Meeting Title: Analytics Engineering Daily Sync Date: 2025-02-20 Meeting participants: Luke Daque, Uttam Kumaran, Awaish Kumar, Caio Velasco
WEBVTT
1 00:02:44.580 ⇒ 00:02:45.330 Luke Daque: Hello!
2 00:03:00.310 ⇒ 00:03:01.030 Awaish Kumar: No.
3 00:03:02.770 ⇒ 00:03:03.660 Luke Daque: I wish.
4 00:03:05.340 ⇒ 00:03:06.489 Awaish Kumar: Hi! How are you?
5 00:03:06.490 ⇒ 00:03:08.710 Luke Daque: Going. I’m doing well. How are you.
6 00:03:10.056 ⇒ 00:03:11.370 Awaish Kumar: Nice, good.
7 00:03:27.310 ⇒ 00:03:28.970 Luke Daque: Hi, Kate Ku!
8 00:03:30.530 ⇒ 00:03:31.850 Luke Daque: How’s it going.
9 00:03:32.240 ⇒ 00:03:34.250 Caio Velasco: Everything good, everything good.
10 00:03:34.670 ⇒ 00:03:36.910 Caio Velasco: A nicer day here. Finally.
11 00:03:40.850 ⇒ 00:03:41.480 Luke Daque: Nice.
12 00:03:43.598 ⇒ 00:03:46.739 Caio Velasco: Are you in Pakistan, or somewhere else?
13 00:03:47.260 ⇒ 00:03:49.329 Awaish Kumar: Yeah, I’m in person right now.
14 00:03:49.720 ⇒ 00:03:51.020 Caio Velasco: Oh, cool, cool.
15 00:03:53.370 ⇒ 00:03:56.020 Caio Velasco: I had a very nice Pakistan friend in
16 00:03:56.490 ⇒ 00:04:03.220 Caio Velasco: in the Netherlands, like really nice. I even thought that he was Brazilian, because it was so similar. The thing you were talking about.
17 00:04:08.310 ⇒ 00:04:10.299 Awaish Kumar: Sorry I didn’t get you.
18 00:04:11.170 ⇒ 00:04:21.989 Caio Velasco: No, I just said that I had a friend from Pakistan when I was in the Netherlands, was a very, very, very nice person, was also mechanical engineer. By coincidence.
19 00:04:23.240 ⇒ 00:04:24.270 Awaish Kumar: Okay.
20 00:04:26.060 ⇒ 00:04:27.699 Caio Velasco: And what time is it? There now.
21 00:04:29.340 ⇒ 00:04:32.710 Awaish Kumar: It’s a 7 Pm.
22 00:04:33.430 ⇒ 00:04:36.060 Caio Velasco: Okay. Also, a bit later than here.
23 00:04:37.370 ⇒ 00:04:37.795 Awaish Kumar: Yeah.
24 00:04:44.480 ⇒ 00:04:47.340 Awaish Kumar: I have lived in Denmark for 3 years.
25 00:04:50.277 ⇒ 00:04:51.259 Caio Velasco: Lived in Denver.
26 00:04:52.640 ⇒ 00:04:53.370 Caio Velasco: Did you like it?
27 00:04:53.370 ⇒ 00:04:58.400 Awaish Kumar: Kind of I lived in Copenhagen, and it was wonderful experience.
28 00:05:00.700 ⇒ 00:05:01.590 Awaish Kumar: Okay.
29 00:05:01.590 ⇒ 00:05:02.310 Caio Velasco: It is.
30 00:05:03.830 ⇒ 00:05:07.010 Caio Velasco: It was nice. Did you like it? It’s very cold. There.
31 00:05:07.800 ⇒ 00:05:10.209 Awaish Kumar: It. It was wonderful, like
32 00:05:10.400 ⇒ 00:05:18.120 Awaish Kumar: I lived in Canada. After that I visited few other countries in Europe as well by the Denmark.
33 00:05:18.260 ⇒ 00:05:29.040 Awaish Kumar: The quality of life in Denmark is like superior than anywhere, as like online
34 00:05:29.300 ⇒ 00:05:32.769 Awaish Kumar: in nearby urban countries, or even in Canada.
35 00:05:33.860 ⇒ 00:05:41.829 Caio Velasco: Yes, I’ve heard I’ve heard about it. It’s a bit similar to the Netherlands, I think. Especially, for like mobility transportation.
