:05.400 ⇒ 00:11:06.120 Amber Lin: Yeah.
36 00:11:06.350 ⇒ 00:11:07.140 Uttam Kumaran: Tables are.
37 00:11:07.140 ⇒ 00:11:13.109 Amber Lin: I think we can combine them into those building tickets, and then we can cancel these.
38 00:11:13.510 ⇒ 00:11:17.109 Amber Lin: I just know we haven’t completely defined everything yet.
39 00:11:17.590 ⇒ 00:11:18.250 Uttam Kumaran: Okay.
40 00:11:18.840 ⇒ 00:11:22.510 Demilade Agboola: Yeah, and also the.
41 00:11:23.640 ⇒ 00:11:36.409 Demilade Agboola: It’s just, it will be probably be things like the proper source. Like, do we use shopify? Do we use Oms, orders, the pros and cons of like using shopify versus the Oms data.
42 00:11:36.630 ⇒ 00:11:37.750 Amber Lin: Things like that.
43 00:11:39.030 ⇒ 00:11:39.730 Uttam Kumaran: Okay.
44 00:11:40.670 ⇒ 00:11:46.729 Uttam Kumaran: Okay. So for this one we don’t have, we’re not gonna have like an ex, any exports. So
45 00:11:46.910 ⇒ 00:11:52.799 Uttam Kumaran: I’m gonna cancel this one we have coming in, and we have the Ms stuff coming in. So
46 00:11:53.000 ⇒ 00:11:54.040 Uttam Kumaran: let me see.
47 00:12:03.070 ⇒ 00:12:04.950 Uttam Kumaran: Okay, so that’s fine.
48 00:13:44.260 ⇒ 00:13:49.269 Uttam Kumaran: Okay, I mean, I feel pretty good about this, I think, like, in terms of
49 00:13:51.940 ⇒ 00:13:58.319 Uttam Kumaran: like, probably going further on requirements. I don’t know them a lot of like I think we should just probably split up
50 00:13:58.520 ⇒ 00:14:04.890 Uttam Kumaran: like the most difficult, like new models, to create. And then
51 00:14:05.060 ⇒ 00:14:09.180 Uttam Kumaran: we can execute on those. And then I think,
52 00:14:10.890 ⇒ 00:14:18.260 Uttam Kumaran: that’s probably like at least step one. There’s also a lot of other things to do. For example, I’m working with
53 00:14:18.690 ⇒ 00:14:27.319 Uttam Kumaran: polytomic to bring in both north beam and loop. So that’s another item that just needs to be sort of tracked. They should have an update this week.
54 00:14:28.462 ⇒ 00:14:31.420 Uttam Kumaran: Additionally, we wanna make sure that
55 00:14:35.490 ⇒ 00:14:38.569 Uttam Kumaran: that we can also set up meta plane as we go.
56 00:14:39.243 ⇒ 00:14:43.619 Uttam Kumaran: Both of those are great things that we can also work on.
57 00:14:43.750 ⇒ 00:14:50.489 Uttam Kumaran: So I don’t know. I feel like those are probably like priority for me.
58 00:14:51.173 ⇒ 00:14:52.120 Uttam Kumaran: I think.
59 00:14:52.220 ⇒ 00:14:58.800 Uttam Kumaran: like we can go through, we can go through planning, I think, probably Kyle. What would probably most
60 00:14:58.900 ⇒ 00:15:04.420 Uttam Kumaran: I think effective. Here is like if we crush through like the 1st couple of like
61 00:15:05.300 ⇒ 00:15:13.960 Uttam Kumaran: core staging models or intermediate models, and then we can hand off for you to create the Martz models?
62 00:15:15.410 ⇒ 00:15:16.800 Uttam Kumaran: Just because I think it’s
63 00:15:17.590 ⇒ 00:15:19.810 Uttam Kumaran: I think it’s gonna be a little bit complicated.
64 00:15:20.349 ⇒ 00:15:29.250 Uttam Kumaran: But then, in the meantime, there are things that we can continue working on in parallel, like the work, to make sure. North beam lands, loop lands.
65 00:15:32.009 ⇒ 00:15:37.310 Uttam Kumaran: and there are some modeling tickets that are actually, I think, like
66 00:15:37.570 ⇒ 00:15:46.510 Uttam Kumaran: things. We we that don’t that aren’t like extremely complicated. So that’s probably what I would suggest in terms of like overall theme for planning today.
67 00:15:48.730 ⇒ 00:15:50.899 Caio Velasco: Okay, I I have just a question.
68 00:15:52.190 ⇒ 00:15:57.649 Caio Velasco: so would be also interesting for me to see. How far from
69 00:15:58.383 ⇒ 00:16:10.899 Caio Velasco: whatever you guys would view for well, raw and intermediate or staging is my, the ones that I made on orders of orders, line items, transactions.
70 00:16:11.501 ⇒ 00:16:22.419 Caio Velasco: Just to see if I was going on the right direction or not, because I spent some time on those, although it was just mainly replicating what is already there in their stage models.
71 00:16:23.300 ⇒ 00:16:24.379 Caio Velasco: But yeah.
72 00:16:25.219 ⇒ 00:16:28.519 Uttam Kumaran: That’s at the that’s at the end of the Tdd. Right.
73 00:16:29.370 ⇒ 00:16:40.470 Caio Velasco: Yes, but those are the the Td. Is just the the questions and and answers. But I have models that I built myself this. All the stage models.
74 00:16:42.410 ⇒ 00:16:47.959 Demilade Agboola: Do you have them in production? No, not production. Sorry. Do you have them in like a a brand?
75 00:16:48.190 ⇒ 00:16:48.830 Demilade Agboola: Yeah.
76 00:16:48.830 ⇒ 00:16:57.209 Caio Velasco: No. So I paid. I can tag you guys again. I just basically reproduced them from whatever they had already of them stems.
77 00:16:57.410 ⇒ 00:17:01.799 Caio Velasco: But just in a SQL. Code. There’s not a Dbt model.
78 00:17:01.900 ⇒ 00:17:08.079 Caio Velasco: Then I tested them. I mean, they are consuming because they’re just consuming from the sources like no, nothing big.
79 00:17:08.655 ⇒ 00:17:15.760 Caio Velasco: But I can also share. Maybe you guys can work on top of that, or I don’t know, because I’m also wondering if I was going in the right direction or not.
80 00:17:16.400 ⇒ 00:17:35.720 Uttam Kumaran: That’s helpful. Yeah, let’s do that. If you can send that over, then we can probably start from there. Yeah, probably my biggest point is that like? Since we’ve been planning for quite some time, I want to start to get a couple of core models out. Some of the more complicated stuff is going to be sub orders.
81 00:17:36.368 ⇒ 00:17:46.219 Uttam Kumaran: And some of these like line items, basically sub orders, line items, and transactions. I think dim customers.
82 00:17:46.460 ⇒ 00:17:50.849 Uttam Kumaran: We’ll be a little bit on the lighter side. Same with same with orders.
83 00:17:53.040 ⇒ 00:17:59.889 Uttam Kumaran: but I think there’s plenty of work so kind of like my goal, for this one is one like, I just want to get through as much
84 00:18:00.110 ⇒ 00:18:16.059 Uttam Kumaran: modeling this week and next week. But then, Kyle, in the in the meantime there are some things around some new sources. And then, in addition, I think we can continue to use the working sessions to walk through like how we’re modeling
85 00:18:17.510 ⇒ 00:18:24.609 Uttam Kumaran: which will basically, once we have, like the core marts, tables ready, or like at least the core staging models, it’ll be really
86 00:18:24.770 ⇒ 00:18:32.569 Uttam Kumaran: a lot easier to create the either the core fact tables or or the summary tables. So that’s where I think the handoff is best.
87 00:18:33.085 ⇒ 00:18:44.620 Uttam Kumaran: But like we’ll be kind of collaborating through the whole thing. So I think, probably my my other suggestion here is that we think through how we want to do the working sessions for the next 2 weeks.
88 00:18:45.934 ⇒ 00:18:47.470 Uttam Kumaran: Like, I think it’s
89 00:18:48.420 ⇒ 00:18:53.769 Uttam Kumaran: I think, like I mean particularly, I’ll need some sort of heads down time to just
90 00:18:54.210 ⇒ 00:19:02.990 Uttam Kumaran: probably build. But then I want to have user working sessions to share logic and to share, like any caveats that we found.
91 00:19:05.540 ⇒ 00:19:10.369 Uttam Kumaran: and I think we can continue to communicate. So it doesn’t seem like we’re just building for a few weeks, you know.
