Meeting Title: Data Team Retro Date: 2025-02-28 Meeting participants: Luke Daque, Michael Weinberg, Uttam Kumaran, Bo Yoon, Robert Tseng, Sahana Asokan, Awaish Kumar, Caio Velasco
WEBVTT
1 00:07:47.750 ⇒ 00:07:49.040 Uttam Kumaran: Hello!
2 00:07:52.180 ⇒ 00:07:53.410 Robert Tseng: Hello!
3 00:07:53.890 ⇒ 00:07:57.189 Robert Tseng: You’re a lakers fan now that Don Chish is in la.
4 00:07:57.190 ⇒ 00:07:59.710 Uttam Kumaran: Now, what do you mean now?
5 00:08:00.950 ⇒ 00:08:02.220 Uttam Kumaran: Since the womb.
6 00:08:02.770 ⇒ 00:08:04.020 Robert Tseng: Okay. Okay.
7 00:08:05.660 ⇒ 00:08:11.860 Uttam Kumaran: You know I have my I have my favorite book with me.
8 00:08:13.470 ⇒ 00:08:15.490 Robert Tseng: Oh, yeah. Okay. Nice.
9 00:08:15.900 ⇒ 00:08:23.069 Uttam Kumaran: Dude. I grew up like, I guess maybe we didn’t talk about. I didn’t know. I didn’t know. I guess I should have asked you. But yeah, dude I I grew up like
10 00:08:23.220 ⇒ 00:08:27.980 Uttam Kumaran: the biggest Kobe Bryant fan ever basically.
11 00:08:28.420 ⇒ 00:08:30.210 Robert Tseng: Hey? Okay. I did not know that.
12 00:08:30.760 ⇒ 00:08:32.409 Uttam Kumaran: Cause the warriors.
13 00:08:32.880 ⇒ 00:08:34.669 Uttam Kumaran: The warriors sucked like.
14 00:08:34.679 ⇒ 00:08:37.459 Robert Tseng: Yeah, they stink. But I was.
15 00:08:37.929 ⇒ 00:08:52.479 Uttam Kumaran: Okay. Then I respect that, too. I just like my dad was a lakers fan. So I grew up like a huge Kobe fan. And then, like, Yeah, when Monte Ellis and Baron Davis had a moment, I I’m I root for the bay as like a
16 00:08:52.760 ⇒ 00:08:58.810 Uttam Kumaran: bay area, but then I can’t root for the warriors, because the warriors fans are very annoying now.
17 00:08:59.930 ⇒ 00:09:00.460 Robert Tseng: And.
18 00:09:00.460 ⇒ 00:09:06.130 Uttam Kumaran: And they had. They had a good moment. It looks like things are crumbling, so I’m happy. I’m happy for
19 00:09:06.700 ⇒ 00:09:10.969 Uttam Kumaran: the championship to go back to La. Otherwise I’m not a big la person.
20 00:09:11.310 ⇒ 00:09:15.300 Uttam Kumaran: just for basketball. I I’m a huge la fan, so I’m very happy.
21 00:09:15.300 ⇒ 00:09:15.900 Robert Tseng: Hmm!
22 00:09:16.960 ⇒ 00:09:19.880 Robert Tseng: Maybe we’ll change your mind when we go to La in a month.
23 00:09:20.483 ⇒ 00:09:38.520 Uttam Kumaran: We gotta steal, we gotta steal well, I’ve just dude. I just beef with, because I I like love Norcal so I can’t. I can’t root, for I can’t root for Socal. But I I think we got a steal of a trade when with Dontech. So.
24 00:09:38.630 ⇒ 00:09:40.090 Robert Tseng: Oh, yeah, for sure.
25 00:09:41.300 ⇒ 00:09:44.750 Uttam Kumaran: You know. Do you remember when they tried to trade Chris Paul to the Lakers.
26 00:09:44.980 ⇒ 00:09:48.080 Robert Tseng: How did that get blocked? And this didn’t get blocked? This is that.
27 00:09:48.080 ⇒ 00:09:57.149 Uttam Kumaran: They blocked that because it was rigged. David Stern was like this was too much like, we can’t have Chris Paul Prime, Chris Paul playing with Kobe. So we’re gonna block it.
28 00:09:58.150 ⇒ 00:10:08.840 Uttam Kumaran: executive order. And we’re now we’re getting retribution where it’s they allowed this like. And Anthony Davis got injured his 1st game.
29 00:10:09.510 ⇒ 00:10:09.960 Uttam Kumaran: It’s
30 00:10:10.410 ⇒ 00:10:10.920 Robert Tseng: Yeah.
31 00:10:12.270 ⇒ 00:10:17.279 Uttam Kumaran: It’s it’s it’s just insane. I’m very happy, though I I haven’t been able to buy any merch.
32 00:10:17.620 ⇒ 00:10:21.320 Uttam Kumaran: I actually did. I do have Dallas Luca Merch
33 00:10:21.660 ⇒ 00:10:26.257 Uttam Kumaran: that I would work because I loved him as a player. I’m not a big fan of Dallas, but
34 00:10:27.250 ⇒ 00:10:31.600 Uttam Kumaran: yeah, I’m waiting for Nba store to then give me something.
35 00:10:32.850 ⇒ 00:10:37.509 Uttam Kumaran: I guess. Yeah. When when we’re when we’re in la, I’ll I’ll I’ll try to get something.
36 00:10:38.010 ⇒ 00:10:38.630 Robert Tseng: Yeah.
37 00:10:43.690 ⇒ 00:10:47.700 Uttam Kumaran: Cool. Let’s see, I think every lot of folks are here.
38 00:10:50.980 ⇒ 00:10:54.590 Uttam Kumaran: Let me message, Luke.
39 00:11:17.730 ⇒ 00:11:18.730 Uttam Kumaran: Hey, Mike.
40 00:11:20.540 ⇒ 00:11:22.170 michael weinberg: Hey? How’s it going.
41 00:11:23.050 ⇒ 00:11:27.019 Uttam Kumaran: Good dude long time. I don’t think I’ve seen your face in a while, but we talk all the time.
42 00:11:27.420 ⇒ 00:11:31.540 michael weinberg: I know. Yeah, I was thinking exactly that I’ve I’ve my hair back.
43 00:11:31.540 ⇒ 00:11:34.080 michael weinberg: Heck no flip down to here.
44 00:11:34.080 ⇒ 00:11:35.070 Uttam Kumaran: I know.
45 00:11:35.633 ⇒ 00:11:42.379 Uttam Kumaran: Maybe while we’re waiting on one or 2 more people, maybe I’ll just have you give an introduction. So you are speaking to
46 00:11:42.500 ⇒ 00:11:51.560 Uttam Kumaran: a data team minus one person. And maybe I can give a brief intro because you’re not gonna hype yourself up
47 00:11:52.362 ⇒ 00:12:05.047 Uttam Kumaran: as much. But Mike is a first, st a really really good friend of mine. We worked together at we work which was my 1st job, and Mike was on the data team there.
48 00:12:06.110 ⇒ 00:12:21.769 Uttam Kumaran: I don’t know what your title was, but definitely was too low at the time, and since then has worked as like a data architect, like has worked basically every job in data. Also, very interestingly, has worked on a lot of the Democratic
49 00:12:21.950 ⇒ 00:12:25.740 Uttam Kumaran: national campaigns. I’m on the data team. So every
50 00:12:25.890 ⇒ 00:12:28.969 Uttam Kumaran: 4 years or so they get like a crew of like
51 00:12:29.400 ⇒ 00:12:37.802 Uttam Kumaran: bunch of like, pretty crazy data people to just go work for like pennies or for free. I don’t know if you even got paid to basically like work on the campaign. So that’s
52 00:12:38.250 ⇒ 00:12:54.190 Uttam Kumaran: that was really cool. And yeah, Mike’s been a really good friend of mine and a really amazing mentor as we building Brainforge. But even otherwise, in data. And it’s sort of who I bounce a lot of ideas about like how data is changing. So I’m excited. He’s gonna be joining us just to sort of
53 00:12:54.200 ⇒ 00:13:10.290 Uttam Kumaran: assist in one helping everybody in the team sort of just understanding how they can be better engineers. But also help us with some of the larger architecture related. Projects, especially around thing, like some of the things we’re working on with urban stems
54 00:13:10.380 ⇒ 00:13:19.239 Uttam Kumaran: where they have, like a couple of really large database decisions to make I think Mike is going to be really helpful there. So yeah, Mike, maybe I’ll let you give
55 00:13:19.420 ⇒ 00:13:20.626 Uttam Kumaran: an intro
56 00:13:21.500 ⇒ 00:13:22.270 Uttam Kumaran: Please.
57 00:13:24.630 ⇒ 00:13:26.239 michael weinberg: Yeah, I mean, I I met.
58 00:13:26.360 ⇒ 00:13:34.819 michael weinberg: I’m gonna return the favor a little bit I I met Utam at we work. Was that your 1st was that your 1st job Utam.
59 00:13:34.970 ⇒ 00:13:37.819 michael weinberg: So it’s literally Utam’s 1st job. And I think, like
60 00:13:38.340 ⇒ 00:13:47.279 michael weinberg: within like a year, it’s just like really obvious that Tom’s just killing it. And I I think I must have said to him very quickly, I remind him this all the time. It’s gonna probably embarrass. I’m like.
61 00:13:47.540 ⇒ 00:13:52.880 michael weinberg: you’re gonna be my boss one day, like, mark my words, because Utam’s
62 00:13:53.140 ⇒ 00:13:59.362 michael weinberg: super smart. I have not met very many people on this planet who are holistic thinkers like you, Tom.
63 00:14:00.490 ⇒ 00:14:08.670 michael weinberg: so I I’m personally excited to be here. I feel vindicated. Personally, I I knew this day would come someday.
64 00:14:10.168 ⇒ 00:14:23.430 michael weinberg: yeah. I mean also, one thing I’ll add about democratic campaigns is that you you work half of for for half of the money that you would get elsewhere at best. But you do work twice the hours.
65 00:14:23.940 ⇒ 00:14:26.390 michael weinberg: So there’s there’s that. That’s it’s it’s
66 00:14:28.997 ⇒ 00:14:36.342 michael weinberg: but you you do. You do work with really amazing people. So that that’s always a a cool experience.
67 00:14:37.620 ⇒ 00:14:40.919 michael weinberg: What? What? What can I? What can I say about myself?