36 00:05:42.140 ⇒ 00:05:51.770 Caio Velasco: it’s it’s truly something different, like, we definitely don’t have that in Brazil. But yeah, I have to still go to Denmark. I’ve never been.
37 00:05:57.910 ⇒ 00:05:59.130 Uttam Kumaran: Hey? Guys, good morning.
38 00:06:00.300 ⇒ 00:06:01.260 Awaish Kumar: Room, one.
39 00:06:01.260 ⇒ 00:06:01.810 Luke Daque: Hey? What’s up?
40 00:06:02.290 ⇒ 00:06:02.790 Uttam Kumaran: Hey?
41 00:06:03.280 ⇒ 00:06:04.220 Uttam Kumaran: How’s everything?
42 00:06:07.780 ⇒ 00:06:08.569 Uttam Kumaran: How’s the day going.
43 00:06:08.570 ⇒ 00:06:09.290 Caio Velasco: I’m good.
44 00:06:10.110 ⇒ 00:06:11.050 Luke Daque: Doing well.
45 00:06:11.680 ⇒ 00:06:12.890 Caio Velasco: Good! How are you?
46 00:06:13.850 ⇒ 00:06:16.490 Uttam Kumaran: I’m good just a lot of work
47 00:06:16.920 ⇒ 00:06:25.169 Uttam Kumaran: yesterday that we tried to push through for Eden and then I got some stuff for Javi out. I also got out like code owners and a couple of things.
48 00:06:25.290 ⇒ 00:06:27.240 Uttam Kumaran: and then worked on.
49 00:06:27.510 ⇒ 00:06:34.800 Uttam Kumaran: worked on some of that documentation work that you know that I messaged about yesterday. But I think you know, that’ll continue to evolve. But
50 00:06:36.500 ⇒ 00:06:42.040 Uttam Kumaran: yeah, I guess sort of like free agenda today. Anything in particular
51 00:06:42.520 ⇒ 00:06:44.949 Uttam Kumaran: anyone want to talk about or need help on.
52 00:06:52.106 ⇒ 00:06:52.880 Uttam Kumaran: I mean.
53 00:06:52.880 ⇒ 00:06:59.097 Uttam Kumaran: there’s nothing I have a hundred things I want to talk about, and I’m sure if someone needs help on something. So.
54 00:07:00.010 ⇒ 00:07:07.079 Caio Velasco: Yeah, no, on my, on my, on my side. I’ll as I mentioned, I’ll try to get this gorgeous brand
55 00:07:07.810 ⇒ 00:07:13.210 Caio Velasco: gorgeous. I always forgot the name. Yeah, gorgeous dashboard ticket and see if I can.
56 00:07:13.796 ⇒ 00:07:20.460 Caio Velasco: Input stuff into the data, flow flow page. And then, by consequence, in the metric spreadsheet.
57 00:07:20.690 ⇒ 00:07:23.830 Caio Velasco: And then I think there’s a structure will help me also
58 00:07:24.140 ⇒ 00:07:26.859 Caio Velasco: settle and and understand what is happening.
59 00:07:27.621 ⇒ 00:07:33.119 Caio Velasco: So for now, I think I’m okay. But I’ll definitely have questions along the way, and then I’ll I’ll message people.
60 00:07:35.530 ⇒ 00:07:41.910 Uttam Kumaran: Okay? Great, yeah. And I and I messaged as well. Like, if you, if you need more hours and you’re working on like process stuff, feel free.
61 00:07:42.324 ⇒ 00:07:59.065 Uttam Kumaran: To do that. I don’t want to build that to the client, but we can absorb that internally. And then, yeah, I’m gonna keep taking stuff from Javi just to keep things moving forward. But sort of let me know how you feel. Probably we can catch up again probably sometime next weekend.
62 00:08:00.010 ⇒ 00:08:09.979 Uttam Kumaran: yeah, I’m sort of. I’m sort of fielding any like urgent questions there. Both of the analysts we have are part time, which kind of makes things rough. So I’m sort of picking up things as they fall. But
63 00:08:10.555 ⇒ 00:08:13.240 Uttam Kumaran: yeah, I would love to hand that off.