92 00:19:11.760 ⇒ 00:19:13.712 Demilade Agboola: Yeah, that’s fair enough.
93 00:19:15.200 ⇒ 00:19:29.900 Demilade Agboola: I see that Kai has just typed us in, but the models like he’s tagged us in it. But yeah, we can. We can definitely just like, split up, start building. And then we can sync on what we’ve done so far. You know.
94 00:19:29.900 ⇒ 00:19:30.490 Uttam Kumaran: Okay.
95 00:19:34.870 ⇒ 00:19:35.340 Amber Lin: Oh!
96 00:19:35.340 ⇒ 00:19:35.730 Caio Velasco: Cool.
97 00:19:39.410 ⇒ 00:19:42.150 Uttam Kumaran: So how do we wanna go through planning like, I mean.
98 00:19:42.474 ⇒ 00:19:50.910 Amber Lin: Sure, let me actually let me share my screen because I I just wanna have an idea of what we’re taking in and what we’re not.
99 00:19:52.820 ⇒ 00:19:59.610 Amber Lin: I think 1st off, we’re not doing these tickets right? We’re just doing them as we build.
100 00:20:00.780 ⇒ 00:20:03.329 Amber Lin: so I will cancel. I can cancel them.
101 00:20:07.930 ⇒ 00:20:10.420 Uttam Kumaran: Can you click on the second one?
102 00:20:19.440 ⇒ 00:20:24.220 Uttam Kumaran: Yeah. As long as these are in those modeling tickets, then I’m okay.
103 00:20:25.041 ⇒ 00:20:34.519 Amber Lin: Okay, so I will clear them out later. And then do we need this dbt folder structure, naming conventions, tacky sanders.
104 00:20:34.520 ⇒ 00:20:40.310 Uttam Kumaran: I’m I’m comfortable with Kyle. What? What? You
105 00:20:40.690 ⇒ 00:20:44.690 Uttam Kumaran: what we had in the Tdd. Can we let me just open that up one more time.
106 00:20:44.950 ⇒ 00:20:45.660 Amber Lin: Yeah. Totally.
107 00:20:46.590 ⇒ 00:20:48.840 Uttam Kumaran: So if I go to tagging
108 00:20:55.520 ⇒ 00:21:02.430 Uttam Kumaran: yeah. So in terms of like the modeling layer, I think, probably. Okay, maybe I can. Maybe I’ll share.
109 00:21:02.790 ⇒ 00:21:03.530 Amber Lin: Yeah.
110 00:21:06.020 ⇒ 00:21:08.660 Uttam Kumaran: I didn’t add this last time, but
111 00:21:09.070 ⇒ 00:21:14.939 Uttam Kumaran: I guess question for everyone. Do we want to have like staging and int
112 00:21:16.130 ⇒ 00:21:22.720 Uttam Kumaran: like, or should we consider just having like one.
113 00:21:25.140 ⇒ 00:21:26.429 Demilade Agboola: What do you mean by one.
114 00:21:27.040 ⇒ 00:21:36.410 Uttam Kumaran: Like, do we need to do? We need 2 intermediate like modeling layers, basically.
115 00:21:37.955 ⇒ 00:21:46.674 Demilade Agboola: So I think we can handle staging in the sense of very like light transformations done there. So that’s usually like
116 00:21:47.090 ⇒ 00:21:47.830 Uttam Kumaran: Okay.
117 00:21:47.830 ⇒ 00:21:59.909 Demilade Agboola: The type kind of changes, or like maybe minor divisions converting hours to, you know, seconds whatever, like those kind of little changes.
118 00:22:01.310 ⇒ 00:22:05.690 Demilade Agboola: But then, I think, int models, we should try to do more heavy
119 00:22:05.870 ⇒ 00:22:13.520 Demilade Agboola: transformations, and like, if you like, if you look at the inventory flow.
120 00:22:13.630 ⇒ 00:22:14.480 Uttam Kumaran: Yeah.
121 00:22:14.770 ⇒ 00:22:18.820 Demilade Agboola: The 8 models have, like the logic of the different parts of
122 00:22:19.700 ⇒ 00:22:24.140 Demilade Agboola: that way, like, if something is up with, say.
123 00:22:24.750 ⇒ 00:22:33.980 Demilade Agboola: we deliver like we deliver it orders, or we delivered orders or things around a certain type setting flow. It’s much easy, for, like
124 00:22:35.060 ⇒ 00:22:41.919 Demilade Agboola: emulator, just go there, make the fix, and that just propagates into the final math models where we’re aggregating these things.
125 00:22:42.210 ⇒ 00:22:47.889 Demilade Agboola: So yeah, I think we should be able to have like int models where we can have those sort of high, heavier
126 00:22:49.168 ⇒ 00:22:53.940 Demilade Agboola: transformation. Then we can have mass models where we’re building towards like the final dashboard.
127 00:22:54.380 ⇒ 00:23:00.480 Demilade Agboola: And then we can also have like facts, models like in terms of like in those in those like
128 00:23:01.980 ⇒ 00:23:12.100 Demilade Agboola: in that folder like orders. And you know customers where potentially, if they want to do some exploratory data analysis, they can just do some
129 00:23:12.290 ⇒ 00:23:16.950 Demilade Agboola: without necessarily always waiting for a final math model.
130 00:23:19.950 ⇒ 00:23:21.359 Uttam Kumaran: Okay, I’m fine with that.
131 00:23:29.590 ⇒ 00:23:35.550 Uttam Kumaran: yeah. And then, probably for this one, I’m just gonna say, polyatomic reverse, etl
132 00:23:41.930 ⇒ 00:23:49.410 Uttam Kumaran: for loop. We’re gonna I mean, we’re gonna pull this Via Api. So this one, I’m gonna remove
133 00:23:49.770 ⇒ 00:23:52.039 Uttam Kumaran: budgets. Yeah, we’re gonna have through sheets.
134 00:23:52.430 ⇒ 00:23:53.980 Uttam Kumaran: This one. I’m not
135 00:23:57.080 ⇒ 00:23:58.430 Uttam Kumaran: sure yet.
136 00:23:59.630 ⇒ 00:24:04.409 Uttam Kumaran: I don’t know, cause I know we have stuff coming through G seats, g sheets.
137 00:24:08.750 ⇒ 00:24:11.090 Uttam Kumaran: So that’s 1
138 00:24:36.400 ⇒ 00:24:40.429 Uttam Kumaran: I think one other environment we can consider. Here is sandbox.
139 00:24:43.430 ⇒ 00:24:50.260 Uttam Kumaran: I don’t know how you do the red, but basically, this can be like a per person playground.
140 00:24:50.840 ⇒ 00:25:03.530 Uttam Kumaran: We will have dev. But Dev will be, for, like running pipelines, locally
141 00:25:05.010 ⇒ 00:25:11.360 Uttam Kumaran: staging will be restricted to basically like full requests.
142 00:25:13.280 ⇒ 00:25:17.820 Uttam Kumaran: And then Prod is going to be production.
143 00:25:18.250 ⇒ 00:25:26.160 Uttam Kumaran: So kind of the point of this is that there’s 2 environments that are kind of you’re not gonna be able to edit directly
144 00:25:26.320 ⇒ 00:25:32.140 Uttam Kumaran: you have one environment here where you can run entire stuff. And then sandbox is like you can do whatever you want, basically.
145 00:25:35.160 ⇒ 00:25:36.889 Uttam Kumaran: so that’s fine.
146 00:25:37.822 ⇒ 00:25:39.510 Uttam Kumaran: We have github.
147 00:25:40.700 ⇒ 00:25:45.779 Uttam Kumaran: And then, yeah, let’s keep going. So dbt, yeah, go ahead.
148 00:25:46.160 ⇒ 00:25:52.010 Demilade Agboola: Is Kyle going to use the cloud or using Dbt core.
149 00:25:54.030 ⇒ 00:25:56.759 Uttam Kumaran: I feel like we’re going to use
150 00:25:59.480 ⇒ 00:26:06.000 Uttam Kumaran: cloud. But you can run like you can trigger cloud jobs from the Cli.
151 00:26:06.560 ⇒ 00:26:11.639 Uttam Kumaran: But I feel like we’re gonna do everything in cloud. That’s what this is that they’re interested in doing that.
152 00:26:12.580 ⇒ 00:26:14.190 Uttam Kumaran: Why did I mess mine up.
153 00:26:17.230 ⇒ 00:26:26.790 Demilade Agboola: No, I I just wanted to know what well, whether Kyle was going to be working in the Cli or not, like in the well cli or cloud, basically.