68 00:14:41.370 ⇒ 00:14:45.901 michael weinberg: I’ll just. I’ll just say a tiny bit, I guess, about my background
69 00:14:46.750 ⇒ 00:14:53.808 michael weinberg: to give some flavor. And then, just you know talk about how I’d like to help. So
70 00:14:54.840 ⇒ 00:14:58.420 michael weinberg: I like, I started off in in data science. But like
71 00:14:58.610 ⇒ 00:15:07.389 michael weinberg: only briefly, because it turns out that, like almost all of data science and like 2014, 15 was like
72 00:15:07.850 ⇒ 00:15:11.799 michael weinberg: writing sequel, making features and stuff like that. And then
73 00:15:12.378 ⇒ 00:15:18.510 michael weinberg: trying to make your queries work. So I very quickly got into like optimization.
74 00:15:19.110 ⇒ 00:15:35.060 michael weinberg: Just because I was given really bad resources turned out, I had a little bit of an act for data engineering. Spent some time doing like some integration stuff for some tiny company in New York, doing like job board listing. So I spent like a year just writing regular expressions.
75 00:15:35.380 ⇒ 00:15:37.869 michael weinberg: A person’s career path for how they get
76 00:15:38.620 ⇒ 00:15:53.810 michael weinberg: to be an expert is is often strange. So I went, I worked for the Clinton campaign. After that they were like, Hey, like, do you know this database, Vertica? And I was like, what the hell is, Vertica? And they’re like, it’s the database we use. And I was like, Oh, okay. And they’re like.
77 00:15:54.430 ⇒ 00:15:57.710 michael weinberg: so what do you know? And I was like, well, I read.
78 00:15:57.880 ⇒ 00:16:07.860 michael weinberg: I read the Manual, and they’re like, Okay, you’re hired. And then I did exactly that. Found that data. Warehouses were super cool. Got a job with. We work after that.
79 00:16:08.268 ⇒ 00:16:12.449 michael weinberg: They were like on like a redshift stack. And I was like, oh, this is
80 00:16:13.220 ⇒ 00:16:24.670 michael weinberg: easier than this vertica thing that I just learned, you know. Found that I enjoyed working with the hyper growth sort of problems that come up. You know. Gotta onboard. People gotta figure out governance
81 00:16:26.626 ⇒ 00:16:36.659 michael weinberg: was super lucky. I think Botham and I were lucky to be able to work with a particularly stupendous manager named who
82 00:16:37.098 ⇒ 00:16:44.519 michael weinberg: provided a lot of cover for us as a team, and encourage us to take big risks. I think that because of those big swings we were able to grow a lot. So
83 00:16:46.190 ⇒ 00:16:48.090 michael weinberg: great to be able to
84 00:16:48.574 ⇒ 00:16:51.406 michael weinberg: build a lot of interesting things. And then
85 00:16:52.190 ⇒ 00:17:05.159 michael weinberg: after that so I got like called up again for the Biden campaign did that it was quicker and and less eventful and painful than the
86 00:17:05.680 ⇒ 00:17:13.394 michael weinberg: Clinton election and then did some consulting after that. And then I was like an engineering manager at a couple of companies.
87 00:17:14.296 ⇒ 00:17:21.903 michael weinberg: following that election. And so I’ve kind of taken a little bit of like an around the world tour in the career space.
88 00:17:23.794 ⇒ 00:17:30.580 michael weinberg: and so now here I I’m excited personally to just be able to be helpful.
89 00:17:31.147 ⇒ 00:17:34.802 michael weinberg: In whatever capacity makes sense for you guys.
90 00:17:35.590 ⇒ 00:17:39.130 michael weinberg: and that could be anything from
91 00:17:39.959 ⇒ 00:17:44.870 michael weinberg: just being a Robert duck for you to talking about architecture,
92 00:17:45.540 ⇒ 00:17:52.850 michael weinberg: and maybe helping figure out what are things that you think would make Rainforge better place, and then see what I can do.
93 00:17:54.280 ⇒ 00:18:02.540 Uttam Kumaran: Cool. And yeah for context, I I’m sure everybody, I think probably the one company between we work and now is Warby Parker. So Mike was at 4 B. For a bit.
94 00:18:02.980 ⇒ 00:18:05.160 Uttam Kumaran: challenging in many ways.
95 00:18:05.790 ⇒ 00:18:07.872 michael weinberg: Too. There was an energy company
96 00:18:08.220 ⇒ 00:18:14.389 Uttam Kumaran: Oh, yeah, the energy company. But I think, yeah, I think in terms of our world like more Ecom stuff like, that’s probably
97 00:18:14.580 ⇒ 00:18:24.960 Uttam Kumaran: the core thing that the energy company. Yeah, there’s a lot of interesting things there, too. So yeah, so I’m I’m excited. I think Mike is a great person that I’ll sort of connect everyone individually with, and
98 00:18:25.430 ⇒ 00:18:41.609 Uttam Kumaran: basically can can leverage for for whatever we need and then so today, I wanted to sort of just run a typical retro. So I sent an a link here in the zoom channel in the zoom chat. If everyone can open that, and I think,
99 00:18:42.640 ⇒ 00:18:52.039 Uttam Kumaran: sort of the way that we’ll be running this for folks that have not been part of a retro is basically one. We sort of start with adding
100 00:18:52.230 ⇒ 00:19:01.680 Uttam Kumaran: just things that are going well, things that aren’t going well, topics that we want to discuss as a team. So these these may be client specific. These may be
101 00:19:02.346 ⇒ 00:19:05.503 Uttam Kumaran: just about process. So anything
102 00:19:06.350 ⇒ 00:19:13.410 Uttam Kumaran: on your mind. We could add here the the primary way to do that is to add, post. It notes here. So I will go ahead and add
103 00:19:14.760 ⇒ 00:19:19.170 Uttam Kumaran: some here. But basically, the goal is to
104 00:19:19.300 ⇒ 00:19:27.800 Uttam Kumaran: add post-its across each of these 4 categories. Where the topic is relevant. For example, if I have a question about
105 00:19:28.114 ⇒ 00:19:44.579 Uttam Kumaran: data engineering that’s related to the way we push code into the pipeline. I would add it here. If there’s something related to data modeling, I would add it in a data modeling section, so feel free to just copy some of these posted notes that I’m putting in here and just make a few more.
106 00:19:44.900 ⇒ 00:19:58.999 Uttam Kumaran: So what we’re gonna start with is basically everybody going in and creating posted notes with topics or ideas or concerns or pain points that we have around these 4 areas. I would break up our work into these 4 parts of the stack.
107 00:19:59.740 ⇒ 00:20:06.330 Uttam Kumaran: and I’ll sort of walk through. So data. Engineering is everything related to data coming into the warehouse governance
108 00:20:06.700 ⇒ 00:20:11.290 Uttam Kumaran: our pipelines. More about our platform like how developers work
109 00:20:11.680 ⇒ 00:20:40.350 Uttam Kumaran: data modeling is everything around. Dbt, writing sequel, creating data models, creating data marts. Dbt, test things like that. Analysis is around, you know, tableau, any of our bi tools, collecting analysis requirements, executing analysis things around process, you know, like things like when Robert mentioned. Hey? Sending looms associated with dashboards any sort of thing like that. And strategy is really the highest level which is, companies sometimes come to us and say, we want to make more money.
110 00:20:40.760 ⇒ 00:20:44.240 Uttam Kumaran: And our job is to think about how we do that with data.
111 00:20:44.460 ⇒ 00:21:05.450 Uttam Kumaran: And so there may be things on the strategy side. When it comes to a particular client. There may be things on the strategy side when it comes to us. That you can basically put there. If it’s an open ended question or more of like a a larger principal question, we can put it there. So yeah, I’m just gonna sort of if if everyone could just copy a few more post its, and we can make
112 00:21:05.620 ⇒ 00:21:08.443 Uttam Kumaran: just a bunch of these. And basically you can just go.
113 00:21:08.980 ⇒ 00:21:13.479 Uttam Kumaran: you can edit these and what we’re gonna start with is basically I’m gonna start with.
114 00:21:13.930 ⇒ 00:21:16.489 Uttam Kumaran: I’ll start with 6 min.
115 00:21:16.630 ⇒ 00:21:27.521 Uttam Kumaran: And we basically can just each take time and create, post its about topics. And then, once that time is up, we’ll each go through and vote.
116 00:21:28.120 ⇒ 00:21:34.229 Uttam Kumaran: I think everybody can probably get like, let’s, we’ll just start with like 3 votes, and we just vote for the ones that that we like.
117 00:21:34.300 ⇒ 00:21:44.709 Uttam Kumaran: And then after that, we’ll go and prioritize what’s possible. Right? So we’ll talk both about these this axes on feasibility and priority.
118 00:21:44.995 ⇒ 00:22:07.785 Uttam Kumaran: And then that’ll give us a sense of like what we want to work on as a team for the next few weeks. So we’ll try to run this every week ideally. But think of this partly as like in a way to as like a therapy session to get everything out that we could be doing better better as a team, but also think through positives. Right? This could be things that we’re doing really. Well, this could be things about
119 00:22:08.310 ⇒ 00:22:15.600 Uttam Kumaran: processes that we want to double down on so yeah, any questions on that.
120 00:22:18.140 ⇒ 00:22:20.230 Uttam Kumaran: any questions on how to use figma.
121 00:22:21.580 ⇒ 00:22:23.969 Uttam Kumaran: I think everybody should be familiar by this point.
122 00:22:25.710 ⇒ 00:22:28.750 Uttam Kumaran: Okay, cool. So I’m gonna start a timer,
123 00:22:29.240 ⇒ 00:22:35.830 Uttam Kumaran: And yeah, I feel I think everybody is here. So let’s go ahead. And I’m just gonna start a 6 min timer, and then
124 00:22:36.220 ⇒ 00:22:41.619 Uttam Kumaran: about a minute to go. I’ll just make sure everybody is ready. So okay, cool.
125 00:27:52.881 ⇒ 00:27:56.820 Uttam Kumaran: We have 1 min left. I’m gonna add another minute, because I feel like
126 00:27:57.320 ⇒ 00:28:00.260 Uttam Kumaran: like people to get it took people a sec to get in the groove.
127 00:28:01.470 ⇒ 00:28:09.510 Uttam Kumaran: So keep going, please, and keep adding like as much stuff as you can. Even if we don’t get everything, we will keep this for future meetings. So
128 00:29:42.850 ⇒ 00:29:46.550 Uttam Kumaran: okay, how does everyone feel good?
