Meeting Title: Zoom-Meeting Date: 2024-06-18 Meeting participants: Atharv Gudi, Uttam Kumaran
WEBVTT
1 00:00:09.770 ⇒ 00:00:11.320 Uttam Kumaran: Hi dars
2 00:00:11.540 ⇒ 00:00:12.310 Uttam Kumaran: us!
3 00:00:28.505 ⇒ 00:00:30.029 Uttam Kumaran: Hey? Can you hear me?
4 00:00:30.870 ⇒ 00:00:32.239 Atharv Gudi: Hi, yeah, I can hear you.
5 00:00:32.549 ⇒ 00:00:36.360 Uttam Kumaran: Hey? Sorry. I’m just off Video. I’m just at a coffee shop working
6 00:00:37.499 ⇒ 00:00:39.069 Uttam Kumaran: So how was your trip.
7 00:00:39.790 ⇒ 00:00:46.569 Atharv Gudi: It was good. It was good. I got back just late last night. That’s why I had to reschedule the whole thing.
8 00:00:46.750 ⇒ 00:00:49.020 Uttam Kumaran: No problem. How was it? What was the highlights.
9 00:00:50.876 ⇒ 00:00:53.583 Atharv Gudi: We went paragliding once.
10 00:00:55.290 ⇒ 00:00:58.830 Atharv Gudi: certainly not. We just went around and we ate a lot of food. I think that was
11 00:00:59.440 ⇒ 00:01:01.590 Atharv Gudi: the whole trip.
12 00:01:03.980 ⇒ 00:01:06.730 Uttam Kumaran: Like just super full just like eating anything.
13 00:01:10.353 ⇒ 00:01:16.659 Atharv Gudi: I’m not able to. I think it’s my wi-fi. That’s the issue. I think I’m I’m just like switching the Wi-fi.
14 00:01:16.660 ⇒ 00:01:18.270 Uttam Kumaran: Okay, okay, no problem. Let me know.
15 00:01:23.330 ⇒ 00:01:25.370 Uttam Kumaran: I’m not saying you have that.
16 00:01:25.560 ⇒ 00:01:29.269 Uttam Kumaran: I’d be honest with my experience, because I don’t think
17 00:01:34.530 ⇒ 00:01:36.689 Uttam Kumaran: they either have to hear people constantly.
18 00:01:37.040 ⇒ 00:01:38.969 Uttam Kumaran: They don’t get dogs, they
19 00:01:40.420 ⇒ 00:01:42.280 Uttam Kumaran: or they’re like, who
20 00:01:42.730 ⇒ 00:01:44.429 Uttam Kumaran: also, I mean, like
21 00:01:44.600 ⇒ 00:01:45.360 Uttam Kumaran: something.
22 00:01:56.420 ⇒ 00:01:57.500 Uttam Kumaran: Chair fundraiser.
23 00:01:59.020 ⇒ 00:01:59.740 Uttam Kumaran: Thanks.
24 00:02:03.730 ⇒ 00:02:05.935 Uttam Kumaran: Yeah.
25 00:02:08.770 ⇒ 00:02:11.330 Uttam Kumaran: It’s like super super awesome
26 00:02:14.910 ⇒ 00:02:16.929 Uttam Kumaran: who have it, for example.
27 00:02:17.160 ⇒ 00:02:18.890 Uttam Kumaran: So it’s not impossible.
28 00:02:19.570 ⇒ 00:02:20.410 Uttam Kumaran: People love them.
29 00:02:21.660 ⇒ 00:02:22.945 Uttam Kumaran: Yeah.
30 00:02:25.370 ⇒ 00:02:27.833 Uttam Kumaran: would it be there?
31 00:02:30.020 ⇒ 00:02:32.050 Uttam Kumaran: So yeah, that’s a good. Yeah.
32 00:02:32.640 ⇒ 00:02:34.429 Uttam Kumaran: It’s just, you know.
33 00:02:37.208 ⇒ 00:02:38.400 Uttam Kumaran: Can you hear me?
34 00:02:38.760 ⇒ 00:02:40.070 Atharv Gudi: Yeah, I can hear you now.
35 00:02:40.310 ⇒ 00:02:44.800 Uttam Kumaran: Okay, cool. No. I was just asking what food and stuff did you get.