64 00:08:14.690 ⇒ 00:08:19.919 Caio Velasco: Yeah, yeah, sure. Sure. No, I totally understand. And that’s why I wanted to try to do this from scratch, so that I
65 00:08:20.400 ⇒ 00:08:28.349 Caio Velasco: and like end to end. And then, if I do understand, then I think I will definitely be able to say thing over, and that’s my expectations.
66 00:08:28.570 ⇒ 00:08:46.349 Uttam Kumaran: Perfect. Yeah, and don’t worry. If I keep tagging you, I just want you to see. I’ll try to document my process for everything. I’m I’m sort of moving across like every client right now, so I’m just picking up things as they sort of drop. But I’ll just keep tagging you just so you can see changes I’m making and sort of be aware of
67 00:08:46.910 ⇒ 00:08:51.170 Uttam Kumaran: sort of how things are going. Most of the questions that come in from the team are
68 00:08:51.330 ⇒ 00:09:04.747 Uttam Kumaran: like, they’re either questions about data accuracy. They’re questions about availability or like new metric questions. So I think we’ll we’ll improve our process of how do we categorize and like slas and things like that?
69 00:09:05.300 ⇒ 00:09:07.770 Uttam Kumaran: But, as I mentioned, like, we just have one.
70 00:09:07.870 ⇒ 00:09:16.529 Uttam Kumaran: We have 2 analysts there, but I would love to sort of. I don’t think the work overall is actually that complicated
71 00:09:16.650 ⇒ 00:09:25.049 Uttam Kumaran: we just are. We actually are probably slow, mainly because we have like these handoffs between ae and analysts. They sort of work
72 00:09:25.190 ⇒ 00:09:29.429 Uttam Kumaran: evening. And then it’s like, there’s like time in between.
73 00:09:29.540 ⇒ 00:09:46.879 Uttam Kumaran: And so I do think that probably as you start to see the whole picture, I’m sure there’s pieces that you could just take, because then I would love to just like what I would just love to give you that time if you can just handle everything. And I do think that’ll streamline stuff for the client, too, because they’re waiting a few days sometimes, for
74 00:09:47.270 ⇒ 00:09:52.310 Uttam Kumaran: like super easy stuff. You know.
75 00:09:52.530 ⇒ 00:09:53.080 Awaish Kumar: You know.
76 00:09:53.080 ⇒ 00:09:54.409 Caio Velasco: No perfect, perfect.
77 00:09:54.680 ⇒ 00:09:57.840 Uttam Kumaran: Cool, awesome.
78 00:10:02.660 ⇒ 00:10:09.119 Uttam Kumaran: Great anyone else a wish. I left some comments on the the sales. Mark Pr.
79 00:10:13.433 ⇒ 00:10:19.280 Awaish Kumar: Yeah, I I have updated that I found
80 00:10:20.450 ⇒ 00:10:22.760 Awaish Kumar: push the changes in the Pra.
81 00:10:24.000 ⇒ 00:10:25.710 Uttam Kumaran: Okay. So I can take a look at that.
82 00:10:26.410 ⇒ 00:10:27.080 Awaish Kumar: Yeah.
83 00:10:28.420 ⇒ 00:10:28.910 Awaish Kumar: Good.
84 00:10:30.720 ⇒ 00:10:36.689 Awaish Kumar: Yeah. Like, overall like, what do you think of the the
85 00:10:37.010 ⇒ 00:10:40.459 Awaish Kumar: segmentation of different dimension in the fact? They will.
86 00:10:43.000 ⇒ 00:10:46.220 Uttam Kumaran: I think it’s good. I mean, I think that’s perfect. I don’t know.
87 00:10:46.740 ⇒ 00:10:54.639 Uttam Kumaran: I think if as long as everybody in the team is good. I mean, we I would love for us to start doing dim fact, summary tables, basically.
88 00:10:55.119 ⇒ 00:11:05.009 Uttam Kumaran: I don’t know. Like Hi, I guess I’ll ask you like. Do you have any strong opinions on, like naming conventions, or like doing things like just star schema, where we have.
89 00:11:05.290 ⇒ 00:11:10.850 Uttam Kumaran: we have dim tables, we have fact tables, and then we just have, like summary or or ag tables.
90 00:11:12.750 ⇒ 00:11:15.730 Uttam Kumaran: I feel like that covers most of the stuff.