154 00:26:26.790 ⇒ 00:26:31.080 Uttam Kumaran: I think there is a cloud. Cli right.
155 00:26:31.380 ⇒ 00:26:35.130 Demilade Agboola: I mean there is. But I’m not the biggest fan of
156 00:26:35.560 ⇒ 00:26:45.039 Demilade Agboola: of Dbt. Cloud. You can always have its I mean, I use it done. But like sometimes I’m just, I’m frustrated because it feels very. It feels very
157 00:26:45.740 ⇒ 00:26:46.620 Demilade Agboola: frustrating.
158 00:26:46.620 ⇒ 00:26:55.239 Uttam Kumaran: Like. Well, one thing we can do is we can make sure all of our local environments are set up so you can run Dbt. On your machine
159 00:26:55.600 ⇒ 00:26:56.890 Uttam Kumaran: if you’d like.
160 00:26:57.790 ⇒ 00:27:01.470 Uttam Kumaran: In addition to triggering stuff on the cloud.
161 00:27:01.760 ⇒ 00:27:02.480 Demilade Agboola: Fair enough.
162 00:27:03.660 ⇒ 00:27:06.670 Uttam Kumaran: So maybe that’s 1 thing that we can
163 00:27:09.150 ⇒ 00:27:14.539 Uttam Kumaran: Maybe amber. Can we add that as a ticket it’s just like configuring all Dbt environments.
164 00:27:15.400 ⇒ 00:27:16.780 Uttam Kumaran: I can get mine set up.
165 00:27:16.780 ⇒ 00:27:17.709 Caio Velasco: That’s a question.
166 00:27:18.110 ⇒ 00:27:18.950 Uttam Kumaran: Yeah.
167 00:27:20.020 ⇒ 00:27:29.080 Caio Velasco: So that’s a question I had like. Is there anything that would prevent us from using Dbt core locally because I always use it? I didn’t know that I thought that Dbt cloud was just an addition.
168 00:27:30.260 ⇒ 00:27:38.130 Uttam Kumaran: Yeah. So for our other clients, the way we get around this is, we run Dbt core for free like on Github.
169 00:27:40.910 ⇒ 00:27:45.330 Uttam Kumaran: But it’s just not the most like collaborative environment, meaning like
170 00:27:45.736 ⇒ 00:27:52.039 Uttam Kumaran: for for Emily. And I think for some of the other folks like it would be hard for them to manage additionally
171 00:27:52.590 ⇒ 00:28:08.380 Uttam Kumaran: like, if a client is willing to pay for Dbt. Cloud, I I actually would rather that meaning it gives us both options like you can run stuff locally using the Cli or use cloud. Dbt core is something we did for other clients, just because it’s
172 00:28:08.810 ⇒ 00:28:13.629 Uttam Kumaran: kind of expensive to to keep that going, and it’s not like
173 00:28:14.230 ⇒ 00:28:19.480 Uttam Kumaran: it’s not like extremely crucial to have it, but it is nice, like they run all our jobs.
174 00:28:19.670 ⇒ 00:28:21.920 Uttam Kumaran: There is an inbuilt ide
175 00:28:22.433 ⇒ 00:28:30.089 Uttam Kumaran: like it’s a it’s a bit nicer. But I still want to enable us to be able to do dbt run in like in cursor. For example.
176 00:28:30.240 ⇒ 00:28:33.220 Uttam Kumaran: versus having to go test that out
177 00:28:33.450 ⇒ 00:28:36.360 Uttam Kumaran: in cloud like, go click a bunch of buttons to do that. You know
178 00:28:39.560 ⇒ 00:28:45.280 Uttam Kumaran: there’s no there’s there’s really like no difference, though, like Dbt, core is what’s getting run by cloud.
179 00:28:45.967 ⇒ 00:28:48.472 Uttam Kumaran: Think more. My point is that
180 00:28:49.140 ⇒ 00:28:56.960 Uttam Kumaran: what’s what’s actually orchestrating and like running it is, is cloud. Is not our gonna be our Github actions.
181 00:29:01.550 ⇒ 00:29:05.680 Amber Lin: So essentially, we’re asking the clients, hey, are you willing to pay for this.
182 00:29:05.960 ⇒ 00:29:08.160 Uttam Kumaran: Well, they’re already paying for it, like they already have it. Yeah.
183 00:29:09.650 ⇒ 00:29:10.190 Amber Lin: So when I.
184 00:29:10.220 ⇒ 00:29:14.670 Demilade Agboola: Yesterday that they had to re-up their payments, which I think they’ve done.
185 00:29:14.670 ⇒ 00:29:21.729 Amber Lin: Oh, okay. So what am I creating a ticket for? Is just for us to decide if we wanna use the cloud.
186 00:29:23.192 ⇒ 00:29:26.630 Uttam Kumaran: No, it’s just to set up our local environments.
187 00:29:26.630 ⇒ 00:29:27.520 Amber Lin: Oh, okay.
188 00:29:28.125 ⇒ 00:29:28.730 Uttam Kumaran: Yeah.
189 00:29:29.160 ⇒ 00:29:40.729 Caio Velasco: But I haven’t set up anything with like Github actions, or anything but set up setting up Dbt. Core as a whole with requirements. Dot AV I have everything in my rep. My personal repos to be honest.
190 00:29:40.880 ⇒ 00:29:44.250 Uttam Kumaran: And then you’re able to run. You’re able to do dbt run, and it works.
191 00:29:44.510 ⇒ 00:29:47.040 Caio Velasco: When I build my own projects. Yes, always.
192 00:29:47.720 ⇒ 00:29:49.190 Uttam Kumaran: No, no! For this project.
193 00:29:49.430 ⇒ 00:29:51.680 Caio Velasco: I haven’t haven’t haven’t checked. No.
194 00:29:52.060 ⇒ 00:29:58.440 Uttam Kumaran: Okay. So that’s yeah. That’s mainly it’s like I want. I want you to be able to do dbt run. And then it it creates it in redshift.
195 00:29:59.010 ⇒ 00:29:59.730 Caio Velasco: Okay. Okay.
196 00:29:59.730 ⇒ 00:30:00.970 Uttam Kumaran: Yeah, like that hook up.
197 00:30:01.370 ⇒ 00:30:13.679 Uttam Kumaran: But the way that’s gonna work is a command will get triggered to Dbt. Cloud. So when you do Dbt. Run, it’ll get piled, compiled, sent to Cloud, and then Cloud will execute on redshift
198 00:30:14.190 ⇒ 00:30:22.589 Uttam Kumaran: but I’ll I’ll walk you guys through it because it’s the 1st time. I think we’ve so first, st like Dbc. Cloud customer. So we’ll we’ll walk through that. That’d be good.
199 00:30:22.930 ⇒ 00:30:28.399 Caio Velasco: Oh, and so that’s why we want Ember to set up those things.
200 00:30:37.180 ⇒ 00:30:40.600 Amber Lin: Wait. What am I setting up? I made the ticket.
201 00:30:41.310 ⇒ 00:30:43.269 Uttam Kumaran: You’re just. You’re just creating the ticket.
202 00:30:43.270 ⇒ 00:30:48.448 Amber Lin: Yes, okay, that makes more sense. Okay.
203 00:30:49.130 ⇒ 00:30:54.161 Amber Lin: alright. So first, st the auditing parts.
204 00:30:55.260 ⇒ 00:30:58.239 Uttam Kumaran: But let me just can we just walk through this last piece? Really.
205 00:30:58.240 ⇒ 00:30:59.869 Amber Lin: Yeah, sure. Sure. Yeah. Go ahead.
206 00:31:00.403 ⇒ 00:31:03.069 Uttam Kumaran: Okay? So dvt project deployment.
207 00:31:03.250 ⇒ 00:31:08.020 Uttam Kumaran: That’s fine warehouse schema management.
208 00:31:09.768 ⇒ 00:31:12.641 Uttam Kumaran: We don’t need this. It’s fine.
209 00:31:19.510 ⇒ 00:31:23.580 Uttam Kumaran: okay, that’s fine testing blah blah.
210 00:31:35.840 ⇒ 00:31:37.470 Uttam Kumaran: Oh.
211 00:31:49.550 ⇒ 00:31:57.400 Uttam Kumaran: okay, so this is fine raw stage. And so I guess my my other question, okay, so we have raw stage.
212 00:31:57.750 ⇒ 00:32:00.410 Uttam Kumaran: So yeah, I think this is probably
213 00:32:01.230 ⇒ 00:32:07.450 Uttam Kumaran: okay. So based on what you said, we’re gonna have everything land into raw and then
214 00:32:08.310 ⇒ 00:32:13.689 Uttam Kumaran: clean and duplicate. So deduplicate sources. Okay, it’s fine.