36 00:02:45.110 ⇒ 00:02:47.909 Atharv Gudi: I had a lot of Tibetan through, cause it’s
37 00:02:47.950 ⇒ 00:02:51.550 Atharv Gudi: there’s a lot of Tibetan refugees that live there. So I just had
38 00:02:51.700 ⇒ 00:02:54.669 Atharv Gudi: bunch of that, and a lot of parata. I love.
39 00:02:55.046 ⇒ 00:03:00.310 Uttam Kumaran: Nice. Yeah, same, I, that’s like what I order at every Indian restaurant. Basically.
40 00:03:01.272 ⇒ 00:03:08.593 Uttam Kumaran: that’s that’s like, it’s like an Indian person. Basically, I feel like the same way they make it so
41 00:03:09.200 ⇒ 00:03:09.930 Uttam Kumaran: fuck
42 00:03:10.110 ⇒ 00:03:11.200 Uttam Kumaran: nice.
43 00:03:11.848 ⇒ 00:03:16.720 Uttam Kumaran: Well, we’ve had a couple of good days. I basically have spoken to.
44 00:03:17.530 ⇒ 00:03:20.719 Uttam Kumaran: and a couple of the other interns. Seems like some people are
45 00:03:21.505 ⇒ 00:03:22.534 Uttam Kumaran: Priya and
46 00:03:23.240 ⇒ 00:03:41.430 Uttam Kumaran: and Akshay are interested in doing like data analysis. So I’ve had them kind of kick off some learnings around sequel, and like learning sequel, Jared is kind of split between some stuff on the sales side like learning a little bit about how sales works as well as
47 00:03:41.430 ⇒ 00:03:55.709 Uttam Kumaran: gonna be focused on data analysis. And then was gonna ask you, I remember, you know, we initially started talking about working within like data engineering but I wanted to confirm because we haven’t spoken like what
48 00:03:56.154 ⇒ 00:04:01.460 Uttam Kumaran: what you’re interested in, and if I can answer any questions, and again, none of this is like
49 00:04:01.680 ⇒ 00:04:09.210 Uttam Kumaran: super fixed or anything like it’s, and it’ll be a lot of overlap. But just wanted to get a sense of where you’re thinking of.
50 00:04:20.180 ⇒ 00:04:21.040 Uttam Kumaran: Hello.
51 00:04:21.970 ⇒ 00:04:22.850 Atharv Gudi: Hello!
52 00:04:23.080 ⇒ 00:04:23.630 Uttam Kumaran: Hey? Okay.
53 00:04:23.630 ⇒ 00:04:24.490 Atharv Gudi: Yeah, did you catch.
54 00:04:24.490 ⇒ 00:04:25.810 Uttam Kumaran: Yeah, did you catch any of that.
55 00:04:26.496 ⇒ 00:04:34.490 Atharv Gudi: I didn’t. Hang on. I’m just gonna try to switch my device and I’ll see if that works better, cause I can’t hear anything on this.
56 00:04:35.490 ⇒ 00:04:39.439 Uttam Kumaran: Okay? One second, you can also try dialing in.
57 00:04:39.790 ⇒ 00:04:41.270 Atharv Gudi: Yeah, I might try that.
58 00:04:44.230 ⇒ 00:04:48.620 Uttam Kumaran: I can see if I can send you the dial in instructions.
59 00:04:53.100 ⇒ 00:04:53.710 Atharv Gudi: Great.
60 00:05:18.545 ⇒ 00:05:19.959 Atharv Gudi: Yeah. Do you hear me? Now?
61 00:05:20.190 ⇒ 00:05:22.070 Uttam Kumaran: I can hear you. Yeah, how about me?
62 00:05:22.070 ⇒ 00:05:25.340 Atharv Gudi: Okay, yeah, I can hear you, too. I think this much. This is much better.
63 00:05:25.510 ⇒ 00:05:44.319 Uttam Kumaran: Okay. Okay, yeah, no. The big thing I was mentioning is that you know, I spoke to Priya Akshay and Jared. And they’re kind of each kind of settled in either data analysis. And Jared is helping me also a little bit on the business side. That’s what he’s kind of has like a background in like entrepreneurship, and is interested kind of in that angle.