129 00:29:47.240 ⇒ 00:29:48.580 Uttam Kumaran: Want some more time.
130 00:29:54.050 ⇒ 00:29:56.569 Uttam Kumaran: Can I get a thumbs down for more time?
131 00:29:59.220 ⇒ 00:30:00.810 Uttam Kumaran: Okay, cool.
132 00:30:01.421 ⇒ 00:30:04.309 Uttam Kumaran: Alright great. So this next step.
133 00:30:04.956 ⇒ 00:30:08.610 Uttam Kumaran: and I will. Just I’m just gonna share
134 00:30:10.380 ⇒ 00:30:14.520 Uttam Kumaran: my screen and for this next step. We’re gonna have everyone vote
135 00:30:15.010 ⇒ 00:30:19.329 Uttam Kumaran: and I will share how to do that like a new browser.
136 00:30:20.840 ⇒ 00:30:35.820 Uttam Kumaran: So what you’ll see here is you’ll see the sticker and you’ll see your your face, or whatever your icon is ideally. We want to use that, or you can use a star. I think.
137 00:30:36.010 ⇒ 00:30:39.930 Uttam Kumaran: given. We have, like, probably around like
138 00:30:40.270 ⇒ 00:30:44.450 Uttam Kumaran: 20 or so. Maybe we each get 5 votes.
139 00:30:45.019 ⇒ 00:30:59.080 Uttam Kumaran: And what you can go through is vote on the topics that are most important to you. And ideally, there’s a bunch of us on this call. So we will sort of focus in on key themes. So go ahead. Take a minute. You have 5 votes.
140 00:30:59.360 ⇒ 00:31:03.049 Uttam Kumaran: You don’t have to use all of them, but don’t go higher.
141 00:31:05.950 ⇒ 00:31:09.689 Uttam Kumaran: and we could talk. If if your topic doesn’t get us, we can still talk about it. But.
142 00:31:30.970 ⇒ 00:31:32.478 Luke Daque: Hi, guys, sorry I’m late.
143 00:31:32.920 ⇒ 00:31:35.579 Luke Daque: Can you send me the Link Bhutan to the.
144 00:31:35.580 ⇒ 00:31:36.180 Uttam Kumaran: Yes.
145 00:31:36.180 ⇒ 00:31:36.970 Luke Daque: Can avoid.
146 00:31:37.430 ⇒ 00:31:38.420 Uttam Kumaran: I guess
147 00:31:47.990 ⇒ 00:31:48.980 Uttam Kumaran: it’s in the zoom chat.
148 00:31:52.890 ⇒ 00:31:55.170 Uttam Kumaran: This is hard. I only get 5 votes.
149 00:31:55.620 ⇒ 00:31:58.280 Uttam Kumaran: Damn, yeah, I’m gonna.
150 00:32:00.250 ⇒ 00:32:01.870 Luke Daque: Are we like voting now?
151 00:32:02.230 ⇒ 00:32:03.740 Uttam Kumaran: Yes, yes.
152 00:32:09.670 ⇒ 00:32:16.270 Uttam Kumaran: we’ll start with the ones that have the highest votes, and then we have more time in this meeting, so we can probably get to a lot of stuff.
153 00:32:16.270 ⇒ 00:32:18.300 Sahana Asokan: How did you create that sticker.
154 00:32:19.434 ⇒ 00:32:23.449 Uttam Kumaran: Right here. Oh, wait. Oh, yeah, it’s it’s at the bottom here.
155 00:32:27.280 ⇒ 00:32:28.090 Sahana Asokan: Okay.
156 00:32:29.000 ⇒ 00:32:29.780 Uttam Kumaran: You got it.
157 00:32:31.840 ⇒ 00:32:34.510 Uttam Kumaran: If you press EI think you’ll open the stamp menu.
158 00:32:36.780 ⇒ 00:32:37.950 Sahana Asokan: Okay, got it?
159 00:32:40.270 ⇒ 00:32:41.779 Luke Daque: How many votes do we get.
160 00:32:43.040 ⇒ 00:32:43.830 Uttam Kumaran: 5.
161 00:32:48.110 ⇒ 00:32:49.020 Luke Daque: Okay. Cool.
162 00:32:52.170 ⇒ 00:32:56.350 Uttam Kumaran: I don’t know how much. How many times did I vote? 1, 2, 3, 4. Can I go? One more
163 00:33:05.550 ⇒ 00:33:12.189 Uttam Kumaran: now? I’m hedging my vote for stuff that got votes. I’m not. I’m, gonna i’m, like, okay, should I be the tie break or
164 00:33:12.890 ⇒ 00:33:14.829 Uttam Kumaran: which county needs me, most
165 00:33:32.470 ⇒ 00:33:35.199 Uttam Kumaran: cool meeting structures nice. That’s me.
166 00:33:39.850 ⇒ 00:33:40.720 Uttam Kumaran: Okay.
167 00:33:44.390 ⇒ 00:33:51.279 Uttam Kumaran: Alright, how do we feel, guys? Everyone voted feel good.
168 00:33:53.600 ⇒ 00:33:58.216 Uttam Kumaran: I love this. I love big jam, too. I’m spending a lot of time big jam these days, and
169 00:33:59.370 ⇒ 00:34:02.020 Uttam Kumaran: it’s great, although I don’t know what these are. Dude.
170 00:34:04.540 ⇒ 00:34:05.050 Uttam Kumaran: Okay.
171 00:34:05.280 ⇒ 00:34:08.500 Payas Parab (TikTok): Was just me trying. I I trying to figure out how to do that.
172 00:34:08.500 ⇒ 00:34:13.510 Uttam Kumaran: Are you? Just gonna we’re gonna find some extra votes like just off to the side somewhere. I’m getting nervous.
173 00:34:16.510 ⇒ 00:34:28.499 Uttam Kumaran: Okay, let me move everything into frame. And then let’s let’s talk. And this is also meant to be okay. So this next piece is definitely meant to be an open discussion. I really don’t want to have to do the talk for the next half hour.
174 00:34:28.690 ⇒ 00:34:33.277 Uttam Kumaran: I will. I will just stop talking, so then it’ll get really awkward.
175 00:34:33.870 ⇒ 00:34:38.580 Uttam Kumaran: What I want to do next is sort of
176 00:34:38.889 ⇒ 00:34:45.069 Uttam Kumaran: start to group things and start with the the most starred items.
177 00:34:45.517 ⇒ 00:34:50.400 Uttam Kumaran: Which I feel like we have a fair bit of those, and I’m just gonna move them.
178 00:34:51.061 ⇒ 00:34:55.000 Uttam Kumaran: I’m just gonna go over them. And whoever wrote them, if you wanna just
179 00:34:55.179 ⇒ 00:35:07.400 Uttam Kumaran: give the sort of 15 second elevator pitch on it. That way. We can all make sure we know what we’re talking about, and then I will start to move these to the, to the board. So
180 00:35:07.590 ⇒ 00:35:11.920 Uttam Kumaran: I’ll start with to the at the bottom. Is everyone happy with our meeting structures?
181 00:35:12.379 ⇒ 00:35:20.070 Uttam Kumaran: Yeah. So this one was me. I have changed a lot of stuff in the meetings over the past 3 weeks because
182 00:35:20.260 ⇒ 00:35:37.310 Uttam Kumaran: we’ve had, like both mo more people join. We’ve had more clients. We’re getting more structured. I just want to know if if everyone’s okay with it, we are dealing with a couple of challenges. Time zone challenges part time challenges different role challenges multiple clients. So
183 00:35:37.580 ⇒ 00:35:39.260 Uttam Kumaran: I just wanted to make sure that
184 00:35:40.408 ⇒ 00:35:48.949 Uttam Kumaran: people are okay with this, does anyone else have any comments here? We can talk about? How do we fix this later? But any other? Anyone want to add anything to the problem.
185 00:35:52.940 ⇒ 00:35:55.074 Caio Velasco: Well, I voted because I’m happy.
186 00:35:55.780 ⇒ 00:35:57.226 Caio Velasco: Okay, okay.
187 00:35:59.979 ⇒ 00:36:24.820 Uttam Kumaran: Can ae team members also take on dashboard analyst analysis tasks. Yeah, I I also I want us to sort of think about the analysis analyst role and ae role sort of overlapping more. And my question for our team is like, can ae take on more? And similarly, can can analysts sort of fish themselves that create new Dvt models if they need to. So that’s the topic there.
188 00:36:26.410 ⇒ 00:36:31.470 Uttam Kumaran: These 2 got 2 stars. Notion has a lot of information.
189 00:36:31.610 ⇒ 00:36:35.759 Uttam Kumaran: Yes, you’re right. We this is a problem right now.
190 00:36:36.416 ⇒ 00:36:45.859 Uttam Kumaran: And then, how do we build? I love this one. I I would have put all my votes here. This is, how do we build a strategic relationship opposed to a dashboard relationship?
191 00:36:46.060 ⇒ 00:36:48.550 Uttam Kumaran: I think this is a great question.
192 00:36:51.500 ⇒ 00:36:52.300 Uttam Kumaran: Cool.
193 00:36:52.900 ⇒ 00:36:55.439 Uttam Kumaran: Let’s move on to here. So
194 00:36:55.830 ⇒ 00:37:01.370 Uttam Kumaran: 2 is alignments on mock ups and data. I assume this is sort of the top
195 00:37:01.550 ⇒ 00:37:13.369 Uttam Kumaran: funnel of, like the project requirements gathering, which is, how do dashboard mockups move into the state where we can match metrics from our data, from our data mark to that. This makes a lot of sense.
196 00:37:15.730 ⇒ 00:37:18.210 Uttam Kumaran: And then, Bo, did you want to talk about this.
197 00:37:22.480 ⇒ 00:37:27.567 Bo Yoon: Yeah, I mean, I just wanted to get clear on
198 00:37:28.260 ⇒ 00:37:32.760 Bo Yoon: which project is the most urgent for like for every day.
199 00:37:33.300 ⇒ 00:37:34.420 Bo Yoon: So so.
200 00:37:34.420 ⇒ 00:37:48.359 Payas Parab (TikTok): Are you? Are you thinking cross platform, or is it like within a certain client? Is it like, okay for one client trying to figure out which thing should we prioritize, or is it like, I have several projects, and I’m like, I don’t know what the fuck’s the most important. I’m just curious.
201 00:37:48.840 ⇒ 00:37:51.450 Bo Yoon: Yeah, across all the crime. All the clients actually.
202 00:37:51.450 ⇒ 00:37:52.419 Payas Parab (TikTok): Got it. Okay.
