Meeting Title: Analytics Engineering Daily Sync Date: 2025-02-21 Meeting participants: Luke Daque, Uttam Kumaran, Awaish Kumar, Caio Velasco


WEBVTT

1 00:01:28.340 00:01:30.020 Caio Velasco: Hey? Rich! It’s great!

2 00:01:32.340 00:01:34.180 Awaish Kumar: Hi! It’s good. How about you?

3 00:01:34.870 00:01:37.260 Caio Velasco: Good! Good, oh, good.

4 00:02:47.600 00:02:48.430 Uttam Kumaran: Hey, guys?

5 00:02:48.900 00:02:50.150 Uttam Kumaran: Sorry for the delay.

6 00:02:52.180 00:02:53.800 Caio Velasco: Hey, you, Tom? I’m good.

7 00:02:54.210 00:02:55.590 Uttam Kumaran: Hey! How are you?

8 00:02:55.840 00:02:56.370 Uttam Kumaran: Good!

9 00:02:56.370 00:02:56.655 Caio Velasco: Sure.

10 00:03:02.196 00:03:04.689 Uttam Kumaran: I don’t know if Luke is coming.

11 00:03:09.030 00:03:10.010 Uttam Kumaran: Message him.

12 00:03:16.700 00:03:17.550 Caio Velasco: Beautiful.

13 00:03:17.996 00:03:18.890 Uttam Kumaran: Okay. Cool.

14 00:03:19.250 00:03:19.970 Luke Daque: Hello!

15 00:03:20.890 00:03:21.289 Uttam Kumaran: Okay, so.

16 00:03:22.730 00:03:23.760 Luke Daque: Don’t worry.

17 00:03:25.580 00:03:26.520 Uttam Kumaran: Cool. How’s

18 00:03:27.420 00:03:34.240 Uttam Kumaran: Alright! 1st Friday, Kyle, so good week. We had a kind of a busy week across

19 00:03:34.740 00:03:37.679 Uttam Kumaran: the board, but really happy to see

20 00:03:38.877 00:03:42.649 Uttam Kumaran: you know, Staff Blitz and Javi started to get better.

21 00:03:43.205 00:03:47.560 Uttam Kumaran: Still, Eden, the client that I’m working on with oasis

22 00:03:47.950 00:03:49.669 Uttam Kumaran: still a little bit of a

23 00:03:49.990 00:03:55.290 Uttam Kumaran: problem. They just have a lot of stuff there. They’re trying to do.

24 00:03:55.410 00:03:59.922 Uttam Kumaran: So we’re trying to play catch up. And they’re a little bit demanding

25 00:04:01.730 00:04:04.096 Uttam Kumaran: but overall I feel pretty

26 00:04:04.790 00:04:08.210 Uttam Kumaran: I’m feeling pretty good. I think it’ll probably take another

27 00:04:08.890 00:04:11.189 Uttam Kumaran: week or 2 for both of those clients.

28 00:04:12.104 00:04:19.175 Uttam Kumaran: To sort of build out the march. But overall, I think, feeling better. We have one more client that also started this week, that

29 00:04:20.350 00:04:25.242 Uttam Kumaran: we’re doing basically like a month long audit and they’re

30 00:04:26.200 00:04:28.479 Uttam Kumaran: They’re gonna be a huge client.

31 00:04:29.230 00:04:31.929 Uttam Kumaran: they have a lot of stuff that’s broken.

32 00:04:33.830 00:04:36.979 Uttam Kumaran: And I’ll talk a little bit about it in the team meeting later.

33 00:04:38.380 00:04:41.560 Uttam Kumaran: But I’ll probably need help from somebody on that

34 00:04:43.350 00:04:50.040 Uttam Kumaran: And then, yeah, I think that’s probably most of the updates. I know we didn’t have any time, really, this week on a lot of like tech that stuff. But

35 00:04:50.290 00:04:56.610 Uttam Kumaran: we we did some really good work on documentation. And you know how to improve that process so

36 00:04:56.790 00:04:58.897 Uttam Kumaran: definitely some improvements?

37 00:04:59.830 00:05:06.680 Uttam Kumaran: so yeah, maybe I’ll pass it off. Anyone wants to give updates or anything we wanna chat about here.

38 00:05:08.750 00:05:11.680 Caio Velasco: So on my end. I’ve been working on the gorgeous

39 00:05:12.320 00:05:21.789 Caio Velasco: dashboard dashboard ticket, and I also wanna show something to to Nicholas, because he told me that he would need more inputs to understand like, what

40 00:05:22.340 00:05:24.529 Caio Velasco: do we need to ask the client

41 00:05:25.316 00:05:38.129 Caio Velasco: to get more details and stuff? So then I started. I started building some things I can. I can show it here now, or or just leave for the stand up. It’s more like up to you. If anyone has any other things that are priority.

42 00:05:38.400 00:05:39.620 Caio Velasco: it’s also fine.

43 00:05:40.460 00:05:45.199 Uttam Kumaran: Yeah, I guess maybe I could ask Luke, or wish there’s anything.