64 00:05:44.778 ⇒ 00:05:51.549 Uttam Kumaran: You know, I remember that we talked a little bit about data engineering, but wondering if you had any like
65 00:05:51.600 ⇒ 00:05:59.060 Uttam Kumaran: got reaction to one of the kind of 4 angles. And I guess the caveat from my side is that it doesn’t. It’s not like super
66 00:05:59.754 ⇒ 00:06:04.509 Uttam Kumaran: like fixed in stone. You know, there’s a lot of overlap between the 3. I just.
67 00:06:04.510 ⇒ 00:06:04.920 Atharv Gudi: Okay.
68 00:06:04.920 ⇒ 00:06:07.930 Uttam Kumaran: Mainly for me, pairing you with someone internally
69 00:06:08.192 ⇒ 00:06:15.520 Uttam Kumaran: and then like kind of giving you some tasks to work on that can actually get deployed into production. I wanna kind of have a sense of where you want to focus on
70 00:06:16.480 ⇒ 00:06:17.290 Atharv Gudi: Ground.
71 00:06:17.290 ⇒ 00:06:23.420 Uttam Kumaran: So yeah, let me know. And I I just I noticed in your stand up report that you had some questions so happy to answer it.
72 00:06:23.420 ⇒ 00:06:33.689 Atharv Gudi: Yeah, I just wanted to know. Cause I didn’t find I mean, I went and did my own research. But in in from the perspective of what the kind of work that we’ll be doing.
73 00:06:33.710 ⇒ 00:06:39.240 Atharv Gudi: Could you just let me know a little bit more about the difference between data, engineering and analytics, engineering.
74 00:06:39.490 ⇒ 00:06:40.049 Uttam Kumaran: Yeah, so.
75 00:06:40.050 ⇒ 00:06:42.530 Atharv Gudi: With the customer. What happens in Brainforge.
76 00:06:42.530 ⇒ 00:06:59.659 Uttam Kumaran: Yeah, so data engineering this stuff with kind of the data engineering work that we do here is a couple of things. One is on the infrastructure side. So this is like setting up new data infrastructure. So setting up new data warehouses, setting up new data pipelines, this is also on the security side. So making sure that we have
77 00:06:59.680 ⇒ 00:07:05.829 Uttam Kumaran: proper security proper role based access and anything involving like moving data around
78 00:07:06.190 ⇒ 00:07:19.419 Uttam Kumaran: on the analytics engineering side. This is primarily focus on data modeling. So this is really trying to have a very great understanding of the business model of the client and being able to translate that into SQL logic.
79 00:07:19.470 ⇒ 00:07:20.920 Uttam Kumaran: So it’s like less.
80 00:07:21.010 ⇒ 00:07:38.499 Uttam Kumaran: It’s close. It’s like similar to data analysis, except analysis. We separate out because you typically aren’t modeling data modeling, meaning like, let’s say, we have just a transaction log from a client. How do you go from a transaction log to what were our sales yesterday.
81 00:07:38.560 ⇒ 00:07:48.480 Uttam Kumaran: There is some data modeling that’s heavy and sequel that needs to happen. And not only just writing sequel, but the actual putting that into a system that can execute that
82 00:07:48.600 ⇒ 00:08:01.639 Uttam Kumaran: doing data testing and basically interacting a lot with data tables to basically help a analyst answer questions. So it’s definitely above data engineering a lot heavier on
83 00:08:02.220 ⇒ 00:08:11.850 Uttam Kumaran: like, really, probably really primarily heavy on SQL, data engineering, it’s mixed between sequel and python. And basically like Gui’s for different software.
84 00:08:12.940 ⇒ 00:08:13.750 Atharv Gudi: Okay, I’m
85 00:08:14.600 ⇒ 00:08:18.129 Atharv Gudi: I’m still thinking of between these 2.
86 00:08:18.420 ⇒ 00:08:21.790 Atharv Gudi: I know I want to do one of these, too. I’m still
87 00:08:22.240 ⇒ 00:08:23.509 Atharv Gudi: trying to get a hold of.