215 00:32:14.860 ⇒ 00:32:17.620 Uttam Kumaran: This is fine. Okay, where are the tags?
216 00:32:30.030 ⇒ 00:32:32.630 Uttam Kumaran: Did we put like Dvt tags anywhere here.
217 00:32:35.340 ⇒ 00:32:36.810 Caio Velasco: I don’t remember.
218 00:32:36.810 ⇒ 00:32:37.940 Demilade Agboola: I hope there’s some.
219 00:32:38.270 ⇒ 00:32:39.489 Caio Velasco: Yeah, I don’t think so.
220 00:32:40.070 ⇒ 00:32:45.020 Uttam Kumaran: So one thing that we can. Yeah, 1 1 thing that we can do is start to tag
221 00:32:45.920 ⇒ 00:32:49.240 Uttam Kumaran: models by like the mart they’re in
222 00:32:51.940 ⇒ 00:32:54.829 Uttam Kumaran: I think that’s probably something I’ll put
223 00:32:59.360 ⇒ 00:33:02.230 Uttam Kumaran: I guess it’s in cement. I guess it’s in.
224 00:33:07.480 ⇒ 00:33:08.280 Uttam Kumaran: Come on.
225 00:33:08.670 ⇒ 00:33:09.400 Demilade Agboola: I mean dude.
226 00:33:09.866 ⇒ 00:33:13.129 Amber Lin: Early or late. Oh, you go ahead.
227 00:33:13.530 ⇒ 00:33:17.160 Demilade Agboola: You can, just. You could also do it within the folder structure.
228 00:33:18.000 ⇒ 00:33:19.730 Uttam Kumaran: Oh, okay.
229 00:33:20.070 ⇒ 00:33:24.590 Demilade Agboola: Yeah, so you could just basically in Dbt product, the yaml you can like.
230 00:33:24.760 ⇒ 00:33:29.179 Demilade Agboola: put out the folder structure. And for each of the folders. Kind of give it a tag.
231 00:33:31.720 ⇒ 00:33:32.610 Demilade Agboola: Okay?
232 00:33:32.610 ⇒ 00:33:33.100 Uttam Kumaran: No.
233 00:33:33.100 ⇒ 00:33:33.690 Demilade Agboola: But also.
234 00:33:33.690 ⇒ 00:33:35.630 Uttam Kumaran: Yeah. Go ahead.
235 00:33:35.630 ⇒ 00:33:39.880 Demilade Agboola: You’ve also that’s faster than if you were going to do it by model by model basis.
236 00:33:42.920 ⇒ 00:33:53.710 Demilade Agboola: So you can, for instance, name different Mods different things, so you can have, like the finance. MoD, give it a tag. You can have the revenue match. Give that a tag as well.
237 00:33:54.539 ⇒ 00:34:04.959 Demilade Agboola: So you can. Now, if you need to set up jobs, you can set up jobs that run revenue, mount upstream or finance math upstream or inventory amount upstream.
238 00:34:10.320 ⇒ 00:34:13.330 Uttam Kumaran: Okay, I think that’s fine. I think we can get to this.
239 00:34:16.900 ⇒ 00:34:25.980 Uttam Kumaran: okay, cool. So I think we can. That’s probably the last thing I had is just to make sure that we’re we can consider that. And then, okay, so let’s maybe let’s move to talking through
240 00:34:28.135 ⇒ 00:34:28.640 Uttam Kumaran: planning.
241 00:34:30.020 ⇒ 00:34:33.019 Amber Lin: Okay, I’ll share screen.
242 00:34:34.159 ⇒ 00:34:42.069 Amber Lin: I added 2 tickets for Dvt, so set of local environment time, add tags.
243 00:34:42.409 ⇒ 00:34:48.989 Amber Lin: And then my question here, do we need these ingestion tickets.
244 00:34:49.260 ⇒ 00:34:51.989 Amber Lin: There’s 2 to check
245 00:34:52.429 ⇒ 00:34:59.749 Amber Lin: on if they can bring North Beyonder loop. Do we decide not to go a Hebrew or stitch? If so I’ll cancel this one.
246 00:35:00.900 ⇒ 00:35:02.999 Uttam Kumaran: Yeah, we’re gonna go with polytomic.
247 00:35:03.000 ⇒ 00:35:09.670 Amber Lin: Okay, awesome. Are we doing any of these ingestion.
248 00:35:13.410 ⇒ 00:35:16.309 Uttam Kumaran: Not 2 90. We’re not doing 2, 92.
249 00:35:17.690 ⇒ 00:35:19.649 Amber Lin: We’re not doing.
250 00:35:20.490 ⇒ 00:35:27.670 Uttam Kumaran: So yeah, or basically, we can. What we can do is we can turn 2 92. And to
251 00:35:28.265 ⇒ 00:35:34.270 Uttam Kumaran: what’s the what’s the one? Yeah, 2, 90. These ones we basically just have to confirm.
252 00:35:35.040 ⇒ 00:35:38.300 Uttam Kumaran: like validate, the polyatomic ingestion from.
253 00:35:38.820 ⇒ 00:35:45.299 Uttam Kumaran: So we could just change like, I would create 2 tickets, though.
254 00:35:47.120 ⇒ 00:35:48.160 Amber Lin: Valid.
255 00:35:48.160 ⇒ 00:35:55.479 Uttam Kumaran: And then I I don’t know. I still think that the probably, whatever was in that document, those tickets are still helpful. Maybe we could.
256 00:35:56.080 ⇒ 00:35:56.930 Uttam Kumaran: Yeah.
257 00:35:56.930 ⇒ 00:35:58.179 Amber Lin: Good feeling back.
258 00:35:58.560 ⇒ 00:36:00.660 Amber Lin: I’ll just edit their titles.
259 00:36:01.000 ⇒ 00:36:12.340 Uttam Kumaran: Yeah. So if you click through it, so we can probably just edit the key question.
260 00:36:12.510 ⇒ 00:36:15.289 Uttam Kumaran: You can remove everything else through the bottom.
261 00:36:16.731 ⇒ 00:36:21.709 Uttam Kumaran: Basic like, you can actually remove everything on the bottom. Basically, we just wanna confirm
262 00:36:21.830 ⇒ 00:36:27.469 Uttam Kumaran: that all necessary models are coming in to power.
263 00:36:28.740 ⇒ 00:36:30.040 Uttam Kumaran: The loop mark.
264 00:36:32.110 ⇒ 00:36:37.040 Uttam Kumaran: And this one I think, Kyle, you can take on. I think it’ll give you some interaction with
265 00:36:37.480 ⇒ 00:36:40.809 Uttam Kumaran: polyatomic and kind of show you some of the ingestion pieces.
266 00:36:43.600 ⇒ 00:36:46.470 Uttam Kumaran: And otherwise I will definitely forget to do these.
267 00:36:47.640 ⇒ 00:36:52.750 Uttam Kumaran: I’ll also make sure you’re in the Channel. We have a channel with them. I don’t know if you’re in there, but I’ll add you there.
268 00:36:53.860 ⇒ 00:36:54.650 Caio Velasco: I’ll check.
269 00:36:56.310 ⇒ 00:36:58.019 Uttam Kumaran: Yeah, I think you’re in there.
270 00:36:58.020 ⇒ 00:36:59.669 Caio Velasco: Yeah, I have vendor polytomic.
271 00:37:00.220 ⇒ 00:37:01.170 Uttam Kumaran: Yeah, perfect.
272 00:37:06.520 ⇒ 00:37:10.670 Uttam Kumaran: though you can see. I just asked them about both the other day, like
273 00:37:10.930 ⇒ 00:37:14.259 Uttam Kumaran: I think they they said they were given updates. So this one, I think
274 00:37:14.560 ⇒ 00:37:18.699 Uttam Kumaran: we could probably put by at end of week. The main thing is just to
275 00:37:19.550 ⇒ 00:37:21.779 Uttam Kumaran: every few days ask them for an update.
276 00:37:22.640 ⇒ 00:37:27.000 Uttam Kumaran: And then once they land it, it’ll be like turning on checking out the tables.
277 00:37:27.990 ⇒ 00:37:28.700 Uttam Kumaran: Yeah.
278 00:37:46.650 ⇒ 00:37:47.380 Amber Lin: Okay?
279 00:37:51.860 ⇒ 00:37:54.709 Amber Lin: So we have polyatomic north beam.