91 00:11:17.350 ⇒ 00:11:21.942 Caio Velasco: Yup, yeah, no, I think the way you guys are doing for me seems totally fine.
92 00:11:22.230 ⇒ 00:11:22.840 Uttam Kumaran: Okay.
93 00:11:22.840 ⇒ 00:11:26.350 Caio Velasco: Yeah, we can definitely start from there. And then if we see something else, we can.
94 00:11:27.030 ⇒ 00:11:28.800 Caio Velasco: Okay, that’s something. Yeah.
95 00:11:29.420 ⇒ 00:11:36.170 Uttam Kumaran: Yeah, I think the only thing away is I’m still. I’m still sort of handling similar to Javi. I’m handling, like all of the
96 00:11:36.640 ⇒ 00:11:41.209 Uttam Kumaran: like. If you look at the Channel from yesterday, I’m handling like all these small small questions
97 00:11:41.640 ⇒ 00:11:51.349 Uttam Kumaran: I have like no time. It’s getting extremely hard. So I just want to know that I can pass off some of those to you. To take on.
98 00:11:51.460 ⇒ 00:11:57.263 Uttam Kumaran: because, yeah, I can’t spend like 4 or 5 h on Eden every day.
99 00:11:58.440 ⇒ 00:12:06.630 Uttam Kumaran: so I don’t know. Are you looking at the Channel and sort of seeing those questions come in? I would love to just tag you, but I think also I’m not exactly sure
100 00:12:07.080 ⇒ 00:12:12.310 Uttam Kumaran: sometimes what hours you’re working. So if it’s urgent, I don’t know whether I can tag you in.
101 00:12:13.270 ⇒ 00:12:32.370 Awaish Kumar: Yeah, like I, I mentioned the hours I’m working on. So between 9 to 2 2 pm, like, I’m available on slack and not. Yeah, I reply, if it’s in these, and but if it’s after that I like have to like I look at in the next day, so.
102 00:12:33.630 ⇒ 00:12:36.880 Uttam Kumaran: And is that 9 to 2? Us. Time.
103 00:12:36.880 ⇒ 00:12:38.000 Awaish Kumar: He is. Yeah.
104 00:12:38.000 ⇒ 00:12:47.008 Uttam Kumaran: Okay, east coast. Okay, okay. I mean, did you? Okay? So then, I think, even, for between now and then, like, were you able to check out the conversations that me and
105 00:12:47.790 ⇒ 00:12:52.469 Uttam Kumaran: me and Robert were having in slack about like the Ltv. Work.
106 00:12:53.710 ⇒ 00:12:57.734 Awaish Kumar: Yeah, I have read them. But like, there’s a lot of different
107 00:12:58.390 ⇒ 00:13:01.590 Awaish Kumar: like, it’s, it’s a lot of different messages and threads.
108 00:13:01.710 ⇒ 00:13:05.109 Awaish Kumar: So it’s hard to like grasp
109 00:13:06.190 ⇒ 00:13:11.900 Awaish Kumar: what was the final outcome. But, like I’ve read it the 1st part.
110 00:13:12.490 ⇒ 00:13:12.850 Uttam Kumaran: Okay.
111 00:13:12.850 ⇒ 00:13:19.299 Awaish Kumar: Exactly which you have been doing, you ran. But yeah, I
112 00:13:20.890 ⇒ 00:13:25.580 Awaish Kumar: I didn’t fully, completely grasp the calculate calculations, and I I don’t know
113 00:13:26.338 ⇒ 00:13:30.250 Awaish Kumar: you mentioned some projected Ltv. And some other.
114 00:13:30.250 ⇒ 00:13:30.740 Uttam Kumaran: Yeah.
115 00:13:31.600 ⇒ 00:13:32.110 Awaish Kumar: No.
116 00:13:32.110 ⇒ 00:13:42.410 Uttam Kumaran: Yeah, maybe I can. Maybe I can send a message on it, but I don’t. I’m sort of in meetings for the next few hours. So if you have time to take on this Pr. That Robert needs, that would be
117 00:13:42.630 ⇒ 00:13:53.089 Uttam Kumaran: really helpful. Basically, they want to calculate Ltv. But like not not? Predicted Ltv, like, actually, the lifetime value of every single customer. Which is.