44 00:05:45.340 00:05:46.490 Uttam Kumaran: Yeah.

45 00:05:49.356 00:05:57.499 Awaish Kumar: No, actually I for the sales. MoD I I replied to your comments.

46 00:05:57.610 00:05:58.280 Uttam Kumaran: Okay.

47 00:05:58.832 00:06:04.417 Awaish Kumar: Like. I have merged the Pr. And on the slack you mentioned a few things

48 00:06:05.570 00:06:07.959 Awaish Kumar: and those were like.

49 00:06:08.817 00:06:14.639 Awaish Kumar: I I commented on that that, for example, some of the code

50 00:06:14.960 00:06:19.279 Awaish Kumar: which which you maybe saw that it’s it’s not in our

51 00:06:19.430 00:06:24.715 Awaish Kumar: new MoD. It’s because maybe it was duplicated or unused, and

52 00:06:25.664 00:06:26.120 Uttam Kumaran: Okay.

53 00:06:26.120 00:06:40.459 Awaish Kumar: Yeah, so and this, yeah, a payment dimension was not there, because it’s it’s like, we only had one or 2 fields were being used, so it didn’t add any other payment. Related information. So I just

54 00:06:41.351 00:06:44.369 Awaish Kumar: included those information. The transaction table itself.

55 00:06:45.025 00:06:50.360 Awaish Kumar: So that is merged and the for Ltv calculations. I think

56 00:06:52.400 00:06:59.749 Awaish Kumar: like I I got a positive response from Bo yoon, so we will see if they come up with anything else.

57 00:07:03.080 00:07:06.610 Awaish Kumar: And yes, so I will be working on marketing mark

58 00:07:07.350 00:07:13.360 Awaish Kumar: today. If there is nothing no ad hoc requests, then I will start working on marketing.

59 00:07:14.670 00:07:21.890 Uttam Kumaran: Okay, yeah, let’s let’s work on marketing. I think I’m gonna schedule a meeting for Monday to do a review with the analyst team.

60 00:07:22.617 00:07:25.889 Uttam Kumaran: Of of our progress on the marts.

61 00:07:26.380 00:07:33.509 Uttam Kumaran: I think today they have a presentation. So they’re not gonna have time to to probably meet with us. But I’ll grab time on

62 00:07:35.450 00:07:37.010 Uttam Kumaran: on Monday to do that

63 00:07:38.475 00:07:44.350 Uttam Kumaran: and then we can review basically our progress on the sales mart and marketing mart with them.

64 00:07:45.042 00:07:48.757 Uttam Kumaran: They’ll give some more specifics on what other tables?

65 00:07:49.280 00:07:52.450 Uttam Kumaran: But I think we’ve made good enough progress to then start to get some feedback, so.

66 00:07:53.500 00:07:54.780 Awaish Kumar: Yeah, sure.

67 00:07:56.200 00:07:57.460 Uttam Kumaran: Okay, cool.

68 00:07:57.966 00:08:03.619 Uttam Kumaran: Brandon, Luke. Any updates on stock with stuff? I left some comments on the Pr.

69 00:08:03.890 00:08:10.820 Luke Daque: Yeah, so yeah, I’m I’m working on those. So basically trying to consolidate all the events into just one

70 00:08:10.970 00:08:14.110 Luke Daque: single event back model.

71 00:08:14.440 00:08:19.180 Luke Daque: And then, yeah, also the the the

72 00:08:19.400 00:08:29.830 Luke Daque: updates that were shared by Mitch last Wednesday for the users, subscriptions and organizations tables. So we should have all the calculated fields.

73 00:08:30.860 00:08:35.020 Luke Daque: Based on that based on our call.

74 00:08:35.620 00:08:37.609 Luke Daque: So yeah, I

75 00:08:38.000 00:08:43.960 Luke Daque: yeah, I guess once I get, I consolidate all the events. Then maybe we can merge this Pr.

76 00:08:46.570 00:08:55.049 Uttam Kumaran: Okay, great that’s perfect. And then, yeah, I think, for we have the stock puts meeting later.

77 00:08:55.340 00:08:55.710 Luke Daque: Yeah.

78 00:08:55.950 00:09:00.310 Uttam Kumaran: Be able to get the unified events in by then. Yeah.

79 00:09:00.310 00:09:00.950 Luke Daque: Agree.

80 00:09:01.420 00:09:05.640 Luke Daque: I also maybe just create a real

81 00:09:05.780 00:09:09.080 Luke Daque: dashboard for the events as well. I’m not sure how

82 00:09:09.720 00:09:13.829 Luke Daque: like what? What metrics you can add just accounts, yeah.

83 00:09:13.830 00:09:18.539 Uttam Kumaran: Exactly like I. Well, the one thing I want to enable is the join between

84 00:09:20.310 00:09:22.659 Uttam Kumaran: events and the users.