88 00:08:24.220 ⇒ 00:08:27.329 Uttam Kumaran: I. My, my suggestion would be to
89 00:08:27.450 ⇒ 00:08:30.930 Uttam Kumaran: to try analytics engineering 1st
90 00:08:31.840 ⇒ 00:08:42.550 Uttam Kumaran: and then see see if you like it. It’s gonna require pretty heavy understanding of sequel. Which I I don’t remember. If you had any previous background, like working.
91 00:08:42.559 ⇒ 00:08:42.899 Atharv Gudi: I have.
92 00:08:42.900 ⇒ 00:08:43.950 Uttam Kumaran: And it’s a little.
93 00:08:44.200 ⇒ 00:08:46.119 Atharv Gudi: I do? I do I? Yeah.
94 00:08:46.530 ⇒ 00:09:09.359 Uttam Kumaran: Okay, cool. Then. Actually, that helps because the like Akshay and Priya, they’re just learning and kind of getting familiar with sequel right now. So I kinda told them, Hey, start with data analysis. And then you can decide where you want to go. But if you’re really comfortable with sequel, then tomorrow I’m gonna do a. I’m just doing a basic review session of like kind of like sequel fundamentals for everybody, and like walking through some code.
95 00:09:09.420 ⇒ 00:09:13.479 Uttam Kumaran: And then I would love to just like kind of pair you up. And yeah.
96 00:09:13.760 ⇒ 00:09:15.719 Atharv Gudi: I think that’s that last bit. I
97 00:09:15.940 ⇒ 00:09:20.070 Atharv Gudi: the her I got the tomorrow you were mentioning something.
98 00:09:20.070 ⇒ 00:09:27.469 Uttam Kumaran: Yeah, I’m gonna do like a sequel fundamentals tomorrow, basically just like kind of overview of sequel. And how we use sequel here internally.
99 00:09:27.793 ⇒ 00:09:32.500 Uttam Kumaran: Because Priya and Akshay are just learning it for the 1st time right now.
100 00:09:33.010 ⇒ 00:09:33.810 Atharv Gudi: Okay.
101 00:09:34.357 ⇒ 00:09:35.099 Uttam Kumaran: So I can.
102 00:09:35.100 ⇒ 00:09:35.770 Atharv Gudi: Yeah.
103 00:09:36.070 ⇒ 00:09:57.300 Uttam Kumaran: Yeah. So tomorrow morning I’ll be scheduling that but I would like to include you in that. Just so you you can get like a little bit of a overview. And I’ll I’ll be showing some code and things like that. And then if you want, if I think let’s focus on the analytics engineering path. Because if you have a good understanding of sequel, then this is basically, how do you actually execute sequel and production? How do you do data testing
104 00:09:57.757 ⇒ 00:10:03.649 Uttam Kumaran: how do you like structure schemas and databases? This is basically everything that happens within the data warehouse.
105 00:10:04.720 ⇒ 00:10:05.120 Atharv Gudi: Him.
106 00:10:05.120 ⇒ 00:10:25.890 Uttam Kumaran: So there, there will be some component of like data movement within the warehouse. But this is like a nice way to get started using SQL and using Snowflake. And then you can decide whether you want to move towards it. Engineering later. That’s totally fine, or or continue working on stuff. Here. And we have a, we have actually like a bunch of analytics engineering work
107 00:10:26.381 ⇒ 00:10:28.429 Uttam Kumaran: that needs to get done. So
108 00:10:28.975 ⇒ 00:10:51.254 Uttam Kumaran: it’s actually great. I’m actually very happy. I didn’t. I didn’t want to push anyone. But that’s actually my background is primarily in analytics engineering. That’s what I really like. Did it did really well, and then kind of tough taught a lot of people so, and the folks that we have on the team that do analytics engineering are are very, very good. So you have a you’ll have a lot of support, and I think
109 00:10:51.790 ⇒ 00:10:58.169 Uttam Kumaran: I will. I’ll I’ll begin to send you some materials on, on some of the specific technologies. And
110 00:10:58.270 ⇒ 00:11:04.880 Uttam Kumaran: I think there’s some really great like kind of like short courses that you can do that just to take a few days that you can run through and basically.
111 00:11:04.880 ⇒ 00:11:05.210 Atharv Gudi: Yeah, but.