203 00:37:56.910 ⇒ 00:37:58.050 Uttam Kumaran: That’s really great.
204 00:37:59.000 ⇒ 00:38:01.799 Uttam Kumaran: On the data modeling side. It looks like,
205 00:38:02.570 ⇒ 00:38:09.242 Uttam Kumaran: yeah. So this one is, I really want us to work on testing.
206 00:38:10.410 ⇒ 00:38:15.390 Uttam Kumaran: I think we are having to do a lot of counts every time we push stuff.
207 00:38:15.510 ⇒ 00:38:19.069 Uttam Kumaran: And I want to start to have the machine do that for us
208 00:38:19.260 ⇒ 00:38:24.520 Uttam Kumaran: ultimately. I think Eden is a really good place to start a waste. You’re probably the most
209 00:38:26.320 ⇒ 00:38:41.659 Uttam Kumaran: prime to actually take this on for Eden. But we can talk about that. And I think I wanna we we tried to do this early on. We just didn’t have enough capacity. I think now, we want to. As we push out data models in March, we layer on testing as part of our development process. So we can talk about that?
210 00:38:43.068 ⇒ 00:38:52.819 Uttam Kumaran: Great. And then on data engineering. Yeah, there was a couple of things on cleaning up. This is heard. And then, yeah, sequel Fluff on a repo level.
211 00:38:53.320 ⇒ 00:38:56.749 Uttam Kumaran: I am a big fan of this. This is on my to do list.
212 00:38:56.980 ⇒ 00:38:58.609 Uttam Kumaran: I just need, like a day
213 00:38:58.900 ⇒ 00:39:06.480 Uttam Kumaran: to go learn everything and add this to every repo. But this is her okay, cool. So let me move some of these to this area.
214 00:39:06.985 ⇒ 00:39:10.234 Uttam Kumaran: Especially the one. But we’ll start with the ones that got
215 00:39:11.700 ⇒ 00:39:15.239 Uttam Kumaran: the most votes. And then we can start to kind of group these.
216 00:39:17.620 ⇒ 00:39:23.500 Uttam Kumaran: also I can. I can. Probably I can just spotlight myself, too. If you guys want to follow me and
217 00:39:24.040 ⇒ 00:39:26.560 Uttam Kumaran: or you can watch the shared screen.
218 00:39:28.250 ⇒ 00:39:30.810 Uttam Kumaran: go on. Let me move these.
219 00:39:33.070 ⇒ 00:39:37.520 Payas Parab (TikTok): They really thought of everything with this product, with the spotlight feature like it’s like they like knew.
220 00:39:37.520 ⇒ 00:39:38.940 Uttam Kumaran: Dude. This is a great product.
221 00:39:38.940 ⇒ 00:39:40.679 Payas Parab (TikTok): It’s crazy! How well they thought of it!
222 00:39:40.680 ⇒ 00:39:47.510 Uttam Kumaran: This is the best. This is like one of the best products we use internally like, and I don’t think it’s very common, for.
223 00:39:48.140 ⇒ 00:39:52.030 Uttam Kumaran: like companies like ours to use this. And it’s a shame because.
224 00:39:52.830 ⇒ 00:39:59.819 Uttam Kumaran: like design designers like this, this is basically just like whiteboarding. And it’s like the best whiteboard product that exists.
225 00:40:02.800 ⇒ 00:40:08.829 Uttam Kumaran: And they and this is like their side project like to versus the actual product. So
226 00:40:09.120 ⇒ 00:40:14.400 Uttam Kumaran: okay, great. So I think now, what I’m gonna start to do is just look at
227 00:40:14.835 ⇒ 00:40:24.260 Uttam Kumaran: if there are other sort of tickets that are related to these that we can sort of group, and then we can begin to prioritize. So I saw a couple on like cleanup
228 00:40:24.420 ⇒ 00:40:26.020 Uttam Kumaran: that I’m gonna move here.
229 00:40:26.812 ⇒ 00:40:29.500 Uttam Kumaran: Which is this one?
230 00:40:31.416 ⇒ 00:40:38.490 Uttam Kumaran: There was this one, this one.
231 00:40:39.040 ⇒ 00:40:44.920 Uttam Kumaran: this one. Okay. Cool. Lots of cleanup.
232 00:40:47.142 ⇒ 00:40:49.309 Uttam Kumaran: Very satisfying work.
233 00:40:49.980 ⇒ 00:40:54.159 Uttam Kumaran: Okay, that’s sort of all. Here.
234 00:40:56.830 ⇒ 00:40:59.050 Uttam Kumaran: Try to bring things to the front. Okay?
235 00:40:59.200 ⇒ 00:41:05.460 Uttam Kumaran: And then this one is, can Aet members also take on dashboarding tasks. I don’t think there was
236 00:41:06.010 ⇒ 00:41:10.270 Uttam Kumaran: any other ones related to this.
237 00:41:10.930 ⇒ 00:41:14.720 Uttam Kumaran: Oh, okay.
238 00:41:15.354 ⇒ 00:41:21.889 Uttam Kumaran: then there is meeting structures. Okay, that that’s probably the only one prioritize the most urgent project.
239 00:41:22.080 ⇒ 00:41:29.795 Uttam Kumaran: Don’t think there was anything related to there.
240 00:41:32.060 ⇒ 00:41:37.839 Uttam Kumaran: alignment on mockups and data. Okay, strategy testing strategic relationship. Good notion.
241 00:41:38.510 ⇒ 00:41:44.690 Uttam Kumaran: Okay, I’m gonna leave there. And then I’m gonna move a couple really to the strategic relationship stuff. Which is this.
242 00:41:45.590 ⇒ 00:41:46.610 Uttam Kumaran: this?
243 00:41:51.970 ⇒ 00:41:53.940 Uttam Kumaran: According to this, there
244 00:42:00.580 ⇒ 00:42:02.610 Uttam Kumaran: anything else that?
245 00:42:03.290 ⇒ 00:42:06.309 Uttam Kumaran: Yeah, this is probably similar to this.
246 00:42:10.730 ⇒ 00:42:15.120 Uttam Kumaran: this one, this one.
247 00:42:17.370 ⇒ 00:42:21.670 Uttam Kumaran: These are all related to like dashboard, ae, analysts like handoff stuff.
248 00:42:23.580 ⇒ 00:42:28.779 Uttam Kumaran: Okay, this is great.
249 00:42:29.330 ⇒ 00:42:31.039 Uttam Kumaran: And then last one.
250 00:42:34.634 ⇒ 00:42:52.259 Uttam Kumaran: Okay, I’m gonna yeah. This is a great one. I love this one. I’m I’m building like a ton of templates right on fig jam. So I think we can have one that looks really really good. And it’s also like really presentable. We’ll have the design team work on something like this. Okay, great. So.
251 00:42:54.120 ⇒ 00:43:01.449 Uttam Kumaran: yeah, I guess the next piece is, I sort of want to open it up to how we want to think about like prioritization for these items.
252 00:43:03.080 ⇒ 00:43:06.970 Uttam Kumaran: Does anyone want to start like? And I’ll just again we have.
253 00:43:07.290 ⇒ 00:43:10.110 Uttam Kumaran: how do we get people to work more cross functionally?
254 00:43:10.580 ⇒ 00:43:14.050 Uttam Kumaran: Notion, cleanup, strategic relationship?
255 00:43:16.210 ⇒ 00:43:21.760 Uttam Kumaran: How do we do? The Ae analyst handoff cleanup meeting structure.
256 00:43:21.950 ⇒ 00:43:23.470 Uttam Kumaran: Prioritization.
257 00:43:24.300 ⇒ 00:43:25.420 Uttam Kumaran: Fantastic.
258 00:43:27.187 ⇒ 00:43:35.699 Uttam Kumaran: I feel like these 2 are really good place to start. Does anyone want to like add any comments to this? I think the floor is everybody’s, and then we can work on.
259 00:43:36.890 ⇒ 00:43:39.000 Uttam Kumaran: Wait. What? What actually we can do here?
260 00:43:44.250 ⇒ 00:43:48.000 Uttam Kumaran: Maybe Sahana, awaish or Kyle.
261 00:43:52.930 ⇒ 00:43:58.900 Payas Parab (TikTok): Is there like a world in which for, like these like, how do we hand things off? I feel like everyone has their own
262 00:43:59.170 ⇒ 00:44:12.090 Payas Parab (TikTok): style for these things right? And I think it’s sort of like it’s just like every person is like, Hey, this is how I think we should like organize all the stuff between a and a like. Everyone has different styles. So I feel like there’s sort of like a
263 00:44:12.560 ⇒ 00:44:20.110 Payas Parab (TikTok): like, how can we learn each other’s styles, and like what’s the best format for everyone and like rather than otherwise, what happens is like.
264 00:44:20.240 ⇒ 00:44:28.490 Payas Parab (TikTok): I think we should do it this way. Someone else thinks we should do it that way. And like they’re all valid ways. It’s just like everyone sort of has a different style of working. So I don’t know.
265 00:44:28.490 ⇒ 00:44:36.729 Uttam Kumaran: Yeah, can we? Can we talk about like? So this is, I’ll I’ll just set the stage, because this is sort of our current best method of solving.
266 00:44:36.730 ⇒ 00:44:37.080 Payas Parab (TikTok): Yeah.
267 00:44:37.080 ⇒ 00:44:39.150 Uttam Kumaran: Process which is
268 00:44:39.600 ⇒ 00:44:46.580 Uttam Kumaran: having this. Basically, I think this is the probably the place to look at, which is, we have a given dashboard we’re working on.
269 00:44:47.060 ⇒ 00:44:59.709 Uttam Kumaran: We have the tickets related to the business questions, and then what what the analyst needs in terms of the metric name. The Ae. Team then goes on and says, cool, here’s like, Here’s
270 00:44:59.950 ⇒ 00:45:01.600 Uttam Kumaran: where you can go get it.
271 00:45:01.740 ⇒ 00:45:06.959 Uttam Kumaran: And for our context, we also have a little bit of info on like where it’s coming from.
272 00:45:08.290 ⇒ 00:45:17.750 Uttam Kumaran: I guess my question is to pious Bo Sahana like, Is this seem like a good place? We haven’t rolled this out across like all clients.
273 00:45:18.508 ⇒ 00:45:22.780 Uttam Kumaran: Not for any reason. Apart from just time, like.