85 00:09:22.920 00:09:31.519 Uttam Kumaran: So I think we need 2 things. Once, once you create the events table, if you can just create like a a summary table like a quick, summary table that’s just

86 00:09:32.060 00:09:35.659 Uttam Kumaran: users. And then you pick off some events from

87 00:09:37.870 00:09:42.809 Uttam Kumaran: or you basically join. Yeah, you just pick off some events that are that were relevant in the metric sheet.

88 00:09:44.280 00:09:44.840 Luke Daque: Hmm.

89 00:09:44.840 00:09:50.000 Uttam Kumaran: And basically, I wanna just show that okay, we can. Now, we can now link the events to the users.

90 00:09:51.150 00:09:54.860 Luke Daque: How, how do we like join them? Just use that just email.

91 00:09:55.490 00:09:58.599 Uttam Kumaran: Yeah, what do you have? What do you have on the segment side?

92 00:09:59.770 00:10:01.649 Luke Daque: I don’t think there’s a

93 00:10:02.330 00:10:08.560 Luke Daque: well I have to look again. I’m not actually sure like, if there’s a user id. But like

94 00:10:09.750 00:10:15.524 Luke Daque: like, for I guess if there’s not none, then maybe we can use just the

95 00:10:16.660 00:10:19.089 Luke Daque: email for now email address.

96 00:10:20.520 00:10:24.150 Uttam Kumaran: Okay, yeah, maybe just do an email. And then we can ask

97 00:10:24.980 00:10:30.859 Uttam Kumaran: Mitch about if there’s another column to join there. I thought he mentioned that there is a user id

98 00:10:31.070 00:10:33.849 Uttam Kumaran: like I, there’s an identity column somewhere there.

99 00:10:34.350 00:10:37.040 Luke Daque: Yeah, I’ll have. I’ll have to take a look again.

100 00:10:37.410 00:10:39.020 Luke Daque: I’m not quite sure. Yeah.

101 00:10:39.020 00:10:55.150 Uttam Kumaran: Yeah, just keep maybe it’d be helpful while you’re while you’re going through it in the client, in the, in the, in our internal Stack List Channel. Can you just start a thread while you’re working today? That way? I can poke in and out. I’m sort of in. I have some client demos.

102 00:10:55.998 00:10:58.191 Uttam Kumaran: basically up until the

103 00:10:59.150 00:11:04.090 Uttam Kumaran: team meeting. But I I should be able to sort of give some comments.

104 00:11:04.541 00:11:08.460 Uttam Kumaran: Just keep this updated, and that way I can poke in and sort of assist

105 00:11:08.950 00:11:12.310 Uttam Kumaran: and then we don’t need to hop on or anything, so that’d be helpful.

106 00:11:12.900 00:11:13.800 Luke Daque: Sounds good.

107 00:11:16.100 00:11:34.809 Uttam Kumaran: Okay? And then, yeah, maybe, Kyle, we can go through your work. I feel like, I think some of those, some of the others are, gonna be busy today. I know Nico is out today. So maybe we could spend the next whatever amount of time just reviewing that. And then I also want to try and grab time

108 00:11:35.860 00:11:36.690 Uttam Kumaran: with

109 00:11:37.640 00:11:45.266 Uttam Kumaran: with Nico as as soon as we can on Monday and the analyst team to sort of get your questions answered?

110 00:11:45.790 00:11:50.099 Uttam Kumaran: so. But maybe I can. I can just take a look at stuff and see if I can provide any guidance.

111 00:11:51.030 00:11:52.250 Caio Velasco: Okay, perfect.

112 00:11:52.450 00:11:55.949 Caio Velasco: So let me. I’ll share my screen here. Then I’ll I’ll show you.

113 00:12:05.810 00:12:07.669 Caio Velasco: Okay. Can you guys see my screen?

114 00:12:10.170 00:12:11.040 Uttam Kumaran: Yes.

115 00:12:11.370 00:12:11.950 Caio Velasco: Yep.

116 00:12:15.350 00:12:18.140 Uttam Kumaran: And then I updated this Doc a bit.

117 00:12:20.180 00:12:23.179 Uttam Kumaran: I didn’t see your new comments, so I can go through that as well.

118 00:12:23.620 00:12:24.640 Caio Velasco: No worries, no.

119 00:12:24.640 00:12:26.869 Uttam Kumaran: But this dog is getting better. I feel like.

120 00:12:27.380 00:12:42.510 Caio Velasco: Yeah, yeah, no, it’s getting definitely better. And oh, when I started working, then I was always missing something for my own questions. So then it helped structure a little bit more. For example, yesterday was like, Okay, if I’m gonna go at some point, I’ll have to

121 00:12:44.630 00:12:47.160 Caio Velasco: create a Pr, or work, or yeah.

122 00:12:47.160 00:12:55.250 Caio Velasco: something. Right? So then it’s like, Okay, what should I do then? I was talking to Luke, and he told me like, Oh, we’re we’re doing everything in depth. That’s what we should do.