112 00:11:05.210 ⇒ 00:11:12.580 Uttam Kumaran: You can run, you can run through them in. We have a personal snowflake environment for brainfores that you can use for any sort of a testing and things like that.
113 00:11:12.842 ⇒ 00:11:30.229 Uttam Kumaran: And then I have a perfect person to to kind of pair you up with, I mean, of course. But I want to pair you up with someone. So in case I’m busy. You have someone ask questions. So let’s let’s plan on that I’m gonna send you. I’m gonna send you one thing about what I’m gonna be reviewing tomorrow. Give me one second.
114 00:11:30.680 ⇒ 00:11:31.410 Atharv Gudi: Oh, alder.
115 00:11:38.790 ⇒ 00:11:44.349 Uttam Kumaran: And again depending on how confident you are in sequel. This may be helpful or just
116 00:11:44.900 ⇒ 00:11:46.190 Uttam Kumaran: you know, if
117 00:11:46.410 ⇒ 00:11:49.290 Uttam Kumaran: more content. But I’m I’m gonna paste in our
118 00:11:50.270 ⇒ 00:11:52.829 Uttam Kumaran: in our notion, Doc, in our meeting Doc.
119 00:11:53.150 ⇒ 00:11:53.610 Atharv Gudi: Okay.
120 00:11:53.610 ⇒ 00:11:55.150 Uttam Kumaran: Just resources here.
121 00:11:59.420 ⇒ 00:12:15.398 Uttam Kumaran: So there’s this, there’s this tool that I recommend to everybody who comes and ask me, like, how do you get into data basically to learn sequel. And it’s called sequels. Do patrick sent it over last week. Basically, it’s just like a really high level overview of exercises in sequel.
122 00:12:15.860 ⇒ 00:12:24.170 Uttam Kumaran: my suggestion is like, if you’re if you want to even brush up just a little bit to run through. That should be pretty quick for you. That’s what I’ll be kind of reviewing and answering any questions of tomorrow.
123 00:12:25.943 ⇒ 00:12:26.509 Uttam Kumaran: I’m gonna.
124 00:12:27.021 ⇒ 00:12:28.329 Atharv Gudi: So I have that there
125 00:12:29.040 ⇒ 00:12:32.130 Atharv Gudi: in which part of notion can I find that.
126 00:12:32.130 ⇒ 00:12:36.559 Uttam Kumaran: It’s it’s in the. It’s in the Uttam atharv meeting notes.
127 00:12:37.460 ⇒ 00:12:38.679 Atharv Gudi: Meeting Notes.
128 00:12:40.250 ⇒ 00:12:42.250 Uttam Kumaran: So if you go to your name and you scroll all the way.
129 00:12:42.250 ⇒ 00:12:42.570 Atharv Gudi: Yeah.
130 00:12:42.570 ⇒ 00:12:44.459 Uttam Kumaran: Bottom. Yeah, yeah, perfect.
131 00:12:46.530 ⇒ 00:12:49.009 Atharv Gudi: I got it I got it. The SQL.
132 00:12:49.040 ⇒ 00:12:50.230 Atharv Gudi: Zoo, yeah.
133 00:12:50.420 ⇒ 00:12:53.669 Uttam Kumaran: Yeah. And so the other things I’m gonna also put in here.
134 00:12:54.240 ⇒ 00:12:57.499 Uttam Kumaran: I’m actually, I could just do this right now. So Dbt control
135 00:12:58.950 ⇒ 00:12:59.930 Uttam Kumaran: insulted.
136 00:13:00.170 ⇒ 00:13:01.130 Uttam Kumaran: So you.
137 00:13:42.530 ⇒ 00:13:43.479 Atharv Gudi: Oh, yeah, I see.
138 00:13:44.200 ⇒ 00:13:48.476 Uttam Kumaran: Yeah, I’m just gonna give you. I’m gonna put a couple of these. But I’m also gonna
139 00:13:49.180 ⇒ 00:13:50.500 Uttam Kumaran: confirm
140 00:13:51.280 ⇒ 00:13:54.389 Uttam Kumaran: with another teammate on what are some good.