274 00:45:22.780 ⇒ 00:45:42.950 Payas Parab (TikTok): I think this is a step. I think this is the best one we’ve had so far. I just like, I don’t think it’s like all the way there, I like, it’s just like it’s 1 of those things where it’s like putting together the requirements. And then like also looking at the data tables and like also reviewing. Sometimes I just like review the Github code myself to be like, Oh, like, why is that not coming out right? I
275 00:45:43.470 ⇒ 00:46:06.039 Payas Parab (TikTok): like. I’ve made Github tickets. I’ve done like, you know, other stuff. We have the tickets in notion. We sort of have like a text like written version of this sometimes, or you’re like, I’m on the go. But I want to get the requirements in someone’s hands. So Boomer Core at writes an email right. And so like I don’t know like this is the best one I had. But like updating a spreadsheet also is like it’s it’s kind of not like
276 00:46:06.720 ⇒ 00:46:10.409 Payas Parab (TikTok): like I have to be like. You know what I mean, like you have to be like in the right zone to kind of like.
277 00:46:10.410 ⇒ 00:46:10.810 Uttam Kumaran: Yes.
278 00:46:10.810 ⇒ 00:46:18.690 Payas Parab (TikTok): Things tag the ticket like it’s it’s literally the best I’ve seen so far. But I I still think there’s room to make it better. And I it’s like it’s kind of an open call
279 00:46:18.850 ⇒ 00:46:21.440 Payas Parab (TikTok): to everyone how we do that.
280 00:46:21.440 ⇒ 00:46:27.740 Uttam Kumaran: Okay, Sahana, Bo, do you guys have any thoughts on this.
281 00:46:27.740 ⇒ 00:46:31.509 Sahana Asokan: Yeah, I agree with Pius, like, I think it’s
282 00:46:31.620 ⇒ 00:46:36.570 Sahana Asokan: like better than what we currently have. I just don’t know if it’s gonna solve all the problems.
283 00:46:38.720 ⇒ 00:46:40.469 Bo Yoon: Yeah, I agree as well.
284 00:46:41.010 ⇒ 00:46:41.680 Uttam Kumaran: Okay.
285 00:46:42.250 ⇒ 00:46:54.890 Uttam Kumaran: yeah, I all of those methods are like, insignificant to me. Email, blah, blah, actually, frankly, for most of our clients, we’re handling like 5 things. Right? We’re hiding like 3 to 5, like
286 00:46:55.020 ⇒ 00:46:56.220 Uttam Kumaran: deliverables.
287 00:46:56.480 ⇒ 00:47:00.449 Uttam Kumaran: We went really, Od on like notion.
288 00:47:00.670 ⇒ 00:47:16.200 Uttam Kumaran: And I think it like, did okay when we when it was like a couple of us, and we had like 100 tickets. Now, it’s sort of hurting us like there’s it’s just like way too crazy. In fact, for this whole week we ran everything, not in notion, and we crushed it this week like it was the best week we’ve had. So
289 00:47:16.560 ⇒ 00:47:44.070 Uttam Kumaran: I actually am like, and I’ve always been like less interested in like figuring out the best Pm. Tool. I. The reason I like this process is because it brings in the context that the analysts have, and then it brings in the context that the Aes have. And then you can. This is where the discussion happens right like, for example, though, you’re like, Okay, I got age. But then the age thing, there’s some ages that come in as numbers. Some come in. Still as a year. Then I’m like, Okay, I gotta go fix that. I gotta go fix some reject somewhere.
290 00:47:44.120 ⇒ 00:47:49.660 Uttam Kumaran: That conversation can either happen in slack, or here, I think that’s fine.
291 00:47:50.700 ⇒ 00:47:51.210 Uttam Kumaran: More of.
292 00:47:51.210 ⇒ 00:48:04.349 Payas Parab (TikTok): I think it’s good that it doesn’t happen in slack, right slack stuff gets lost. I I that’s my! That’s my I don’t mind slack like. I don’t mind it, but I know, like some people don’t like my like 8 page messages that are like what the fuck do. I do with this on top.
293 00:48:04.350 ⇒ 00:48:06.229 Uttam Kumaran: Yeah, I don’t like it. I don’t like that.
294 00:48:06.590 ⇒ 00:48:07.050 Uttam Kumaran: Yeah.
295 00:48:07.392 ⇒ 00:48:11.850 Uttam Kumaran: Cause I’m like, it’s immediate, like one like nobody’s gonna read it.
296 00:48:11.850 ⇒ 00:48:12.250 Payas Parab (TikTok): No.
297 00:48:12.250 ⇒ 00:48:14.279 Uttam Kumaran: Kind of has to get sent somewhere.
298 00:48:14.610 ⇒ 00:48:15.899 Payas Parab (TikTok): That’s what I mean that like that.
299 00:48:15.900 ⇒ 00:48:16.620 Uttam Kumaran: Oh, yeah.
300 00:48:16.620 ⇒ 00:48:19.710 Payas Parab (TikTok): Yeah, I exactly so like, but like.
301 00:48:20.650 ⇒ 00:48:46.909 Payas Parab (TikTok): like updating us, like, sometimes, it’s just like, easy to like flow. I’m like, Okay, cool. This is what needs to get done, or it’s like a quick like. If if let’s say, there’s like a quick question that’s like super urgent, then like, if you’re going in that spreadsheet. There’s like 8 like cells on that specific dashboard that are like, here are all my outstanding questions which are amazing questions, just to like. You know what I mean? It’s good for ae to be asking questions, but it’s like, then I’m sitting there like now. It’s like 2030 min of my time to like, go.
302 00:48:47.170 ⇒ 00:48:56.270 Payas Parab (TikTok): you know, review all of those things and like, and then update in a spreadsheet. And I have to be at my computer and I have to have like Snowflake open on the other tab. And it’s like.
303 00:48:56.390 ⇒ 00:49:10.990 Payas Parab (TikTok): for some reason it should be easier to quickly look at it with snowflake open and like, send a slack message. Right? Like, I’m literally typing on my phone like, okay, cool this table. This like, we need this extra thing, this thing, and then otherwise, I’m like going in and like.
304 00:49:11.360 ⇒ 00:49:16.579 Payas Parab (TikTok): or it’s like. And the slack message also doesn’t work right? So there’s like probably some happy medium. And I’m like.
305 00:49:16.700 ⇒ 00:49:20.320 Payas Parab (TikTok): maybe there’s a tool out there that’s kind of addressed this before.
306 00:49:20.740 ⇒ 00:49:26.489 Payas Parab (TikTok): If there isn’t, it’s like probably a tool we could make and sell like I’m I’m intrigued by that, too.
307 00:49:26.720 ⇒ 00:49:27.610 Uttam Kumaran: Okay.
308 00:49:28.000 ⇒ 00:49:36.750 Uttam Kumaran: so let’s talk about this. I mean, I think, Sahana, this is a great example, because we are literally gonna have to do this like this is a dashboard mock up that Sahana worked on.
309 00:49:36.910 ⇒ 00:49:47.000 Uttam Kumaran: This is sort of the top of the funnel where Sahana’s worked with the team to basically do the dashboard mock up for many of our dashboards that we’ve built. We haven’t had this, however.
310 00:49:47.330 ⇒ 00:50:04.989 Uttam Kumaran: for the analyst team. I think we will start having this as an expectation one. It it helps. There’s 2 things. One, it helps build, buy in from the team, from the stakeholder, from the client on like we’re building this dashboard. Let’s make sure we listen to everything you need versus kind of some of the stuff we did for Joby, which is just like
311 00:50:05.270 ⇒ 00:50:06.499 Uttam Kumaran: toss ever like.
312 00:50:06.650 ⇒ 00:50:11.620 Uttam Kumaran: oh, they have 5 overarching questions about Amazon. And then we’re basically like guessing at what the views are.
313 00:50:11.840 ⇒ 00:50:15.789 Uttam Kumaran: This is probably what we’re gonna move for towards but like
314 00:50:15.980 ⇒ 00:50:20.049 Uttam Kumaran: so to go from this to something that awaii can act on
315 00:50:20.550 ⇒ 00:50:24.420 Uttam Kumaran: like. That’s what I want to talk about, right? So I guess.
316 00:50:24.560 ⇒ 00:50:33.640 Uttam Kumaran: like, I think this is a good discussion we could probably have is like from this. It’s very clear that there are metrics. Sorry it’s a little blurry, but it’s clear that there’s metrics.
317 00:50:34.140 ⇒ 00:50:36.549 Uttam Kumaran: Is it best to then say, like, Okay, I
318 00:50:36.850 ⇒ 00:50:39.260 Uttam Kumaran: like, we could hand this to Awaii.
319 00:50:39.800 ⇒ 00:50:42.200 Uttam Kumaran: and then basically a waste can build this.
320 00:50:42.340 ⇒ 00:50:48.449 Uttam Kumaran: I still think it’s sometimes helpful to hear the list, to see the question list
321 00:50:48.570 ⇒ 00:50:51.170 Uttam Kumaran: and like, get a little bit of the business context.
322 00:50:51.840 ⇒ 00:50:57.710 Uttam Kumaran: But I don’t know. I think this is a great example of like something we should just walk through right now, like, how how are we gonna action on this like.
323 00:51:00.470 ⇒ 00:51:19.979 Sahana Asokan: Yeah, I think that’s a good point. But I do think like this, mock up. These mock up should be a requirement on the analytics end because it helps. You understand the business questions that are answered. And you can also kind of get an idea of how the data needs to be visualized, which probably helps you guys on the modeling
324 00:51:20.270 ⇒ 00:51:21.620 Sahana Asokan: side right?
325 00:51:23.100 ⇒ 00:51:26.510 Uttam Kumaran: Do you think that it’s like
326 00:51:27.050 ⇒ 00:51:30.950 Uttam Kumaran: 10 times more work, or like a little bit more work to go?
327 00:51:31.190 ⇒ 00:51:34.089 Uttam Kumaran: Do this, and then, I guess question for a wish.
328 00:51:34.290 ⇒ 00:51:36.239 Uttam Kumaran: Do you think we need this
329 00:51:36.640 ⇒ 00:51:38.579 Uttam Kumaran: get if we just have this asset.
330 00:51:38.980 ⇒ 00:51:51.410 Sahana Asokan: Yeah, I think it’s more of a I think, from a from my perspective, it probably would take me like an another 30 min to fill something like that out. I think it’s more on. Do you guys need it like, does it help you guys.
331 00:51:52.670 ⇒ 00:51:54.760 Awaish Kumar: Yeah, I think like sheet is.