123 00:12:55.480 00:13:05.069 Caio Velasco: Then I just put a little bit here just to organize what is happening, so that I also understand. And well, if anyone else comes in as a ae or whatever

124 00:13:05.600 00:13:09.890 Caio Velasco: the person would be able to come here. And just like, Okay, I know what to do.

125 00:13:10.697 00:13:16.589 Caio Velasco: And but yeah, for this was just gonna be this part. But let me focus more on the

126 00:13:17.270 00:13:19.899 Caio Velasco: on the ticket. Let me see.

127 00:13:20.910 00:13:28.785 Caio Velasco: Okay, for example, this is the ticket I have. And these are the specifications like an initial ones.

128 00:13:29.859 00:13:39.440 Caio Velasco: Then I’ll say, okay, let me check the 1st one, and I have no idea about what gorge is or what macros are. So I started from literally from scratch

129 00:13:41.220 00:13:51.360 Caio Velasco: Then, when I was going into into Snowflake and trying to understand what was happening, I felt like I missed the structure so that my work is more efficient.

130 00:13:51.500 00:13:56.369 Caio Velasco: So I went to the let me get from here.

131 00:13:57.480 00:13:59.871 Caio Velasco: Where is this? From?

132 00:14:01.590 00:14:04.050 Caio Velasco: The only thing that I have a link in here? But

133 00:14:05.503 00:14:11.700 Caio Velasco: okay. So then I went to to the spreadsheet that you made some updates.

134 00:14:11.880 00:14:17.320 Caio Velasco: But before working into the metrics one.

135 00:14:17.430 00:14:21.960 Caio Velasco: I started something on my own, just to see if I was following my own reason.

136 00:14:24.240 00:14:25.650 Caio Velasco: Oh, thank you.

137 00:14:27.810 00:14:29.329 Caio Velasco: Let me hide this.

138 00:14:32.200 00:14:36.729 Caio Velasco: So I created one here. With the same idea.

139 00:14:36.950 00:14:40.549 Caio Velasco: But then I was like, okay. The the idea would be to have

140 00:14:41.190 00:14:44.229 Caio Velasco: I. I went to Snowflake, and I got all the

141 00:14:45.198 00:14:51.329 Caio Velasco: tables and column names from the gorgeous source, and I put them here?

142 00:14:52.189 00:14:58.069 Caio Velasco: And then I started like, okay, it would be nice to see like, if I’m creating the gorgeous dashboard

143 00:14:58.340 00:15:04.529 Caio Velasco: with some kind of metric that usually comes from the business questions.

144 00:15:04.710 00:15:18.899 Caio Velasco: And I will have a definition here, because that’s what I usually miss when I’m looking into the data to try to understand what they want. I don’t even know what a macro is. So this is the column for this, and then well, a brief description.

145 00:15:19.600 00:15:23.789 Caio Velasco: This is kind of like connected to the tickets. I’ll go back to the ticket in a bit.

146 00:15:24.555 00:15:28.969 Uttam Kumaran: And this is just if it’s being used or not. You know, for now.

147 00:15:29.110 00:15:37.510 Caio Velasco: For now there’s, of course, almost nothing. But this would be everything that we have as sources pointing to or potentially pointing to the dashboard.

148 00:15:38.419 00:15:53.040 Caio Velasco: and then, when I started like, look into the going through the questions and going to the database. And then I come here. It’s like, okay, this is what I have for now, maybe the macro metric that they want from the 1st question.

149 00:15:53.240 00:15:59.360 Caio Velasco: which is which macros are being used the most. Yeah.

150 00:15:59.787 00:16:11.449 Caio Velasco: maybe it would come from this table. I I look into the table. And then I saw some things like, Okay, maybe come from there. And then, when I wasn’t wasn’t when I was in the ticket. I started doing this

151 00:16:11.560 00:16:23.499 Caio Velasco: this flow also for Nicholas, so that he understand a bit more because he sent me a message saying, like, Hey, I’m not an engineer, so I might need more guidance, understanding like, what exactly do we need from the client.

152 00:16:23.760 00:16:30.919 Caio Velasco: So there’s like, Okay, if I’m doing this work, this is what usually I miss, like the definitions of like, what is a macro, for example?

153 00:16:31.110 00:16:42.570 Caio Velasco: And usually there are answer to potential questions that we always have when we go to the database. So usually, if we are talking about a macro, I usually try to see if there’s a table name or column name

154 00:16:42.790 00:17:02.809 Caio Velasco: for, for that matter, if there’s no macro in the name itself, then yeah, it gets a bit more. It takes a bit more time to understand where is the information coming from? So this is also something that I don’t know if the client has any knowledge on this. Or if there’s any data analysts over there, there would be able to help in this. But at least they know

155 00:17:03.030 00:17:09.360 Caio Velasco: what is happening, and why? Sometimes it’s difficult, and it takes more time than, for example.

156 00:17:09.838 00:17:13.860 Caio Velasco: For this one, I would say, like, what are the macros? What? What are macros?