118 00:13:53.230 ⇒ 00:14:05.000 Uttam Kumaran: it’s basically just their total revenue that they spend right with the with the company and the way they want to do that is 3 ways they 1st want to look at Ltv. For for every customer
119 00:14:05.620 ⇒ 00:14:08.370 Uttam Kumaran: hooked onto the month they started.
120 00:14:08.540 ⇒ 00:14:13.470 Uttam Kumaran: but also all the revenue they spent with Eden. The second piece is, they want to look at
121 00:14:13.980 ⇒ 00:14:21.339 Uttam Kumaran: and attributed to any product that they bought. The second piece they want to look at is attributed just to one product, but all the revenue
122 00:14:23.210 ⇒ 00:14:25.250 Uttam Kumaran: like all of the revenue that they’ve
123 00:14:25.510 ⇒ 00:14:33.140 Uttam Kumaran: they’ve used, they’ve all the revenue they spent with the with the client. And the 3rd thing, they just want to look at 1st product and the revenue associated with the 1st product.
124 00:14:33.680 ⇒ 00:14:42.890 Uttam Kumaran: So 3 different types of like product. 1st product. Ltv, 1st product, total Ltv and all products total. Ltv.
125 00:14:45.350 ⇒ 00:14:51.370 Awaish Kumar: Like for like we, how do we want to calculate it? For, like every customer.
126 00:14:52.090 ⇒ 00:14:57.599 Uttam Kumaran: And then the the. So it’s like a, it’s a monthly thing. So basically, we hook onto the 1st month
127 00:14:58.130 ⇒ 00:14:59.810 Uttam Kumaran: that they make a purchase.
128 00:15:02.760 ⇒ 00:15:03.395 Awaish Kumar: Okay.
129 00:15:05.330 ⇒ 00:15:09.450 Uttam Kumaran: And if you look the monthly Ltv. Cohorts table, you’ll see I already did.
130 00:15:09.730 ⇒ 00:15:17.439 Uttam Kumaran: I already did basically like looking at all their products and all the revenue.
131 00:15:17.830 ⇒ 00:15:20.189 Uttam Kumaran: and then you tie that back to the 1st month.
132 00:15:20.300 ⇒ 00:15:25.009 Uttam Kumaran: I have a Pr. That I can that I can push. It just needs validation
133 00:15:25.200 ⇒ 00:15:26.959 Uttam Kumaran: for the other 2 categories.
134 00:15:30.200 ⇒ 00:15:39.650 Awaish Kumar: But like what do you mean by 1st month, like the person who like month of the 1st purchase up from a customer? Or
135 00:15:39.790 ⇒ 00:15:40.809 Awaish Kumar: what is the 1st one?
136 00:15:40.810 ⇒ 00:15:53.229 Uttam Kumaran: Exactly. Yeah. So the first.st So the 1st purchase by every customer. So it’s basically monthly cohorting, like we want to look at every single month, all of the customers in that month that made their 1st purchase.
137 00:15:53.440 ⇒ 00:15:57.939 Uttam Kumaran: And then we want to look at. We want to look at all of the subsequent revenue.
138 00:15:58.510 ⇒ 00:16:01.309 Uttam Kumaran: but it’s all but the date spine is that month.
139 00:16:02.980 ⇒ 00:16:08.040 Awaish Kumar: Yeah, I I just want to understand that. But if, for example, if we take a month February
140 00:16:08.170 ⇒ 00:16:19.069 Awaish Kumar: and and the there are 10 customers who made their 1st purchase in February. So then, we only take these 10 customers, or are we looking to take all the customers who made the
141 00:16:19.210 ⇒ 00:16:20.550 Awaish Kumar: even if you’re thinking.
142 00:16:20.550 ⇒ 00:16:21.460 Uttam Kumaran: Purchase.
143 00:16:22.530 ⇒ 00:16:24.799 Awaish Kumar: Okay, the 10 customers whose
144 00:16:24.950 ⇒ 00:16:31.179 Awaish Kumar: and they made their 1st order in this month, then only these 10 customers are part of this
145 00:16:31.400 ⇒ 00:16:33.270 Awaish Kumar: Ltv calculation, right?
146 00:16:33.270 ⇒ 00:16:38.410 Uttam Kumaran: Yes, but then you take all of the revenue that they’ve spent beyond that month.