332 00:51:55.380 ⇒ 00:52:03.009 Awaish Kumar: It is helpful it makes things at one place. And
333 00:52:03.220 ⇒ 00:52:08.139 Awaish Kumar: also there’s like description. Edit there. So, and, like
334 00:52:08.620 ⇒ 00:52:12.420 Awaish Kumar: all the exceptions or discrepancies like this, can be.
335 00:52:12.420 ⇒ 00:52:12.770 Uttam Kumaran: Yeah.
336 00:52:12.770 ⇒ 00:52:16.380 Awaish Kumar: Put in there. So it’s it’s more useful
337 00:52:16.860 ⇒ 00:52:19.020 Awaish Kumar: for us to go in. And
338 00:52:19.180 ⇒ 00:52:24.309 Awaish Kumar: if we know already, like what kind of data we are expecting, or things like that, it will be.
339 00:52:24.430 ⇒ 00:52:28.420 Awaish Kumar: oh, much easier, or like the
340 00:52:28.680 ⇒ 00:52:32.770 Awaish Kumar: much like it will be it will make us
341 00:52:33.446 ⇒ 00:52:38.440 Awaish Kumar: much more efficient in not making any errors in the data.
342 00:52:41.170 ⇒ 00:52:50.090 Uttam Kumaran: Yeah, I I tend to agree in that. I still think that this is valuable. Because, for example, if if we talk about Comp the definition of completed order.
343 00:52:50.300 ⇒ 00:52:52.779 Uttam Kumaran: If we go ahead and build a completed order.
344 00:52:52.990 ⇒ 00:52:58.050 Uttam Kumaran: I am guessing we will get a slack of like, hey? What’s what’s incompleted orders.
345 00:52:58.330 ⇒ 00:52:59.579 Sahana Asokan: Yeah, that’s fair.
346 00:52:59.810 ⇒ 00:53:10.470 Uttam Kumaran: Right. And it’s and that’s gonna happen, I think, for probably half the metrics like. And and I guess successful payments on all of these like, what if we? What if we go in and we find a 4? th
347 00:53:11.050 ⇒ 00:53:15.309 Uttam Kumaran: It’s like there’ll be sending centralize that conversation. So I think that.
348 00:53:15.590 ⇒ 00:53:19.500 Uttam Kumaran: for example, if one of these rows is like it’s literally
349 00:53:20.910 ⇒ 00:53:25.900 Uttam Kumaran: question, or it can cause one, it may be like, Tell me about like
350 00:53:26.130 ⇒ 00:53:43.700 Uttam Kumaran: it could be like, tell me about the order types that we have across these 4 things. And then we basically can go in here. Say, Okay, you cannot find it in dim orders. There is an order status flag. And then we can basically put some context from our end because we’re gonna go in and learn everything about
351 00:53:43.980 ⇒ 00:54:02.379 Uttam Kumaran: this whole process, and then we may find something that you you may not have known, and the business may not have even known. And then we sort of centralize the QA. Here, and the QA. Is a piece that, like Kyle really put together. I’ll make this like, don’t worry about the spreadsheet format. I’ll make this look really nice. But
352 00:54:02.670 ⇒ 00:54:09.449 Uttam Kumaran: I think that 30 min to do this, in addition to the mock up is basically it like, I don’t want us to do any more work than that.
353 00:54:11.040 ⇒ 00:54:15.619 Uttam Kumaran: But however, we don’t have this for several dashboards, and I think we want to start doing this.
354 00:54:16.144 ⇒ 00:54:23.709 Uttam Kumaran: And of course I think I’ll I’ll I’ll work on the design team getting you, and I’ll work with them to get you a good template format. That way. This.
355 00:54:23.920 ⇒ 00:54:26.529 Uttam Kumaran: hopefully, is easier to to build in the future.
356 00:54:26.800 ⇒ 00:54:37.290 Sahana Asokan: Yeah, I think that’s good. I actually agree with you, I think, in the like the excel sheet, or whatever I think, what we should also be doing as analytics. People is
357 00:54:37.640 ⇒ 00:54:41.989 Sahana Asokan: defining the metrics. So like, for example, to your point.
358 00:54:42.240 ⇒ 00:54:54.200 Sahana Asokan: I wouldn’t expect you guys to understand what a completed order is. It’s not just when an order is confirmed, it’s when it’s delivered to the customer. So I guess you guys would probably need all of those nuances.
359 00:54:54.300 ⇒ 00:54:59.089 Sahana Asokan: but I think to everyone’s point slack, everything gets kind of
360 00:54:59.850 ⇒ 00:55:02.240 Sahana Asokan: lost. So I think this is kind of like a.
361 00:55:03.730 ⇒ 00:55:08.419 Uttam Kumaran: Like. For example, if we, if we, if we go to like an example of something like.
362 00:55:09.090 ⇒ 00:55:11.240 Uttam Kumaran: I think this is a good example of like
363 00:55:12.090 ⇒ 00:55:17.949 Uttam Kumaran: I don’t know. I’m gonna try to pick on pious like.
364 00:55:17.950 ⇒ 00:55:19.020 Payas Parab (TikTok): Call.
365 00:55:20.100 ⇒ 00:55:31.010 Uttam Kumaran: I don’t know. Like, yeah, something where it’s like, hey, can we just go like, here’s I mean. But this is a good example of like something that came up yesterday, which is like, can we add product category? Can we add order, flag? Can we add total spent?
366 00:55:31.800 ⇒ 00:55:36.989 Uttam Kumaran: I went, and just did the 1st 2, the one and 3. Cause I was like, okay, I know where it is
367 00:55:37.760 ⇒ 00:55:43.750 Uttam Kumaran: for me. I’m kind of like, did that need to have gone through the excel process.
368 00:55:44.140 ⇒ 00:55:51.740 Uttam Kumaran: Maybe it’s on me to take in feedback this way, and then I can go update like that product category now exists. But
369 00:55:51.870 ⇒ 00:55:56.380 Uttam Kumaran: frankly, I don’t. I think also we would have solved many of these issues. Have we had a dashboard mockup
370 00:55:56.580 ⇒ 00:56:03.800 Uttam Kumaran: off Rep, you know, so I don’t know. We’ll sort of see some of these, but I overall do want to see our slack back and forth.
371 00:56:04.010 ⇒ 00:56:12.660 Uttam Kumaran: so to be reserved more for, like urgent like, okay, throw everything out. We need to do this by like 2 Pm. Or like existential, like
372 00:56:12.860 ⇒ 00:56:16.309 Uttam Kumaran: long form discussion about fields and things like that.
373 00:56:16.820 ⇒ 00:56:19.299 Uttam Kumaran: Otherwise, I do think this process is pretty good.
374 00:56:22.490 ⇒ 00:56:25.419 Uttam Kumaran: Okay, cool. If we’re all in agreement there, then, yeah, sorry. Go ahead.
375 00:56:26.650 ⇒ 00:56:28.410 Sahana Asokan: I was gonna say, go ahead.
376 00:56:29.466 ⇒ 00:56:30.900 Caio Velasco: Go ahead.
377 00:56:33.510 ⇒ 00:56:47.299 Caio Velasco: So I was just gonna say that oh, since I started like not long ago, like 2 weeks ago and then, for example, when I started with this idea of building gorgeous dashboard and helping
378 00:56:47.300 ⇒ 00:57:06.160 Caio Velasco: well build the models and everything. The 1st thing the 1st question I had was. What is happening here? What is gorgeous? What is what is a macro? So at the end of the day, when I, for example, started feeling this spreadsheet. And then there was another another tab. I think I called entity
379 00:57:06.280 ⇒ 00:57:11.780 Caio Velasco: definition, or something was more like to guide myself on learning about it.
380 00:57:12.233 ⇒ 00:57:20.340 Caio Velasco: Then I don’t know. Like, what is the boundary in terms of do we need this, or do we need to do a little bit more on on this side or not.
381 00:57:20.680 ⇒ 00:57:27.109 Caio Velasco: but at least when I started without it, I was feeling a bit lost in organizing my own work.
382 00:57:27.250 ⇒ 00:57:32.140 Caio Velasco: So if somehow this can help set this this
383 00:57:32.660 ⇒ 00:57:49.469 Caio Velasco: connection between analysts and us. For example, should I be putting effort into into understanding really like going to Gordon’s website and understand, what is a macro? What is the definition of it? Or or does does it need to come from analyst that maybe they have more knowledge about it. So
384 00:57:49.580 ⇒ 00:57:51.489 Caio Velasco: I just wanted to add this comment.
385 00:57:53.320 ⇒ 00:57:53.890 Uttam Kumaran: Okay.
386 00:57:54.550 ⇒ 00:58:04.310 Uttam Kumaran: okay, I think the action here is is pretty clear. So I feel good about a resolution. I think we will. This will cause us to in on initially. This will slow things down.
387 00:58:04.855 ⇒ 00:58:13.140 Uttam Kumaran: Right? Because we will start to have to get mockups. However, our job is to explain to the client. Why, this actually will end up saving them iteration cycles.
388 00:58:13.550 ⇒ 00:58:32.399 Uttam Kumaran: because the reason why we spent 3 weeks on 2 dashboards for Job is we didn’t have this and nobody. We didn’t know what we needed to build. They didn’t know what they wanted. And so we sort of like, we’re doing this. And this is a classic data. Pro, this is like, top top 5 classic issues and data is.
389 00:58:32.650 ⇒ 00:58:40.110 Uttam Kumaran: Oh, I need this thing to be different. I need this thing. It’s not agreeing on the requirements at a time, and setting some sort of boundary. So this is
390 00:58:40.360 ⇒ 00:58:49.454 Uttam Kumaran: this is great. I know we have a few minutes more minutes left. But I think this is a huge rock that we move forward. Let’s talk a little bit about.
391 00:58:52.190 ⇒ 00:58:54.470 Uttam Kumaran: this one. So yeah, clean up.
392 00:58:55.490 ⇒ 00:59:06.349 Uttam Kumaran: I mean, I agree. I just, I think, that this is on probably the A team just to set time and prioritize. We have naming conventions. We have ideas on this.
393 00:59:07.350 ⇒ 00:59:13.349 Uttam Kumaran: is that, does everyone understand? Like raw staging marts.
394 00:59:13.780 ⇒ 00:59:20.000 Uttam Kumaran: staging versus production, or like raw intermediate marks? Does everyone get that sort of those concepts.
395 00:59:24.780 ⇒ 00:59:29.059 Luke Daque: I suppose the Ae. Team does. But I’m not sure what they do.