157 00:17:14.371 00:17:19.289 Caio Velasco: And then I found a website from gorgeous to see like, Okay, is this

158 00:17:19.510 00:17:31.829 Caio Velasco: what we are looking for? Should I get? Come here and there’s and then understand exactly what type of macro are you looking for? So that when I go to the data, see? Like, Oh, okay, it’s in this column, for example.

159 00:17:34.350 00:17:40.449 Caio Velasco: and and then I did some, just some digging. And I’m sure, like, okay, if I go to the macro table and get just a role.

160 00:17:40.720 00:17:46.930 Caio Velasco: I have this from the most important columns that I found. Is this what it we are looking for?

161 00:17:47.040 00:17:50.210 Caio Velasco: And is this coming from here, for example.

162 00:17:50.550 00:17:50.900 Uttam Kumaran: Yeah.

163 00:17:50.900 00:17:52.869 Caio Velasco: But but let’s see.

164 00:17:53.100 00:18:21.789 Caio Velasco: you know, this is I mean, of course, this is my work, but maybe the the person on the client side was like, Oh, okay, I now understand what they need something like that. And the same for tickets to when I was trying to understand like which ticket fields are being used the most today. What is the tickets? Field? And then I went to the database. I saw 2 tables, ticket details and tickets, but in ticket details there were there was some, I mean, some columns. This one was the only interesting one.

165 00:18:21.950 00:18:25.240 Caio Velasco: and there’s like a huge crazy Json inside

166 00:18:25.570 00:18:38.432 Caio Velasco: messages on inside. And then I was looking into it. I was like, Okay, maybe this is coming from inputs that the that the client I mean the user is is doing whatever part of the Javi

167 00:18:38.990 00:18:43.179 Caio Velasco: workflow or purchase workflow.

168 00:18:43.430 00:18:44.820 Caio Velasco: And

169 00:18:46.920 00:19:07.090 Caio Velasco: and yeah, and then I found something here saying, Is it? Is it coming from here or not. And then, yeah, that’s what I was just doing today with more emphasis. And then I hope that when Nicholas see this, he can like, oh, okay, maybe. Now I understand a bit more. What should we answer? So instead of them just giving us this.

170 00:19:07.450 00:19:11.900 Caio Velasco: maybe Nico can look into this. And like, be a bit more specific.

171 00:19:12.030 00:19:13.429 Caio Velasco: That was the idea.

172 00:19:14.970 00:19:18.409 Caio Velasco: Yeah, I don’t know if it’s making sense or or not, or.

173 00:19:18.410 00:19:25.000 Uttam Kumaran: No, it makes sense. I mean again, it just starts to ask really helpful questions. I think my question would be the difference between

174 00:19:25.240 00:19:30.865 Uttam Kumaran: what we wanted like. I went ahead and did the metrics and dimensions sheet the the

175 00:19:32.190 00:19:49.079 Uttam Kumaran: yeah, that one, I guess. What is your what is your feedback on this, like versus versus yours, like, how can we make this one better, or like, for example, these are the ones I made for the dashboard. Do you think that we want to have like one area with all of our metrics?

176 00:19:49.190 00:19:52.870 Uttam Kumaran: Do you want it to? Should we? Should we just have it be dashboard

177 00:19:53.510 00:19:56.180 Uttam Kumaran: focus. And then we like ditch. This basically.

178 00:19:57.270 00:20:02.609 Caio Velasco: So when I look at the 1st one I was thinking like, who is the person

179 00:20:03.220 00:20:07.369 Caio Velasco: looking at this first? st Is this for the client? Or is this for the ae.

180 00:20:08.010 00:20:14.600 Uttam Kumaran: Yeah. So the my purpose for this is that when they go to build a dashboard it’s validated against these.

181 00:20:15.490 00:20:22.149 Uttam Kumaran: meaning they can go select which metric they have and don’t have.

182 00:20:22.610 00:20:26.650 Uttam Kumaran: So that’s 1 of the 1st questions is like, what metrics do I have available?

183 00:20:27.380 00:20:31.360 Uttam Kumaran: But I don’t know. Like, if you go to the net margin, dash you’ll see that the

184 00:20:33.010 00:20:40.269 Uttam Kumaran: you’ll see that these metric names here are validated against that that list, meaning it’s

185 00:20:41.050 00:20:43.450 Uttam Kumaran: it’s a join against that list.

186 00:20:43.450 00:20:51.850 Caio Velasco: Okay, okay, I see. And, for example, let me let me see if I understand here. So, for example, this metric here who define this

187 00:20:53.010 00:20:57.009 Caio Velasco: was someone that was starting to build the dashboard, or or.

188 00:20:57.010 00:21:00.250 Uttam Kumaran: No, we did so. The Ae. Team built it in.

189 00:21:00.250 00:21:00.960 Caio Velasco: Okay.

190 00:21:01.110 00:21:03.919 Uttam Kumaran: Yeah. The 18 built in as part of fact orders.

191 00:21:04.180 00:21:09.440 Uttam Kumaran: The analyst team needs it as part of this net margin dashboard.