280 00:37:55.495 ⇒ 00:37:58.420 Amber Lin: Are we doing any of
281 00:38:00.890 ⇒ 00:38:03.310 Amber Lin: These people.
282 00:38:04.480 ⇒ 00:38:05.920 Amber Lin: Is it already done.
283 00:38:07.350 ⇒ 00:38:11.050 Uttam Kumaran: Can we remove? 2, 91.
284 00:38:13.000 ⇒ 00:38:14.269 Uttam Kumaran: Or what is this one.
285 00:38:15.870 ⇒ 00:38:16.429 Amber Lin: Are you? Click it.
286 00:38:21.860 ⇒ 00:38:25.549 Uttam Kumaran: Oh, yeah, okay, let’s yeah. Let’s just mark this as canceled.
287 00:38:27.900 ⇒ 00:38:30.197 Uttam Kumaran: I mean, better have the stuff.
288 00:38:30.820 ⇒ 00:38:34.090 Uttam Kumaran: stitch pipeline. What is a stitch pipeline decommissioning.
289 00:38:35.388 ⇒ 00:38:39.839 Amber Lin: I believe in a document. This is AI. I think, a sense that they we were.
290 00:38:40.050 ⇒ 00:38:45.120 Uttam Kumaran: Is there anything? Is there anything we need to remove from stitch? Part of this.
291 00:38:45.810 ⇒ 00:38:48.650 Demilade Agboola: I’m not sure. I don’t think there is anything to remove from set.
292 00:38:49.310 ⇒ 00:38:49.970 Uttam Kumaran: Okay.
293 00:38:50.240 ⇒ 00:38:56.099 Amber Lin: I’ll cancel that do we still need this one to check Hevo.
294 00:39:03.870 ⇒ 00:39:06.610 Uttam Kumaran: yeah, you can leave this. It’s fine.
295 00:39:09.120 ⇒ 00:39:16.730 Demilade Agboola: I think, in the sense of auditing hero pipelines. I don’t know. Are we? Are we thinking about? If
296 00:39:17.660 ⇒ 00:39:22.030 Demilade Agboola: isn’t, isn’t that just like validating the sources that we’re going to use for this project.
297 00:39:23.770 ⇒ 00:39:27.560 Uttam Kumaran: Yeah, basically, I just want to check like that. We’re getting everything from shopify.
298 00:39:27.900 ⇒ 00:39:31.800 Uttam Kumaran: Okay? So cause auditing just made it sound like, yeah, I,
299 00:39:31.800 ⇒ 00:39:34.590 Uttam Kumaran: yeah, yeah, you can just do validate. Yeah, that’s fine.
300 00:39:36.360 ⇒ 00:39:41.797 Uttam Kumaran: I’m it’s just like, I’m gonna go do that, anyway. So we might as well just have documented
301 00:39:42.650 ⇒ 00:39:48.390 Uttam Kumaran: build data val validation layer this one is kind of overkill.
302 00:39:49.100 ⇒ 00:39:49.760 Amber Lin: Okay.
303 00:39:52.680 ⇒ 00:39:53.610 Amber Lin: Alright.
304 00:39:56.020 ⇒ 00:40:00.869 Amber Lin: I’ll have Kyle check in on these 2.
305 00:40:01.140 ⇒ 00:40:02.080 Amber Lin: Yeah, that’s.
306 00:40:02.080 ⇒ 00:40:06.940 Uttam Kumaran: Fine, and both of them you can put like 1 point, because it’s just making sure that they land.
307 00:40:07.230 ⇒ 00:40:08.660 Amber Lin: Okay.
308 00:40:09.020 ⇒ 00:40:16.080 Uttam Kumaran: Check. If polyatomic can bring in, we can mark that one as duplicate, or
309 00:40:16.550 ⇒ 00:40:19.175 Uttam Kumaran: I’ve already checked. Yeah, whatever
310 00:40:20.090 ⇒ 00:40:22.130 Uttam Kumaran: And then what is 3, 17.
311 00:40:24.230 ⇒ 00:40:28.479 Amber Lin: Oh, that’s a note of what we’re gonna do.
312 00:40:28.480 ⇒ 00:40:29.640 Uttam Kumaran: Okay, okay, cool.
313 00:40:30.708 ⇒ 00:40:37.549 Uttam Kumaran: Yeah. I feel like for the staging. Let’s just split it half and half.
314 00:40:39.010 ⇒ 00:40:45.860 Uttam Kumaran: Between them a lot. And I but like, what are some good splits we can do like, I mean.
315 00:40:45.860 ⇒ 00:40:48.850 Uttam Kumaran: devil. I can take transactions.
316 00:40:50.940 ⇒ 00:40:55.190 Uttam Kumaran: Yeah, I can take any of the financials if you want to take orders.
317 00:40:56.760 ⇒ 00:40:57.350 Demilade Agboola: Yeah, sure.
318 00:40:57.850 ⇒ 00:40:58.890 Uttam Kumaran: What do you think?
319 00:41:00.210 ⇒ 00:41:01.610 Demilade Agboola: Sure, or this is fine.
320 00:41:01.610 ⇒ 00:41:04.979 Uttam Kumaran: And then I’m gonna take the subscription stuff as soon as loops ready.
321 00:41:06.480 ⇒ 00:41:09.250 Uttam Kumaran: and then line items is in orders. World.
322 00:41:09.630 ⇒ 00:41:10.390 Demilade Agboola: Yeah.
323 00:41:11.890 ⇒ 00:41:12.570 Uttam Kumaran: Okay.
324 00:41:13.270 ⇒ 00:41:15.520 Demilade Agboola: And it won’t kind of like strike through.
325 00:41:16.290 ⇒ 00:41:21.390 Demilade Agboola: because that’s their like forced upgrades model. But I mean, we’re going to.
326 00:41:21.390 ⇒ 00:41:25.650 Uttam Kumaran: For that like for that, aren’t we? Just gonna like, put in the call.
327 00:41:25.650 ⇒ 00:41:28.469 Demilade Agboola: Yeah, I mean, so this.
328 00:41:28.470 ⇒ 00:41:32.210 Uttam Kumaran: I guess you can create a new. You can create a new table. I guess if you want. Yeah.
329 00:41:32.210 ⇒ 00:41:38.430 Demilade Agboola: Yeah. So this is based off how they have it built. I probably will just do my own thing or no problem. I will do my own thing.
330 00:41:39.350 ⇒ 00:41:41.610 Demilade Agboola: but I will look at how like
331 00:41:41.850 ⇒ 00:41:45.839 Demilade Agboola: where some of that data is coming from, and how to rebuild it.
332 00:41:51.632 ⇒ 00:41:57.419 Amber Lin: Based on that? Do I make a new staging? Subscriptions ticket.
333 00:42:02.300 ⇒ 00:42:03.997 Uttam Kumaran: No, there is cause there is
334 00:42:04.730 ⇒ 00:42:07.160 Amber Lin: Oh, just this one, right. Fax subscription.
335 00:42:07.160 ⇒ 00:42:12.770 Uttam Kumaran: I would just I would just leave that. I’ll I’ll create it if I end up doing it. I just don’t know.
336 00:42:12.770 ⇒ 00:42:21.169 Amber Lin: Okay, sounds good. Any. Do we still need the refund? When I was reading the document we said this might not be needed.
337 00:42:22.100 ⇒ 00:42:24.170 Amber Lin: or something along those lines.
338 00:42:31.060 ⇒ 00:42:32.360 Uttam Kumaran: For refunds.
339 00:42:32.840 ⇒ 00:42:37.780 Amber Lin: Yeah, it might not be oms refunds. I remember something about refunds.
340 00:42:38.450 ⇒ 00:42:42.180 Demilade Agboola: I don’t know about refund specifically. But we also need to just figure out, like.
341 00:42:42.810 ⇒ 00:42:46.050 Demilade Agboola: how much of Lms data we want to rely on versus.
342 00:42:46.050 ⇒ 00:42:47.300 Amber Lin: Yeah, okay.
343 00:42:48.090 ⇒ 00:42:53.990 Uttam Kumaran: You? Yeah, you could. So you can anything of the anything on the financial side you can add
344 00:42:54.160 ⇒ 00:42:55.420 Uttam Kumaran: for me?
345 00:42:56.350 ⇒ 00:42:59.710 Uttam Kumaran: I guess this one will be somewhat between us. But
346 00:43:01.490 ⇒ 00:43:04.050 Uttam Kumaran: yeah, I’m I’ll I’ll handle this. And then
347 00:43:04.774 ⇒ 00:43:09.439 Uttam Kumaran: Demoda, I can make this available to you if you need to pull something from here, but
348 00:43:09.720 ⇒ 00:43:13.380 Uttam Kumaran: I’m gonna pull. I’ll pull this from shopify. So.