147 00:16:40.130 ⇒ 00:16:45.119 Awaish Kumar: So not just the revenues they spent in that month, but the revenue they spent in all subsequent months.
148 00:16:45.280 ⇒ 00:16:48.319 Uttam Kumaran: So you’re basically looking at the value of that customer
149 00:16:48.570 ⇒ 00:17:01.899 Uttam Kumaran: hooking it onto the 1st month. And the goal for the business is they want to look at that their customers have higher Ltv. Over time, meaning that they’re spending more with the company that they’re staying longer. They’re making all their payments.
150 00:17:02.240 ⇒ 00:17:06.349 Uttam Kumaran: That’s the goal for the, for, the, for, the, for the for Eden.
151 00:17:07.510 ⇒ 00:17:15.880 Awaish Kumar: Okay. So what I understand is that we are looking to find the customers who made their 1st orders in in a specific month.
152 00:17:16.050 ⇒ 00:17:22.230 Awaish Kumar: and then for those customers get all the they’ll get. The total revenue they embed
153 00:17:22.430 ⇒ 00:17:24.590 Awaish Kumar: go from the admin right.
154 00:17:24.940 ⇒ 00:17:25.720 Uttam Kumaran: Yes.
155 00:17:26.790 ⇒ 00:17:29.860 Awaish Kumar: Okay, this is one of the calculation for Mtv.
156 00:17:30.490 ⇒ 00:17:38.930 Uttam Kumaran: Yes, so the other 2 calculations are, gonna be we want to just look at the revenue associated with their 1st order.
157 00:17:39.320 ⇒ 00:17:43.479 Uttam Kumaran: So not any revenue associated with other products they may have bought after
158 00:17:45.040 ⇒ 00:17:54.359 Uttam Kumaran: the second thing we want to do is for the 1st thing I mentioned. We’re doing a product list ag, where I have a list ag of all of the products they bought.
159 00:17:54.670 ⇒ 00:18:00.539 Uttam Kumaran: The last piece they want to do is they just want to have the 1st product they bought as a as a dimension.
160 00:18:02.200 ⇒ 00:18:11.664 Uttam Kumaran: So I think I have a Pr for that. I just haven’t tested. I did it like late last night, and I’ll send it to you, and then maybe you can take a look and validate it.
161 00:18:12.310 ⇒ 00:18:13.969 Uttam Kumaran: I think I got it. I just
162 00:18:14.220 ⇒ 00:18:21.720 Uttam Kumaran: I was like running out of energy. I couldn’t figure I couldn’t like just read the sequel anymore. So I’ll just send you the Pr. And you can take a look.
163 00:18:23.770 ⇒ 00:18:25.539 Awaish Kumar: Yeah. Okay. Sure.
164 00:18:25.850 ⇒ 00:18:27.090 Uttam Kumaran: Okay, okay, great
165 00:18:32.300 ⇒ 00:18:40.789 Uttam Kumaran: cool. And then, yeah, Ryan, anything else on like stack with side. Let me know.
166 00:18:41.200 ⇒ 00:18:46.759 Luke Daque: Yeah, I think I’m good. So far, I’m just yeah. I just pushed some changes to the Pr.
167 00:18:47.199 ⇒ 00:18:55.299 Luke Daque: I’ll merge that. And maybe today, if you if you want, you won’t be able to review it, I’ll just probably merge it. That’s just the events. Pr.
168 00:18:55.530 ⇒ 00:18:58.269 Luke Daque: and then I’ll create a different one for
169 00:18:59.650 ⇒ 00:19:01.880 Luke Daque: yeah, the the updates to the rest of the.
170 00:19:02.320 ⇒ 00:19:07.469 Uttam Kumaran: Can you? Yeah. Can you tag me in the Pr Channel? I I thought I should be getting
171 00:19:07.961 ⇒ 00:19:16.389 Uttam Kumaran: notifications, but I guess I’m not from the Pr Reviews Channel. Can you just tag me in that pr like in that in the slack channel? I’ll I’ll go review it.
172 00:19:16.720 ⇒ 00:19:17.360 Luke Daque: Cool.
173 00:19:18.270 ⇒ 00:19:19.219 Uttam Kumaran: Okay, cool.