192 00:21:11.000 00:21:21.269 Uttam Kumaran: So my, my question is more of like when they go to build this dashboard. For example, here, this is a piece of logic that that should probably be in

193 00:21:22.040 00:21:23.040 Uttam Kumaran: the repo.

194 00:21:24.370 00:21:35.249 Uttam Kumaran: Otherwise this is staying in Meta Base somewhere, right? But they’re building what they call as like a product category. So one, this helps understand what metrics are they calculating that

195 00:21:35.360 00:21:37.059 Uttam Kumaran: isn’t coming from us?

196 00:21:38.090 00:21:46.510 Uttam Kumaran: There may they may do some quick divides or rounding that we don’t care about, but like, if there’s key pieces of logic like this, or like this.

197 00:21:46.920 00:22:01.669 Uttam Kumaran: that we can just sort of bring into the repo we should. So I want us to have visibility. But if you scroll down you’ll see that there’s now here. The here’s like other values, like, for example, they want these values in.

198 00:22:02.550 00:22:07.949 Uttam Kumaran: They want these values in the dashboard. So then they can just look and see which metrics are available.

199 00:22:10.910 00:22:20.640 Caio Velasco: Okay, okay. So okay, I see. So they are. Of course, they are doing something directly on the, on, on the data visualization tool they are using.

200 00:22:20.960 00:22:23.640 Caio Velasco: and we don’t necessarily have that

201 00:22:24.020 00:22:27.650 Caio Velasco: information. For example, this thing here came from them.

202 00:22:32.660 00:22:33.310 Uttam Kumaran: Yeah.

203 00:22:33.820 00:22:34.910 Caio Velasco: Is that right? Thank you.

204 00:22:39.990 00:22:40.590 Caio Velasco: Let me see if.

205 00:22:40.590 00:22:48.310 Uttam Kumaran: So if you go to your. So your dad, if you go to your dashboard, this implies that they’re so for this one they’re gonna start with.

206 00:22:49.340 00:22:52.669 Uttam Kumaran: they’re gonna start with this. And then

207 00:22:53.000 00:22:55.460 Uttam Kumaran: we fill this out. Is that correct?

208 00:22:56.210 00:22:56.930 Caio Velasco: Yes.

209 00:22:57.675 00:22:57.990 Caio Velasco: Okay.

210 00:22:57.990 00:22:58.620 Caio Velasco: Exactly. Yeah.

211 00:22:58.620 00:23:04.739 Uttam Kumaran: Actually, that makes sense. Because right now, I sort of doing that in 2 places, this actually makes

212 00:23:05.280 00:23:09.549 Uttam Kumaran: sense. This makes more sense because this combines both of these basically.

213 00:23:10.580 00:23:16.430 Caio Velasco: Yeah, I think that. Yeah, yeah, I know where where you’re heading now. Yes, some something like that to combine both sides as well.

214 00:23:16.430 00:23:17.280 Uttam Kumaran: Okay, do.

215 00:23:17.280 00:23:24.180 Caio Velasco: What we do, so that we have like a tracking mechanism at the end of the day. That’s really like, if you wanna do what is

216 00:23:24.580 00:23:38.470 Caio Velasco: using a certain dashboard. You just come here. It’s like, Okay, these are all the sources. Maybe if there is for some reason a change in a source or a schema, or whatever. Maybe you can come here quickly. And okay, I have to change this or that.

217 00:23:38.580 00:23:42.809 Caio Velasco: That was my initial idea. But I mean, definitely open for suggestions.

218 00:23:52.350 00:23:53.520 Caio Velasco: And this one.

219 00:23:53.520 00:24:01.199 Uttam Kumaran: Well, then, we will sort of migrate these to to this format. But I think this is a great format moving forward for all dashboards.

220 00:24:02.317 00:24:09.769 Uttam Kumaran: And basically allows, say, we, we have to basically say without they need to fill all of this out, 1st this side

221 00:24:10.200 00:24:16.870 Uttam Kumaran: and then we come in and fill up this side and then that establishes what work needs to be done for us.

222 00:24:19.120 00:24:21.119 Caio Velasco: Yes, but do you think that

223 00:24:21.240 00:24:27.779 Caio Velasco: it will always start with us in terms of going into Snowflake and getting all the because I started.

224 00:24:27.800 00:24:28.510 Uttam Kumaran: No, no.

225 00:24:28.510 00:24:34.470 Caio Velasco: So snowflake, and got everything, all the tables and columns, names, and I put it there, or the opposite.

226 00:24:34.470 00:24:38.519 Uttam Kumaran: I mean, ideally, it should start from the analysts need.

227 00:24:39.086 00:24:44.769 Uttam Kumaran: because we’re not gonna like, I don’t want us to just build models just to build models. We we happen to be doing that

228 00:24:44.900 00:24:50.049 Uttam Kumaran: because at the moment we’re sort of like in a little bit of like playing catch up

229 00:24:51.510 00:24:56.589 Uttam Kumaran: in most situations. That’s the process we’ve gone through. But I do think it actually should start from

230 00:24:57.320 00:24:58.280 Uttam Kumaran: this side.