349 00:43:13.380 ⇒ 00:43:14.300 Demilade Agboola: Yeah, okay.
350 00:43:14.970 ⇒ 00:43:17.149 Uttam Kumaran: Yeah, I don’t. I can pull this from shopify.
351 00:43:20.160 ⇒ 00:43:27.845 Uttam Kumaran: Basically the way I’m gonna do transactions to give everyone like a little bit of a sense of like, how transactions works like if you think about
352 00:43:29.160 ⇒ 00:43:33.369 Uttam Kumaran: like, if you think about a ledger and you think about different
353 00:43:33.670 ⇒ 00:43:47.220 Uttam Kumaran: money, related events right. You could have a spend, you can have a cancellation. You could have a refund and so we want all of those events to actually be in in one table.
354 00:43:47.370 ⇒ 00:43:52.309 Uttam Kumaran: so that when you look at a single order, for example, like you look at an order, Id, you’ll get
355 00:43:52.510 ⇒ 00:43:55.989 Uttam Kumaran: both the amount of money that came in and the amount of money that went out
356 00:43:56.100 ⇒ 00:44:11.859 Uttam Kumaran: versus updating a single record. So it’s it is like a ledger, right? So typically like when they invented like ledgers. The reason like, it’s like a ledger. Because you write down like someone bought this. Okay, they were. They return this, or they like, we’re gonna discount this. And they’re all individual events.
357 00:44:12.020 ⇒ 00:44:16.499 Amber Lin: So yeah, that’s how we’ll be doing transactions.
358 00:44:16.930 ⇒ 00:44:17.680 Amber Lin: Okay.
359 00:44:17.980 ⇒ 00:44:28.539 Caio Velasco: Question on that. When shopify has a transactions table. Why is, do you know why it’s not done in that way? Because that’s that’s a very basic accounting thing, right?
360 00:44:29.670 ⇒ 00:44:34.909 Uttam Kumaran: Yeah, you’re right. I I think it’s because the I mean
361 00:44:35.090 ⇒ 00:44:44.379 Uttam Kumaran: I can only guess. But the way I think about it is that their customers see transactions as just revenue, positive events.
362 00:44:44.770 ⇒ 00:44:45.300 Caio Velasco: Harm.
363 00:44:45.300 ⇒ 00:44:50.449 Uttam Kumaran: Versus like versus like
364 00:44:51.004 ⇒ 00:44:58.249 Uttam Kumaran: refund transaction is a transaction, but it’s a negative event. So I don’t know. I I also agree with you like.
365 00:44:58.570 ⇒ 00:45:09.580 Uttam Kumaran: I think this should. It should all be just event based items that affect a few metrics. But typically we stitch that like, if you go into the way we did for pool parts.
366 00:45:09.720 ⇒ 00:45:13.620 Uttam Kumaran: you’ll see that we actually bring in the refund transactions in
367 00:45:15.120 ⇒ 00:45:17.099 Uttam Kumaran: yeah, I don’t know. I don’t know why.
368 00:45:17.770 ⇒ 00:45:21.849 Caio Velasco: Yeah, but but they save the the events like like a Cdc kind of thing.
369 00:45:23.310 ⇒ 00:45:33.270 Uttam Kumaran: Yeah, that’s how it should be. Because you basically want to see all transaction related events to a specific set of dimensions. So all the events, because then you can quickly look at like.
370 00:45:33.780 ⇒ 00:45:37.730 Uttam Kumaran: otherwise, you’re yeah. You’re basically you have to update the values in a row
371 00:45:38.120 ⇒ 00:45:49.260 Uttam Kumaran: right? Instead, like, I want to be. I just want the full history of transactions, and if you’re pulling orders and you’re pulling the latest, you can go do that on top of that right?
372 00:45:50.408 ⇒ 00:45:54.359 Uttam Kumaran: Versus, like. We need some record of everything in one area.
373 00:45:54.630 ⇒ 00:45:57.590 Uttam Kumaran: But I’ll I could show you once it’s done like, how.
374 00:45:57.590 ⇒ 00:45:58.160 Caio Velasco: Okay.
375 00:45:58.160 ⇒ 00:45:59.559 Uttam Kumaran: We stitch it. Yeah.
376 00:46:00.590 ⇒ 00:46:01.280 Caio Velasco: Thank you.
377 00:46:02.190 ⇒ 00:46:08.574 Amber Lin: Alright for transactions. Shop transactions, refunds. I put it on a new term.
378 00:46:09.160 ⇒ 00:46:17.240 Amber Lin: Orders sub orders line items. I put on time a lot 8. Is that the same for the split line items.
379 00:46:20.470 ⇒ 00:46:30.240 Demilade Agboola: I mean technically, yes. It’s just if we will remodel them the same way, like we’ll model them the same way that they are currently modeled right now.
380 00:46:30.450 ⇒ 00:46:34.630 Demilade Agboola: But yeah, you should. You can assign them to me as well.
381 00:46:35.516 ⇒ 00:46:43.029 Amber Lin: Okay, we’ll see. If then, I guess we’ll see if we still need them, i’ll put a tag
382 00:46:43.950 ⇒ 00:46:52.110 Amber Lin: okay, so this cycle, we’re mostly building these models. We’re not touching them. In fact, tables.
383 00:46:52.110 ⇒ 00:46:56.940 Uttam Kumaran: Yeah, probably the only one here is like, actually Kai. I think you can probably take the dim calendar.
384 00:46:57.380 ⇒ 00:46:58.090 Amber Lin: Hmm.
385 00:46:58.841 ⇒ 00:47:01.759 Uttam Kumaran: We have some code on how to build this somewhere.
386 00:47:02.740 ⇒ 00:47:03.350 Amber Lin: Hmm.
387 00:47:03.350 ⇒ 00:47:06.237 Uttam Kumaran: Like how to build a standard calendar
388 00:47:07.510 ⇒ 00:47:07.990 Demilade Agboola: Email.
389 00:47:07.990 ⇒ 00:47:08.309 Uttam Kumaran: Trust me!
390 00:47:08.460 ⇒ 00:47:14.540 Demilade Agboola: You might also want to sync with the team, and how they look at it. For instance, I know Emily.
391 00:47:14.590 ⇒ 00:47:15.290 Uttam Kumaran: Oh, yeah.
392 00:47:15.560 ⇒ 00:47:21.820 Demilade Agboola: In particular about how like, if things happen on Mondays, they attributed to the previous week, or something like that.
393 00:47:22.240 ⇒ 00:47:27.430 Demilade Agboola: so they, their their calendar might be slightly different.
394 00:47:27.540 ⇒ 00:47:29.750 Demilade Agboola: but it still won’t be that crazy.
395 00:47:30.650 ⇒ 00:47:32.380 Demilade Agboola: Well, it shouldn’t be that crazy.
396 00:47:33.230 ⇒ 00:47:33.930 Caio Velasco: Okay.
397 00:47:34.240 ⇒ 00:47:41.069 Caio Velasco: yeah, along with those that I marked, you guys. There’s also like a team products team customers. There are
398 00:47:41.240 ⇒ 00:47:48.635 Caio Velasco: some things that I did also make you can check. But the team calendar was the only one that was like. Should we do this? Well, now I know.
399 00:47:49.850 ⇒ 00:47:50.560 Amber Lin: No.
400 00:47:52.430 ⇒ 00:47:53.679 Uttam Kumaran: Cool, and then.
401 00:47:53.680 ⇒ 00:47:54.589 Amber Lin: Nothing else here.
402 00:47:54.590 ⇒ 00:48:02.100 Uttam Kumaran: Also dim customers. I think, Kai, you can take this one. This will basically be sourcing customers from
403 00:48:03.350 ⇒ 00:48:10.849 Uttam Kumaran: it’s ideally, we just want, like, literally a list of all the customers and all their core identifying information. We don’t.
404 00:48:11.660 ⇒ 00:48:16.879 Uttam Kumaran: It’s not necessary for us to have metrics here, but a couple of helpful metrics would be like
405 00:48:17.170 ⇒ 00:48:25.820 Uttam Kumaran: total spend last purchase date, you know, like that’s kind of like a nice to have.
406 00:48:25.980 ⇒ 00:48:33.540 Uttam Kumaran: But dim customers is what will power every customer. Id field we we use.
407 00:48:34.490 ⇒ 00:48:35.910 Uttam Kumaran: So this is a good one, too.
408 00:48:41.750 ⇒ 00:48:44.050 Uttam Kumaran: I don’t think they have this right.