141 00:13:57.440 ⇒ 00:13:58.969 Uttam Kumaran: what are some good
142 00:14:00.470 ⇒ 00:14:03.740 Uttam Kumaran: Dbt courses? But that’s gonna be a really good one.
143 00:14:08.460 ⇒ 00:14:08.830 Atharv Gudi: Ray
144 00:14:24.520 ⇒ 00:14:26.700 Atharv Gudi: This Dbt course requires.
145 00:14:26.840 ⇒ 00:14:28.979 Atharv Gudi: Does it require registration?
146 00:14:29.759 ⇒ 00:14:35.490 Uttam Kumaran: You may just have to register. It’s just like for free. You may just have to give them your screen for Gmail.
147 00:14:35.590 ⇒ 00:14:41.196 Uttam Kumaran: Probably they just use it from. They just use it for marketing and stuff. So don’t worry too much about that
148 00:14:42.500 ⇒ 00:14:45.350 Uttam Kumaran: And then one second I’ll do one more. But
149 00:15:52.420 ⇒ 00:15:57.709 Uttam Kumaran: so each of these, you know, I would go ahead and start, and the things that you need from me.
150 00:15:57.880 ⇒ 00:16:00.480 Uttam Kumaran: or I want to give you snowflake
151 00:16:00.700 ⇒ 00:16:04.090 Uttam Kumaran: credentials to the brain forge.
152 00:16:05.685 ⇒ 00:16:06.050 Atharv Gudi: Cam.
153 00:16:06.500 ⇒ 00:16:07.250 Uttam Kumaran: Org.
154 00:16:07.690 ⇒ 00:16:09.870 Uttam Kumaran: I want to intro to
155 00:16:10.250 ⇒ 00:16:11.160 Uttam Kumaran: or
156 00:16:11.540 ⇒ 00:16:13.050 Uttam Kumaran: training for
157 00:16:15.678 ⇒ 00:16:18.259 Uttam Kumaran: and then I’m gonna go ahead. And
158 00:16:18.500 ⇒ 00:16:21.620 Uttam Kumaran: I think tomorrow, let’s talk. And I just wanna
159 00:16:21.951 ⇒ 00:16:29.740 Uttam Kumaran: see if you have a chance to click around these. And then basically, I want to do a kind of try to schedule like a review with me, you and Brian.
160 00:16:29.790 ⇒ 00:16:38.310 Uttam Kumaran: Maybe on Friday it makes most sense. Just so we could answer any questions again like, and and my question to you will actually be like
161 00:16:38.800 ⇒ 00:16:41.709 Uttam Kumaran: like, what’s more, of your learning style. To give you an
162 00:16:41.980 ⇒ 00:16:53.929 Uttam Kumaran: an example, I am not good at taking these courses, although I like I’m ha! I’m happy to walk through. The real learning I have is like you give me tasks, and I can do that kind of in parallel.
163 00:16:54.306 ⇒ 00:17:00.540 Uttam Kumaran: However, some people, some people really love the structured learning of these courses. Some people are like.
164 00:17:01.031 ⇒ 00:17:10.790 Uttam Kumaran: They have Adhd, and they’re just like, I gotta do something so in interested in, like what your like learning style is when it comes to these sorts of online courses or self kind of guided
165 00:17:11.119 ⇒ 00:17:12.160 Uttam Kumaran: horses.
166 00:17:12.579 ⇒ 00:17:19.909 Atharv Gudi: Yeah. So for all of these, I feel like I can get a fair, a rough idea, or a fair idea of
167 00:17:20.069 ⇒ 00:17:23.059 Atharv Gudi: things from courses. But I do like to
168 00:17:23.639 ⇒ 00:17:27.189 Atharv Gudi: see how it is work. I’m more of an observer.
169 00:17:27.279 ⇒ 00:17:28.469 Atharv Gudi: Okay? And
170 00:17:28.569 ⇒ 00:17:34.349 Atharv Gudi: someone who. So I’d like to observe and see how people work on things. And just basically.
171 00:17:34.549 ⇒ 00:17:45.199 Atharv Gudi: you know, look at that thought process. What are they thinking about? Are they thinking about something that I’m not thinking about, and then maybe eventually, you know, get my toes in and then start doing things on my own.