231 00:24:59.190 00:25:01.590 Caio Velasco: Okay. And do you think that before?

232 00:25:02.060 00:25:14.039 Caio Velasco: I mean, I’m I’m trying to think who would really have to touch these? This spreadsheet at the end of the at the end of the day, because is getting from here. Maybe we can structure.

233 00:25:14.040 00:25:16.100 Uttam Kumaran: The analyt like

234 00:25:16.100 00:25:25.840 Uttam Kumaran: right. The the analysts should take this and be able to go into Snowflake and sort of get it break down for us. What, ma, what metrics they want

235 00:25:26.140 00:25:31.629 Uttam Kumaran: right like I I don’t think I don’t think what the requirements we got for this were enough at all

236 00:25:31.990 00:25:32.620 Uttam Kumaran: like.

237 00:25:32.620 00:25:33.389 Caio Velasco: Yeah, that’s true.

238 00:25:33.390 00:26:02.819 Uttam Kumaran: I get that? There’s just 5 questions, but then tomorrow there’ll be 10 questions. The next day there’ll be 15 questions. We’re in the business of structuring scalable models. Right? So we will see all of these things that they want. And then also probably notice. Okay, we should probably build like a few different models around this. We’ll keep a little bit of extra information. We’ll satisfy your needs. But then there’s gonna be more stuff there, right? So just answering those questions for us isn’t helpful. I want this like, and I don’t. I think they can

239 00:26:03.140 00:26:12.049 Uttam Kumaran: do this level of granularity, because for most dashboards we are doing dashboard mockups where we’re going to the client and and asking them how they want the dashboard built things like that.

240 00:26:12.440 00:26:18.630 Uttam Kumaran: So I know in this case we started from this side, but I think we’ll start from this side moving forward. But

241 00:26:18.920 00:26:22.289 Uttam Kumaran: we’re sort of in the situation. We are right now for this. So.

242 00:26:22.760 00:26:23.480 Caio Velasco: That’s fine!

243 00:26:23.990 00:26:25.839 Uttam Kumaran: May not need everything, so.

244 00:26:26.260 00:26:36.180 Caio Velasco: Okay, so let’s say that they would start with like this 3 lines, and then I would come here and I would find in the database. What are the most important things for those things.

245 00:26:36.300 00:26:44.020 Uttam Kumaran: Yeah. And ideally, they can put even here like. And I think maybe in the definition, they put like an example, or like something like that, like

246 00:26:44.490 00:26:51.210 Uttam Kumaran: where to go validate this. But then also. So on. When we do this side, we’re gonna

247 00:26:51.320 00:26:59.450 Uttam Kumaran: we’re gonna start moving these to like actual like March models, right? So like, how do you see that interaction with this exercise.

248 00:27:02.730 00:27:04.980 Caio Velasco: You say the Dbt models.

249 00:27:05.250 00:27:05.660 Uttam Kumaran: Yes.

250 00:27:05.660 00:27:08.570 Caio Velasco: Yeah, see this.

251 00:27:10.670 00:27:14.889 Caio Velasco: Yeah, maybe this is just a way of well, make sure that they

252 00:27:15.810 00:27:20.580 Caio Velasco: not only they have what they need, but they are also being specific enough.

253 00:27:20.850 00:27:23.359 Caio Velasco: And then, when we moved to

254 00:27:24.610 00:27:29.679 Caio Velasco: well, to write in the Dbt models, then at least, we I mean, we have

255 00:27:30.470 00:27:36.249 Caio Velasco: an idea of what are the source of truth or everything we need. So I think it’s just a

256 00:27:36.560 00:27:38.000 Caio Velasco: like a process.

257 00:27:38.620 00:27:42.520 Caio Velasco: To be honest, I’m I’m I’m from. If I go now and try to

258 00:27:42.830 00:27:48.829 Caio Velasco: to view the Dbt model for well, one of the fact tables that will build the gorgeous dashboard.

259 00:27:49.705 00:27:54.969 Caio Velasco: Maybe I still wouldn’t need another column here to track that as well.

260 00:27:55.670 00:27:58.729 Caio Velasco: But I mean there is a connection, for sure.

261 00:28:04.740 00:28:11.920 Caio Velasco: because at the end of the day, what? What this is giving us is input for for the from clause in the Dbt models.

262 00:28:12.350 00:28:13.110 Caio Velasco: bye.

263 00:28:13.460 00:28:15.750 Caio Velasco: And then we are tracking everything

264 00:28:32.220 00:28:33.382 Caio Velasco: that makes sense.

265 00:28:34.030 00:28:35.039 Uttam Kumaran: That makes sense.

266 00:28:35.150 00:28:38.700 Uttam Kumaran: I just think for for this, like.