409 00:48:46.010 ⇒ 00:48:47.060 Caio Velasco: No, I remember that when I.
410 00:48:47.060 ⇒ 00:48:50.070 Uttam Kumaran: It ends up, it just ends up in 50 places. I think.
411 00:48:50.350 ⇒ 00:49:01.440 Caio Velasco: Yeah, when I was talking with Emily about that one. She said, that it comes from Oms shopify and postgres. So I kind of pulled from all those 3. So I have, like a dim customer already.
412 00:49:01.800 ⇒ 00:49:02.480 Uttam Kumaran: Exactly.
413 00:49:02.480 ⇒ 00:49:04.819 Caio Velasco: Then I did like a mapping between them as well.
414 00:49:05.200 ⇒ 00:49:12.100 Uttam Kumaran: Yeah. So once that’s ready to review, we can take a look and see like, okay, do we want to dedupe and like, talk to about those questions.
415 00:49:12.350 ⇒ 00:49:16.410 Uttam Kumaran: So there’s 1 more above dim customers, so dim. Pro, can you open dim products?
416 00:49:22.670 ⇒ 00:49:27.000 Uttam Kumaran: Can we? You think you can handle this as well?
417 00:49:30.060 ⇒ 00:49:38.756 Caio Velasco: What I have here for that one is like skew name and images from 3 different
418 00:49:39.640 ⇒ 00:49:46.280 Caio Velasco: sources prod like line items, and the other line items, and also from transactions.
419 00:49:46.680 ⇒ 00:49:47.360 Caio Velasco: That’s what I had.
420 00:49:47.360 ⇒ 00:49:51.099 Uttam Kumaran: Yeah, like, I mean, probably my only
421 00:49:51.640 ⇒ 00:49:58.589 Uttam Kumaran: given how much they’re like changing prices and something I know it’s open. But maybe we should like.
422 00:49:59.000 ⇒ 00:50:04.590 Uttam Kumaran: have this be a slowly changing dimensions table with like
423 00:50:04.880 ⇒ 00:50:09.940 Uttam Kumaran: the prices, because, for example, they change the prices
424 00:50:10.330 ⇒ 00:50:18.600 Uttam Kumaran: and the cost of goods. I think on these pretty often. So it would be great to maybe make this an incremental scd table
425 00:50:18.780 ⇒ 00:50:21.050 Uttam Kumaran: so that we can track those changes.
426 00:50:22.970 ⇒ 00:50:25.210 Uttam Kumaran: I don’t know exactly where the
427 00:50:25.610 ⇒ 00:50:30.539 Uttam Kumaran: products are coming from now. But I pretty sure you can pull all of that from shopify.
428 00:50:32.310 ⇒ 00:50:33.310 Uttam Kumaran: Okay.
429 00:50:33.620 ⇒ 00:50:34.710 Caio Velasco: Makes sense.
430 00:50:34.830 ⇒ 00:50:39.069 Uttam Kumaran: But I don’t know what’s in netsuite, so I guess net oh, Netsuite will be the cost right.
431 00:50:39.510 ⇒ 00:50:40.860 Uttam Kumaran: The cost of goods.
432 00:50:44.990 ⇒ 00:50:47.430 Demilade Agboola: I’m not sure to be honest.
433 00:50:49.230 ⇒ 00:50:53.039 Uttam Kumaran: I think this is a great table, though, like, I think if we can start tracking
434 00:50:53.320 ⇒ 00:50:58.879 Uttam Kumaran: product changes over time, it’d be great. I mean couple of things that we want to have here is like
435 00:50:59.300 ⇒ 00:51:01.679 Uttam Kumaran: the name you make a description
436 00:51:02.110 ⇒ 00:51:07.600 Uttam Kumaran: image, URL. The only reason I’ll say image, URL, is because we can, we can actually use that in looker
437 00:51:07.750 ⇒ 00:51:10.580 Uttam Kumaran: in Looker, you can actually render images
438 00:51:10.750 ⇒ 00:51:13.409 Uttam Kumaran: if you pass the image. URL,
439 00:51:13.520 ⇒ 00:51:16.470 Uttam Kumaran: so it could be like a fun thing for us to build for them.
440 00:51:20.511 ⇒ 00:51:24.300 Uttam Kumaran: and then, yeah, I mainly want to see like the cost related. Stuff.
441 00:51:25.080 ⇒ 00:51:27.770 Uttam Kumaran: So like cost of goods.
442 00:51:31.210 ⇒ 00:51:37.330 Uttam Kumaran: And the I guess the product price in shopify
443 00:51:37.730 ⇒ 00:51:48.759 Uttam Kumaran: which typically this is where they’re they’re doing markdowns right. They’re changing the price. So yeah, that I think that’s probably enough, for now and then, again, this becomes our sort of source of truth across the board for product data.
444 00:51:50.180 ⇒ 00:52:00.500 Uttam Kumaran: This one will maybe tricky, though, because we have bundle products, individual products.
445 00:52:03.010 ⇒ 00:52:11.229 Uttam Kumaran: Right? So I’m not sure. But I’m sure Emily can help us when we get there. But one thing can we put? Yeah, can we put category? Can we just put it underneath as a sub thing?
446 00:52:11.700 ⇒ 00:52:16.669 Uttam Kumaran: Can we just put like bundles versus individual products versus free gifts.
447 00:52:17.560 ⇒ 00:52:21.070 Uttam Kumaran: So open, we have to figure out like whether they’re all gonna end up here or not.
448 00:52:24.880 ⇒ 00:52:29.920 Amber Lin: For cost? Do we need a base cost or just cost of the sold and product price?
449 00:52:32.083 ⇒ 00:52:34.150 Uttam Kumaran: Just product. Price is fine.
450 00:52:39.820 ⇒ 00:52:40.520 Amber Lin: Okay.
451 00:52:41.730 ⇒ 00:52:42.710 Amber Lin: Okay.
452 00:52:45.930 ⇒ 00:52:53.340 Amber Lin: One. Dial, 1, 2, 2, 1, okay.
453 00:52:53.820 ⇒ 00:52:55.100 Amber Lin: Anything else.
454 00:52:58.800 ⇒ 00:52:59.560 Uttam Kumaran: Insist.
455 00:52:59.560 ⇒ 00:53:05.440 Amber Lin: Subscriptions. I think we’re all let me scroll. Yeah, subscriptions I can take, and then scroll.
456 00:53:06.300 ⇒ 00:53:08.120 Uttam Kumaran: Down so.
457 00:53:14.330 ⇒ 00:53:15.990 Uttam Kumaran: Oh.
458 00:53:22.010 ⇒ 00:53:24.050 Uttam Kumaran: I think the monthly
459 00:53:24.580 ⇒ 00:53:30.870 Uttam Kumaran: and weekly revenue summaries you can assign Kyle for that, because that’ll be built on top of March.
460 00:53:32.350 ⇒ 00:53:33.040 Uttam Kumaran: Oh!
461 00:53:33.040 ⇒ 00:53:34.040 Amber Lin: In daily.
462 00:53:36.080 ⇒ 00:53:40.500 Uttam Kumaran: Yeah, I just don’t know whether we’re gonna do. Yeah, you could just let’s just assign all 3. It’s fine
463 00:53:50.750 ⇒ 00:53:55.850 Uttam Kumaran: But these, like we can do later, like we don’t have to do them. Now, yeah, these these are
464 00:53:56.170 ⇒ 00:54:00.160 Uttam Kumaran: some of these ones we’re not gonna get to, probably for another like 2 or 3 weeks.
465 00:54:00.710 ⇒ 00:54:01.065 Amber Lin: Hmm.
466 00:54:03.920 ⇒ 00:54:08.679 Uttam Kumaran: Okay, yeah. I mean, I know we have 5 min. So we can. Maybe we want to talk about the current cycle, or we can.
467 00:54:08.680 ⇒ 00:54:14.330 Amber Lin: Yeah, I wanna look at that. So I’m going to.
468 00:54:22.180 ⇒ 00:54:26.949 Uttam Kumaran: And then can we make sure that the local environment ticket you can assign to me.
469 00:54:27.440 ⇒ 00:54:30.830 Amber Lin: Hmm, actually, I’m gonna do it here.
470 00:54:33.053 ⇒ 00:54:35.260 Amber Lin: Local environment.
471 00:54:39.690 ⇒ 00:54:44.909 Amber Lin: And are we doing this this cycle tag models? By? And mark.
472 00:54:50.387 ⇒ 00:54:52.030 Uttam Kumaran: Not this cycle.