174 00:19:19.350 ⇒ 00:19:23.979 Uttam Kumaran: And then, yeah, the only other things on the infra side. So I added code owners to
175 00:19:24.260 ⇒ 00:19:32.319 Uttam Kumaran: as many repos as I could. Which is basically this group. I think if there’s anything on the data engineering side, I’m I’ll take it on, which is like
176 00:19:32.620 ⇒ 00:19:40.330 Uttam Kumaran: anything related to pipelines or stuff like that. I can review otherwise anything the Dbc project folders this crew will.
177 00:19:40.630 ⇒ 00:19:43.785 Uttam Kumaran: We’ll sort of review any of those items.
178 00:19:44.320 ⇒ 00:19:51.669 Uttam Kumaran: right now. I just have a wish, you and Kyle on Javi that way. It gives some redundancy like in case
179 00:19:53.050 ⇒ 00:20:00.940 Uttam Kumaran: someone’s out. And then also, I’m sort of a reviewer on everything ideally. Again, we’ll try to create some redundancy across clients
180 00:20:01.050 ⇒ 00:20:04.909 Uttam Kumaran: so that you’re not like people aren’t reviewing their own Prs.
181 00:20:06.310 ⇒ 00:20:11.079 Uttam Kumaran: and then we’ll also work on. I think beyond this we’ll work on pr descriptions and things like that.
182 00:20:12.600 ⇒ 00:20:15.870 Uttam Kumaran: Which I think is fine, for now, as long as we’re just getting everything out.
183 00:20:17.660 ⇒ 00:20:21.019 Uttam Kumaran: Yeah. And the other thing is, I may switch us over to linear.
184 00:20:21.720 ⇒ 00:20:25.830 Uttam Kumaran: Does anyone have any opinions on linear.
185 00:20:27.710 ⇒ 00:20:32.419 Luke Daque: I haven’t tested it. Tried it yet, but I I heard like good stuff about it.
186 00:20:32.740 ⇒ 00:20:35.210 Luke Daque: like I’ve read good stuff about it.
187 00:20:37.640 ⇒ 00:20:40.539 Caio Velasco: I don’t. I never worked with it. To be honest.
188 00:20:40.950 ⇒ 00:20:44.890 Uttam Kumaran: It’s sort of like the it’s sort of like Jira.
189 00:20:45.100 ⇒ 00:20:47.020 Uttam Kumaran: but it’s like a little bit better.
190 00:20:48.050 ⇒ 00:20:49.330 Caio Velasco: Linear.
191 00:20:49.800 ⇒ 00:20:51.969 Uttam Kumaran: Linear. LINE. A, R.
192 00:21:00.490 ⇒ 00:21:07.270 Uttam Kumaran: It’s it’s just task. It’s just task tracking. But I don’t know I’m I’m trying. I’m I’m gonna test it out probably later this month.
193 00:21:07.630 ⇒ 00:21:11.980 Uttam Kumaran: So we can consider moving from notion for tasks.
194 00:21:12.220 ⇒ 00:21:14.570 Uttam Kumaran: This notion is just a bit annoying right now.
195 00:21:16.860 ⇒ 00:21:18.850 Uttam Kumaran: But I’m going to test it out and see.
196 00:21:19.020 ⇒ 00:21:20.640 Uttam Kumaran: Maybe just with one client.
197 00:21:28.170 ⇒ 00:21:33.929 Uttam Kumaran: Okay, cool? Yeah. That’s sort of all I had anything else. We have 10 more minutes.
198 00:21:37.220 ⇒ 00:21:40.039 Caio Velasco: On my side, working on gorgeous, now.
199 00:21:40.590 ⇒ 00:21:41.180 Uttam Kumaran: Okay.
200 00:21:42.750 ⇒ 00:21:47.490 Uttam Kumaran: Okay, cool guys. Well, I’ll just message in slack. Just message me if you need anything.
201 00:21:48.120 ⇒ 00:21:49.849 Caio Velasco: Perfect. Thank you.
202 00:21:49.970 ⇒ 00:21:50.510 Uttam Kumaran: Thank you.
203 00:21:50.510 ⇒ 00:21:50.840 Uttam Kumaran: You.
204 00:21:50.840 ⇒ 00:21:51.800 Luke Daque: Thanks guys.
205 00:21:52.010 ⇒ 00:21:52.760 Uttam Kumaran: Bye.