396 00:59:29.440 ⇒ 00:59:31.390 Luke Daque: Analysts. Yeah, analysts.
397 00:59:33.020 ⇒ 00:59:36.200 Bo Yoon: Yeah, it’ll be good if you can explain the difference.
398 00:59:36.380 ⇒ 00:59:47.700 Uttam Kumaran: Great. So and this is probably something that’s worth us doing, even like a little write up on. We have technical write up on it. But basically we’re trying to solve 2 problems with the structure, one.
399 00:59:48.204 ⇒ 01:00:07.895 Uttam Kumaran: we have raw data that comes into the warehouse. We then have modeling that we do. That’s complicated joins business logic. And then we try to produce for the analyst team what’s called a data mark, which is extremely clean and easy. Understand dimension and fact tables, dimension table. You could think about like
400 01:00:08.510 ⇒ 01:00:28.859 Uttam Kumaran: like a dim customers, which is all the customers and dimensionality about them fact tables. You could think of something that has a time series like fact orders or fact transactions, fact tickets. Right? Which means there’s always tickets coming in. And so we build those 2 tables. Then the 3rd table type, we build summary tables where.
401 01:00:29.050 ⇒ 01:00:43.649 Uttam Kumaran: okay, commonly in in tableau, you may have to join 3 things together. You may have to join agents to tickets to Macros. We’re just gonna handle that and build you like a ticket summary table that has all that however, you can. Still, probably you can still get to that. With the building blocks.
402 01:00:43.900 ⇒ 01:00:56.959 Uttam Kumaran: The analyst team should be pulling everything from March right. So we particularly try to keep the logic. That’s like sort of messy in the intermediate layer. And then the reason between having dev staging and production is
403 01:00:57.360 ⇒ 01:01:03.669 Uttam Kumaran: as we develop stuff on the Ae side, we, we’re like testing code. And we need an environment to test code that doesn’t affect
404 01:01:03.950 ⇒ 01:01:04.770 Uttam Kumaran: production.
405 01:01:04.900 ⇒ 01:01:10.779 Uttam Kumaran: So we have a development area. And then we have production. Right? So staging, the reason for staging is when we push a Pr
406 01:01:10.930 ⇒ 01:01:21.690 Uttam Kumaran: that Pr actually gets run in a end to end staging environment. So we can make sure that when we push the code finally product to production, it doesn’t impact doesn’t have any unintended impacts.
407 01:01:22.575 ⇒ 01:01:36.320 Uttam Kumaran: And so that way, that that’s the reason why we have our own local environment in Dev, we have the staging environment. And then we have production. Ultimately, nobody should be able to touch production apart from like our Github actions.
408 01:01:36.886 ⇒ 01:01:42.089 Uttam Kumaran: And so that’s sort of the reason. Commonly companies have like 5 different environments. They’ll have dev
409 01:01:42.560 ⇒ 01:01:46.899 Uttam Kumaran: pre death staging pre prod pro like, I think we’re good with 3 for now.
410 01:01:48.760 ⇒ 01:01:54.350 Uttam Kumaran: that’s sort of the reasoning there. So I, if there’s are there any other comments on this? Apart from, we just need to do this soon.
411 01:01:59.530 ⇒ 01:02:07.189 Uttam Kumaran: If not, then heard on this I will move this, I’ll sit here.
412 01:02:07.720 ⇒ 01:02:09.140 Uttam Kumaran: This is very feasible.
413 01:02:10.319 ⇒ 01:02:11.000 Uttam Kumaran: Cool.
414 01:02:11.300 ⇒ 01:02:15.720 Uttam Kumaran: So that takes off the 2 big pieces. I think before we
415 01:02:16.000 ⇒ 01:02:22.139 Uttam Kumaran: log off today, I want to have 2 conversations, maybe spend like 2 min talking about
416 01:02:22.290 ⇒ 01:02:27.310 Uttam Kumaran: this item, which is, how do we build strategic relationships?
417 01:02:27.590 ⇒ 01:02:30.459 Uttam Kumaran: How do we get an overview of the currency appliance.
418 01:02:30.670 ⇒ 01:02:38.479 Uttam Kumaran: And how do we identify this? I think, for this piece? I honestly think people should expect this in our team meetings on
419 01:02:38.620 ⇒ 01:03:06.379 Uttam Kumaran: Monday, Friday. I think, Robert, you’re probably doing the best job at sort of giving us sort of pulse check on this. I don’t think it’s that helpful, and honestly, probably would lead to more stress if every day we talked about. If clients can renew. That’s like that is our lives. And I’m telling you it’s not like a great. It’s not like good for health to like sort of constantly. Think about that. But I do think it’s helpful on a weekly basis. Sort of get like, are we progressing? And are we growing?
420 01:03:06.880 ⇒ 01:03:09.869 Uttam Kumaran: Is that is everyone good with that like, does that make sense?
421 01:03:17.100 ⇒ 01:03:25.020 Uttam Kumaran: Okay, cool? And then any thoughts on like these 2 items. I know pies you put these down, but I think there’s pretty self explanatory.
422 01:03:25.650 ⇒ 01:03:31.959 Awaish Kumar: I think one of the thing which I shared initially when I joined
423 01:03:32.070 ⇒ 01:03:35.519 Awaish Kumar: about these strategic relationships is that
424 01:03:35.770 ⇒ 01:03:39.810 Awaish Kumar: like, we just don’t deliver the dashboard.
425 01:03:39.940 ⇒ 01:03:57.890 Awaish Kumar: Instead, we like, we figure out the answers to the most painful questions like, if, for example, the revenue is down today, what what are the reasons for that, and share those summaries on a daily basis
426 01:03:58.380 ⇒ 01:04:05.029 Awaish Kumar: something like that. So they don’t have to go in the dashboard and find answers to these questions themselves.
427 01:04:05.170 ⇒ 01:04:13.039 Awaish Kumar: Still, we are telling them, okay, your revenue is down today by 45, by 40%. For so and so reasons.
428 01:04:13.400 ⇒ 01:04:13.810 Uttam Kumaran: Yeah.
429 01:04:13.810 ⇒ 01:04:15.730 Awaish Kumar: Can now take these actions.
430 01:04:18.580 ⇒ 01:04:26.980 Uttam Kumaran: Yeah, I agree. I don’t know, Robert, do you have any ideas on this? I think we talked about like sort of doing weekly or Qbrs, where we’re actually moving from
431 01:04:27.260 ⇒ 01:04:33.510 Uttam Kumaran: being just dashboards. So like actually being like, Hey, we saw this. And here’s the action you should take.
432 01:04:34.910 ⇒ 01:04:38.900 Uttam Kumaran: I don’t know I’m open to like how we should change our process with clients to do that.
433 01:04:40.260 ⇒ 01:04:45.724 Robert Tseng: Yeah, I mean, I think we we do that with
434 01:04:46.990 ⇒ 01:04:50.599 Robert Tseng: at least, Javi and Eden. Like I, we have more like
435 01:04:50.710 ⇒ 01:05:04.300 Robert Tseng: roadmap and strategy check-ins weekly. But the problem is for all these clients we don’t have, like a regular, a fixed set of reports that we built for them that we just like we Weekly Monitor, and we tell them.
436 01:05:04.380 ⇒ 01:05:23.797 Robert Tseng: hey, like the it’s trending up or down. This is like, why and like, we don’t have that conversation like, that’s what the Weekly Business Review is supposed to be, for I did like kind of create a template for, like what we could do, how we could do that for Eden. It’s that Google sheet model I showed you yesterday. I think we could adopt something like that across our Ecom clients.
437 01:05:24.300 ⇒ 01:05:35.459 Robert Tseng: But yeah, I think when this was a problem, I think this is just a problem, for now that we have, we’re covering so much ground with some with our clients when it was just like
438 01:05:35.690 ⇒ 01:05:57.470 Robert Tseng: when I was just doing like mixed panel or amplitude engagements. That was a lot much easier, because it’s just like, here are the 3 dashboards you look at, and let’s just talk through what you’re seeing every week. And and I think that was easier to cover. So I think, yeah, we need to figure out like, what is what are the fixed sets of reports that we can walk through clients
439 01:05:57.470 ⇒ 01:06:14.420 Robert Tseng: every week. Just to like get them in the habit of reviewing their business regularly, because I think most of them are in a reactive state. They’re just like jumping at whatever seems to be on fire, and we need to be the ones to give them consistent consistency. And and looking at the trends.
440 01:06:16.350 ⇒ 01:06:24.569 Uttam Kumaran: Yeah, I I I totally agree. I also think we should make it clear to them that this is budget in terms of our time right like.
441 01:06:24.950 ⇒ 01:06:36.380 Uttam Kumaran: of course, like this has to come from somewhere, and and Sahana is working on a bunch of stuff for new dashboards. Bo is working on dashboard work. So where is the time coming from to actually do this analysis?
442 01:06:36.510 ⇒ 01:06:40.450 Uttam Kumaran: Like, I want to carve that out as scope in our roadmap.
443 01:06:41.014 ⇒ 01:06:44.669 Uttam Kumaran: So I think that’s something that we’re gonna have to understand is.
444 01:06:44.950 ⇒ 01:06:51.829 Uttam Kumaran: I think, dashboard work is gonna always be a thing that’s coming at us. But I do see this as a huge risk.
445 01:06:52.337 ⇒ 01:06:59.009 Uttam Kumaran: And we’ve seen this with clients in the past where we develop all these dashboards. But adoption is also our job?
446 01:06:59.733 ⇒ 01:07:04.429 Uttam Kumaran: And so how can we start to balance tasks coming in with the weekly business reviews
447 01:07:04.820 ⇒ 01:07:17.709 Uttam Kumaran: and like not overload the analyst team. So I think we’ll I think we’ll work on. We’re we’re trying this new process with Eden. We’ll see if we can roll this out to other clients. I’m I’m meeting with them on today to sort of do a version of this
448 01:07:18.447 ⇒ 01:07:22.019 Uttam Kumaran: but also again, I think they people hire us
449 01:07:22.130 ⇒ 01:07:29.519 Uttam Kumaran: uniquely, not just because we can get data work done. There are a lot of people. There are a fair amount of people that can do that.
450 01:07:29.640 ⇒ 01:07:35.100 Uttam Kumaran: but also to tell them, here’s what you should do, that there’s like not many companies that can do
451 01:07:35.527 ⇒ 01:07:53.960 Uttam Kumaran: and so that’s what sets us apart and like, I think we we should lean in there. Frankly, one of the things that we see across many clients is, as we understand their business. From the data side we become apart from like their CEO. We basically become one of the few people in the company that know everything about the company.