473 00:54:53.190 ⇒ 00:54:53.910 Amber Lin: Okay?
474 00:55:03.256 ⇒ 00:55:07.889 Amber Lin: Can I get some help on deadlines, at least on milestone 3.
475 00:55:08.130 ⇒ 00:55:10.429 Amber Lin: What’s for this week? What’s for next week?
476 00:55:13.970 ⇒ 00:55:17.539 Demilade Agboola: So I think 2, 8, 6, 2, 8, 5.
477 00:55:17.670 ⇒ 00:55:20.180 Demilade Agboola: We can try. And input this week.
478 00:55:22.290 ⇒ 00:55:24.490 Demilade Agboola: Today is Tuesday. Okay, this week. Yeah.
479 00:55:26.620 ⇒ 00:55:30.810 Demilade Agboola: And then that those ones will be more of next week.
480 00:55:32.450 ⇒ 00:55:36.979 Amber Lin: Okay for Otam. Which ones are you doing? First? st
481 00:55:37.270 ⇒ 00:55:39.729 Uttam Kumaran: I’d probably put Monday for me.
482 00:55:42.310 ⇒ 00:55:43.930 Uttam Kumaran: Yeah, just for all these 3.
483 00:55:46.950 ⇒ 00:55:48.080 Amber Lin: Next Monday.
484 00:55:48.720 ⇒ 00:55:49.450 Uttam Kumaran: Yeah.
485 00:55:49.870 ⇒ 00:55:51.420 Amber Lin: Okay? Sounds good.
486 00:55:52.173 ⇒ 00:55:56.050 Amber Lin: For Kyle Street tickets. How are we
487 00:55:56.190 ⇒ 00:55:58.959 Amber Lin: putting deadlines? What’s for this week?
488 00:56:01.011 ⇒ 00:56:12.289 Caio Velasco: Well, for products and customers already have something. But I have to check with Emily, because there is new things, especially about the scd thing.
489 00:56:14.210 ⇒ 00:56:16.672 Caio Velasco: I I would not say this weekend. Oh,
490 00:56:17.150 ⇒ 00:56:21.909 Caio Velasco: I mentioned I don’t know if you saw, but I’m I’m oh, Whoa! Whoa! Next week
491 00:56:22.280 ⇒ 00:56:23.329 Caio Velasco: for the whole week.
492 00:56:24.980 ⇒ 00:56:31.669 Caio Velasco: So I would have to work on this after. But I can. I can see what I can do this week, since I already have something for them
493 00:56:32.080 ⇒ 00:56:33.069 Caio Velasco: for those 3.
494 00:56:34.550 ⇒ 00:56:38.060 Uttam Kumaran: Yeah, I feel like, if the most important here are dim customers.
495 00:56:38.630 ⇒ 00:56:39.070 Amber Lin: And.
496 00:56:39.070 ⇒ 00:56:40.749 Uttam Kumaran: And then Jim Calendar should be
497 00:56:41.300 ⇒ 00:56:45.450 Uttam Kumaran: pretty easy to do. I think we already have that script somewhere.
498 00:56:45.790 ⇒ 00:56:48.050 Uttam Kumaran: If you ask in that data channel.
499 00:56:50.320 ⇒ 00:56:54.090 Uttam Kumaran: Basically this is just like creating a standard calendar. And then Emily.
500 00:56:54.090 ⇒ 00:56:54.719 Caio Velasco: Standard, yeah.
501 00:56:54.720 ⇒ 00:56:58.670 Uttam Kumaran: More on fiscal calendars. They can label, but.
502 00:56:59.470 ⇒ 00:57:00.090 Caio Velasco: Cool.
503 00:57:01.560 ⇒ 00:57:02.240 Amber Lin: Okay.
504 00:57:02.890 ⇒ 00:57:11.500 Amber Lin: I’ll prefer this week. We’ll see what we can get done. Let’s aim to get customers done, and then get the code for Dim Calendar.
505 00:57:11.510 ⇒ 00:57:12.430 Caio Velasco: Sure. Okay.
506 00:57:13.180 ⇒ 00:57:18.309 Amber Lin: Do. I also put this as end of the cycle fact subscriptions.
507 00:57:20.380 ⇒ 00:57:26.609 Uttam Kumaran: yeah, you can put it. This is gonna be, depend. This is gonna be blocked by loop like any of the subscriptions work.
508 00:57:26.790 ⇒ 00:57:29.760 Uttam Kumaran: It’s gonna be based on loop. So I don’t know.
509 00:57:30.260 ⇒ 00:57:35.049 Uttam Kumaran: I don’t think we’re gonna get loop until for next week. So.
510 00:57:35.050 ⇒ 00:57:36.550 Amber Lin: I see gotcha.
511 00:57:36.790 ⇒ 00:57:39.610 Uttam Kumaran: I mean I would have. I literally would have started last week, but.
512 00:57:40.134 ⇒ 00:57:44.520 Amber Lin: They’re just kind of like nervous about like random stuff. It’s kind of weird. I’m like.
513 00:57:44.710 ⇒ 00:57:48.539 Uttam Kumaran: Dude just like, have polytomic build this like, can we talk about something else?
514 00:57:50.090 ⇒ 00:57:52.180 Uttam Kumaran: I don’t know why they’re nervous about it like.
515 00:57:53.300 ⇒ 00:57:56.000 Amber Lin: They don’t know Polyton right? That well, I guess.
516 00:57:56.490 ⇒ 00:57:58.870 Uttam Kumaran: The other tools that you suck like
517 00:58:00.610 ⇒ 00:58:03.500 Uttam Kumaran: it’s like, why are they even considering that I don’t know. It’s like.
518 00:58:03.790 ⇒ 00:58:06.440 Uttam Kumaran: I just think that they tend to be like. Very like.
519 00:58:06.600 ⇒ 00:58:12.972 Uttam Kumaran: We need to be very buttoned up across the board. But then nothing is like done. Well, I’m like, what was the point.
520 00:58:14.490 ⇒ 00:58:19.969 Uttam Kumaran: Like you got a great deal on stitch, but now it sucks like. Was it worth it? I don’t know.
521 00:58:21.600 ⇒ 00:58:24.759 Amber Lin: Who’s validating hevo pipelines.
522 00:58:26.067 ⇒ 00:58:27.660 Uttam Kumaran: I can. I can take this one.
523 00:58:27.660 ⇒ 00:58:28.100 Amber Lin: Okay.
524 00:58:34.260 ⇒ 00:58:44.009 Caio Velasco: So question about those other 2, 2, 92 to 90. Is it just to check if they arrived in raw in redshift? Or is it to set up the connection.
525 00:58:45.770 ⇒ 00:58:50.789 Uttam Kumaran: It’s kind of both like I think they’ll they’ll send a note once they have it ready to test.
526 00:58:51.450 ⇒ 00:58:56.499 Uttam Kumaran: We can then create the connection, and then see if the data ends up there.
527 00:58:56.890 ⇒ 00:58:57.650 Caio Velasco: Okay.
528 00:59:03.510 ⇒ 00:59:07.210 Amber Lin: Okay, all right.
529 00:59:09.570 ⇒ 00:59:11.310 Amber Lin: Have a few things.
530 00:59:11.940 ⇒ 00:59:12.910 Amber Lin: It just.
531 00:59:13.090 ⇒ 00:59:14.759 Amber Lin: I think I have to hop
532 00:59:14.980 ⇒ 00:59:19.209 Amber Lin: to. Eden. I’ll clean this up. I think this is good.
533 00:59:19.450 ⇒ 00:59:21.499 Amber Lin: and we know what we need to do.
534 00:59:21.760 ⇒ 00:59:23.310 Amber Lin: And
535 00:59:24.150 ⇒ 00:59:32.620 Amber Lin: yeah, I think there’s a few things in inventory that I’ll check with you on that. See if we can close it. Okay.
536 00:59:34.480 ⇒ 00:59:39.799 Demilade Agboola: Yeah, there’s a little update on inventory, but I think the ticket. But I would.
537 00:59:40.595 ⇒ 00:59:41.120 Amber Lin: Okay.
538 00:59:42.600 ⇒ 00:59:43.680 Amber Lin: Sounds good.
539 00:59:45.480 ⇒ 00:59:46.200 Uttam Kumaran: Okay.
540 00:59:46.200 ⇒ 00:59:49.470 Amber Lin: Okay. Looking good. Thank you. Bye-bye.
541 00:59:49.470 ⇒ 00:59:50.579 Uttam Kumaran: Thank you. Bye.
542 00:59:51.170 ⇒ 00:59:51.760 Amber Lin: Bye.