267 00:28:39.340 00:28:44.540 Uttam Kumaran: okay, so we’re gonna we’re gonna then replace probably replace these with like our models, basically

268 00:28:46.940 00:28:51.130 Uttam Kumaran: meaning, like, if we build like a a dim macros

269 00:28:53.300 00:28:57.249 Uttam Kumaran: or a dim users, we would then replace these with that, because

270 00:28:57.360 00:29:02.600 Uttam Kumaran: these guys want to know where, in the where they can go. Get it from Mart’s.

271 00:29:03.470 00:29:09.099 Caio Velasco: Yeah, yeah, yeah, no. Exactly. So then maybe we could add some new columns and

272 00:29:09.290 00:29:19.610 Caio Velasco: and keep the tracking mechanism even for that part. But like, if this, if this table here ended up pointing to whatever fact table.

273 00:29:19.830 00:29:20.840 Uttam Kumaran: Okay. Okay.

274 00:29:21.220 00:29:30.350 Caio Velasco: Then we have, like a complete, let’s say, data catalog behind the Dbt data image or something like that

275 00:29:30.730 00:29:32.060 Caio Velasco: that makes sense. Yeah.

276 00:29:32.490 00:29:35.770 Uttam Kumaran: Let’s yeah, maybe let’s put that here.

277 00:29:36.070 00:29:41.739 Uttam Kumaran: cause that way. They’re not gonna look at any of this like one. I guarantee it. So.

278 00:29:41.740 00:29:42.160 Caio Velasco: Have a good weekend.

279 00:29:42.160 00:29:46.149 Uttam Kumaran: We can put. We can put the the March model here.

280 00:29:46.640 00:29:49.420 Uttam Kumaran: But then this is really helpful for us to look at.

281 00:29:49.620 00:29:54.749 Uttam Kumaran: Of course, if there’s metrics that are more calculated or more complicated, they won’t have like a direct source.

282 00:29:55.620 00:29:57.319 Uttam Kumaran: But this is perfect.

283 00:29:58.500 00:30:00.679 Caio Velasco: Yeah, I think it’s the ae

284 00:30:01.910 00:30:12.710 Caio Velasco: at the end of the day. It’s the ae responsibility to make sure that like, hey, if I’m building a Dbt model, and I’m using whatever sources I’m I’m sure that I’m coming to this

285 00:30:12.840 00:30:15.220 Caio Velasco: spreadsheet and putting everything here.

286 00:30:15.653 00:30:19.796 Caio Velasco: And then one day, if we have a problem, we will see if that helped or not.

287 00:30:20.550 00:30:21.190 Uttam Kumaran: Okay.

288 00:30:29.550 00:30:33.710 Uttam Kumaran: okay, perfect. So then let’s I wanna talk about this.

289 00:30:33.950 00:30:40.239 Uttam Kumaran: I actually want to talk about this in the team meeting today. So maybe, Kyle, I can ask you if you would like to present that.

290 00:30:41.240 00:30:45.659 Caio Velasco: Just like an example for this for the whole data team that way, they can see this.

291 00:30:46.375 00:30:52.230 Uttam Kumaran: We have it. We do it. We do a Demos section like towards the end of the meeting.

292 00:30:52.912 00:31:04.079 Uttam Kumaran: So maybe you can present this and then that way, I think some people can just see our new process. And then on Monday we’ll talk about how to. Actually, we’ll talk just with the data team on actioning on this.

293 00:31:04.760 00:31:09.070 Caio Velasco: Okay, so, lower.

294 00:31:09.510 00:31:10.070 Uttam Kumaran: Okay.

295 00:31:12.240 00:31:20.540 Uttam Kumaran: okay, awesome. I know we’re at time, guys. Well, thank you. Yeah, slack me. If anything, I’ll be preparing for a team meeting and some client work.

296 00:31:21.450 00:31:23.490 Uttam Kumaran: But yeah, I’m around.

297 00:31:24.550 00:31:26.760 Luke Daque: Thank you. Thank you. Thank you.

298 00:31:26.760 00:31:32.377 Uttam Kumaran: Thank you. And and the one thing Kyle, maybe if you if you want to message

299 00:31:33.320 00:31:44.349 Uttam Kumaran: Pius in the Javi channel. Pius is an an analyst on that team. He may be able to assist with some requirements on gorgeous.

300 00:31:44.940 00:31:46.810 Uttam Kumaran: I would just ping him there.

301 00:31:47.580 00:31:48.850 Caio Velasco: Bias, okay.

302 00:31:49.180 00:31:52.504 Uttam Kumaran: Yeah, he’s cool. Guy.

303 00:31:53.483 00:31:54.330 Caio Velasco: Oh, nice!

304 00:31:54.780 00:31:55.390 Uttam Kumaran: Okay.

305 00:31:55.560 00:31:56.619 Uttam Kumaran: Alright. Thanks. Guys.

306 00:31:56.620 00:31:57.630 Caio Velasco: Alright! Alright! Thank you.

307 00:31:58.630 00:31:59.100 Uttam Kumaran: Excellent.