452 01:07:54.280 ⇒ 01:08:02.240 Uttam Kumaran: But we don’t. We don’t use that. Apart from just making dashboards. And so I think that we have a lot of leverage to do more
453 01:08:02.600 ⇒ 01:08:06.529 Uttam Kumaran: more there. So I think this is a great action item.
454 01:08:08.740 ⇒ 01:08:16.640 Uttam Kumaran: I have a bunch of notes here. But I’m just gonna move this. I think this is definitely high priority in terms of feasibility. We’ll see.
455 01:08:17.692 ⇒ 01:08:19.867 Uttam Kumaran: Yeah, I know we’re at time.
456 01:08:21.000 ⇒ 01:08:26.750 Uttam Kumaran: I I know. I think the the last pulse check question I’ll just have is like, how do we feel about the meetings.
457 01:08:27.201 ⇒ 01:08:32.079 Uttam Kumaran: I still like doing the roadmaps on Mondays. I think we may space those out as we get
458 01:08:32.390 ⇒ 01:08:35.069 Uttam Kumaran: more clarity about like at least 2 weeks worth of work.
459 01:08:35.330 ⇒ 01:08:47.560 Uttam Kumaran: Are we okay with like I, I just one thing I did did for next week is, I just combined the meetings into 1 45 min meeting. Originally they took up a lot of the time, and now I think we can cover almost everything we need to in that time.
460 01:08:47.819 ⇒ 01:08:49.830 Uttam Kumaran: Are we good with that for next week.
461 01:08:50.170 ⇒ 01:08:52.850 Uttam Kumaran: and are we good with Mondays? And this meeting.
462 01:08:58.550 ⇒ 01:09:02.669 Payas Parab (TikTok): Okay, I thought people were gonna be like, stop moving meetings. Blah! Blah!
463 01:09:02.670 ⇒ 01:09:20.289 Payas Parab (TikTok): I will. I will raise my hand if if no one else. I just like my own thing is like what there’s like a bunch of things on there. It sort of makes me like, okay, like, which ones are the most important to do and like, I think you’ve done a good job of like paying us of like, hey, are you joining this one? Because, like. Clearly, there’s something that’s like needed. I just like
464 01:09:21.100 ⇒ 01:09:27.539 Payas Parab (TikTok): there’s just a bunch right? And it sort of becomes this like which ones are the important ones to attend. If you’re trying to balance that, I just like
465 01:09:27.729 ⇒ 01:09:33.420 Payas Parab (TikTok): it’s like sort of just like I would just caution against like boy who? Cried Wolf with like, there’s like a lot of meetings. Then you’re kind of like, okay.
466 01:09:33.710 ⇒ 01:09:40.970 Payas Parab (TikTok): I’m not. Also, it’s not like a hundred percent clear. If it’s like, you absolutely need to come to this one, or you don’t need to come to you. Get what I’m saying like, it’s like.
467 01:09:40.979 ⇒ 01:09:43.239 Uttam Kumaran: I. Yeah, I also will say.
468 01:09:43.679 ⇒ 01:09:51.229 Uttam Kumaran: we are very like for folks on the data team. I don’t think we have. We are very meeting light like they’re maxed
469 01:09:51.529 ⇒ 01:09:53.039 Uttam Kumaran: 2 meetings a day.
470 01:09:53.249 ⇒ 01:09:58.189 Uttam Kumaran: So I will say that, like we don’t have like bullshit, we don’t have a lot of bullshit meetings.
471 01:09:59.024 ⇒ 01:10:09.399 Uttam Kumaran: Which I’m happy about. I think I think at minimum, I think it’s a requirement to come to the daily data meeting because we talk about anything.
472 01:10:09.400 ⇒ 01:10:09.740 Payas Parab (TikTok): Okay.
473 01:10:09.740 ⇒ 01:10:13.819 Uttam Kumaran: Get done in sync. We usually talk about there, so I will. I will push on that
474 01:10:13.990 ⇒ 01:10:32.729 Uttam Kumaran: I also have time to talk to the Aes every morning. That’s been really amazing, because we talk about sort of like platform things. And then the analyst team meeting I also have. Typically it’s me. Bo Sahana sometimes joins. Jacob, sometimes joins. That’s also great, because we sort of talk about everything analyst related
475 01:10:32.840 ⇒ 01:10:33.600 Uttam Kumaran: ideally.
476 01:10:33.600 ⇒ 01:10:34.110 Payas Parab (TikTok): But, my, my.
477 01:10:34.540 ⇒ 01:10:40.089 Payas Parab (TikTok): it’s like if like people join sometimes right where it’s like, oh, like oh, like it! It kind of like it resolves.
478 01:10:40.090 ⇒ 01:10:44.140 Uttam Kumaran: I mean, I’m just not like I don’t wanna play cop and be like
479 01:10:44.290 ⇒ 01:10:53.839 Uttam Kumaran: have to join these. I will say if I do. If you, if I do need to do that, the brain force data meeting that happens every day is like the one thing to join.
480 01:10:55.590 ⇒ 01:11:01.290 Uttam Kumaran: So if that’s I will play cop there and say like, that’s the one thing sure.
481 01:11:01.470 ⇒ 01:11:04.020 Uttam Kumaran: meetings across the horizontal meetings
482 01:11:04.270 ⇒ 01:11:09.179 Uttam Kumaran: for the Aes. We’re all on every day. So I’m less concerned about that. I know that on the analyst side.
483 01:11:11.000 ⇒ 01:11:18.670 Uttam Kumaran: typically, it’s been productive last week, I think Bo right. So I I would love to keep that, and just to learn as an analyst squad.
484 01:11:18.950 ⇒ 01:11:21.120 Uttam Kumaran: The the data meeting that’s at
485 01:11:21.907 ⇒ 01:11:27.989 Uttam Kumaran: in the morning is good. I know that’s early. Pst, it’s like, so if we want to
486 01:11:28.260 ⇒ 01:11:40.340 Uttam Kumaran: think about timing, ping me. But that one, I think, is still really, really core, because that’s the only time we meet every day and go through the most urgent client things, and we don’t talk about other stuff is going well, I don’t talk about it really.
487 01:11:40.845 ⇒ 01:11:43.590 Uttam Kumaran: And we push a lot of stuff still, Async
488 01:11:43.950 ⇒ 01:11:52.280 Uttam Kumaran: and I’m really trying to keep us out of like other meetings like, if if that can’t happen, then I have to book calls on specific topics. So I feel like we can batch everything there.
489 01:11:54.800 ⇒ 01:12:08.189 michael weinberg: I think it’s it’s worth noting that, like in general, some meetings will be more valuable, Tom. Like as a listener and an asker than to like any other participant, which means like it might feel like your presence could be
490 01:12:08.380 ⇒ 01:12:09.986 michael weinberg: not helpful.
491 01:12:10.950 ⇒ 01:12:16.600 michael weinberg: But the fact that everyone’s present means that it’s able to have like a complete picture of what’s going on.
492 01:12:16.820 ⇒ 01:12:22.390 michael weinberg: It’s hard to to like assess, you know, to evaluate what that value is, but it’s
493 01:12:22.660 ⇒ 01:12:24.819 michael weinberg: it’s most likely pretty high.
494 01:12:25.180 ⇒ 01:12:28.509 michael weinberg: So there, there could be like differences in perception.
495 01:12:29.000 ⇒ 01:12:33.670 michael weinberg: so I do think it’s important to like. If you ever feel like. You’re not sure if you’re
496 01:12:33.860 ⇒ 01:12:37.260 michael weinberg: relevant, or something that’s like a great thing to bring up
497 01:12:37.810 ⇒ 01:12:43.419 michael weinberg: because, honestly, in all likelihood, you are, your presence is valued more than you know.
498 01:12:47.080 ⇒ 01:12:51.679 Uttam Kumaran: Thanks, Mike, that’s helpful. Yeah, I agree. I mean, a lot of this business is built on trust
499 01:12:52.040 ⇒ 01:12:53.980 Uttam Kumaran: and communication. So
500 01:12:54.590 ⇒ 01:12:59.919 Uttam Kumaran: 2 meetings a day, Max French on engineering side, I try to give everybody at least like
501 01:13:00.120 ⇒ 01:13:05.439 Uttam Kumaran: 6 7 h of like more head sound time, so can hold me to that.
502 01:13:05.990 ⇒ 01:13:12.169 Uttam Kumaran: But otherwise I think this is a great meeting. So I’m gonna put some stuff like that we talked about in motion early next week, and
503 01:13:12.360 ⇒ 01:13:31.600 Uttam Kumaran: we’ll do another round of this next Friday. And hopefully, we talk. We can talk about some stuff we didn’t get to, and some new items. But yeah, ping me on the side or in the data channel. If this was helpful, or if it’s anything about this format that we want to change, we will be doing 2 roadmap sessions on Monday, so I’ll invite folks to that. It was very helpful to do that this week.
504 01:13:32.415 ⇒ 01:13:35.449 Uttam Kumaran: Any other questions, please. Message. Me.
505 01:13:37.840 ⇒ 01:13:38.660 Uttam Kumaran: Cool.
506 01:13:38.940 ⇒ 01:13:40.500 Uttam Kumaran: Okay. Thanks. Everyone.
507 01:13:40.500 ⇒ 01:13:42.709 Robert Tseng: Can the Eden folks stay on the call.
508 01:13:43.620 ⇒ 01:13:46.609 Uttam Kumaran: Cool. Yeah, Robert, I’ll make you host.
509 01:13:47.320 ⇒ 01:13:47.980 Robert Tseng: Alright!
510 01:13:48.660 ⇒ 01:13:51.989 Uttam Kumaran: Actually, I need. I need the zoom for another meeting.
511 01:13:51.990 ⇒ 01:13:53.930 Robert Tseng: Alright! Alright! I’ll send another one. Yeah.
512 01:13:53.930 ⇒ 01:13:54.939 Uttam Kumaran: Okay. Okay.
513 01:13:54.940 ⇒ 01:13:58.576 Sahana Asokan: I need to prep for an 1130 call. So
514 01:13:59.330 ⇒ 01:14:01.919 Sahana Asokan: is it? I guess I’ll stay on. It’s fine.
515 01:14:02.380 ⇒ 01:14:07.370 Uttam Kumaran: Yeah, I think. Maybe I think Robert’s probably just got masters in slack. Bye.