172 00:17:45.380 ⇒ 00:17:47.590 Uttam Kumaran: Okay, okay, perfect. So
173 00:17:47.730 ⇒ 00:17:50.400 Uttam Kumaran: I think we should. Probably
174 00:17:50.870 ⇒ 00:17:58.839 Uttam Kumaran: we should probably kick you off with a task as well that you can do some pair pair programming with with Brian.
175 00:17:59.253 ⇒ 00:18:09.899 Uttam Kumaran: I’m gonna discuss with him what’s the best task that is a kind of isolated that you can take on. It’s these tools are a little bit like they build on top of sequel.
176 00:18:10.501 ⇒ 00:18:20.339 Uttam Kumaran: And there. And but the thing I want to continue to say to everyone is like, I want everybody to learn at their own pace. And basically, my goal is for you to be able to push
177 00:18:20.400 ⇒ 00:18:21.889 Uttam Kumaran: production code
178 00:18:21.920 ⇒ 00:18:25.690 Uttam Kumaran: well before, like the end of August, and so.
179 00:18:25.690 ⇒ 00:18:26.270 Atharv Gudi: But I.
180 00:18:26.270 ⇒ 00:18:34.929 Uttam Kumaran: I want people to learn at their own pace. But at the same time, like we have, either through these courses or through us. We have all the answers that you need.
181 00:18:35.317 ⇒ 00:18:38.589 Uttam Kumaran: The other things I’m just going to put in here are
182 00:18:38.740 ⇒ 00:18:41.959 Uttam Kumaran: structuring ebt best.
183 00:18:43.600 ⇒ 00:18:46.009 Uttam Kumaran: and there’s 2 kind of like
184 00:18:46.670 ⇒ 00:18:49.840 Uttam Kumaran: things that I reference really often about like.
185 00:18:49.920 ⇒ 00:18:51.859 Uttam Kumaran: how do you structure? dB, T.
186 00:18:51.970 ⇒ 00:18:53.119 Uttam Kumaran: And we all.
187 00:18:53.120 ⇒ 00:18:53.440 Atharv Gudi: So.
188 00:18:53.440 ⇒ 00:18:57.059 Uttam Kumaran: Have a structured Dbt Doc internally.
189 00:18:57.130 ⇒ 00:18:58.858 Uttam Kumaran: that I will also.
190 00:19:00.040 ⇒ 00:19:01.610 Uttam Kumaran: let’s name here.
191 00:19:08.050 ⇒ 00:19:09.059 Uttam Kumaran: You’re up to.
192 00:19:32.470 ⇒ 00:19:34.279 Uttam Kumaran: Okay, perfect. So
193 00:19:34.440 ⇒ 00:19:39.550 Uttam Kumaran: I think the big, the biggest thing is, tomorrow we’re gonna schedule. I’m gonna have us
194 00:19:39.900 ⇒ 00:19:42.060 Uttam Kumaran: the SQL Zoo.
195 00:19:43.070 ⇒ 00:19:43.630 Atharv Gudi: Yeah.
196 00:19:43.630 ⇒ 00:19:44.739 Uttam Kumaran: Worth of you.
197 00:19:47.290 ⇒ 00:19:53.720 Uttam Kumaran: And then I’m gonna make sure you have. You have access to our internal snowflake warehouse where you’ll be able to
198 00:19:53.800 ⇒ 00:20:00.220 Uttam Kumaran: basically, all these things will in interact with snowflake. So you’ll be able to create tables, create data warehouses.
199 00:20:00.240 ⇒ 00:20:06.850 Uttam Kumaran: Set up your local environment. You’re you’re familiar with like setting up like, have you used Vs code before on your laptop?
200 00:20:06.850 ⇒ 00:20:08.149 Atharv Gudi: I have. Yeah, I have.
201 00:20:08.410 ⇒ 00:20:11.229 Uttam Kumaran: Okay, cool. So then I’m gonna send you also our
202 00:20:11.540 ⇒ 00:20:12.920 Uttam Kumaran: engineering upon it.
203 00:20:14.600 ⇒ 00:20:16.210 Uttam Kumaran: This will be helpful.
204 00:20:52.220 ⇒ 00:20:52.900 Uttam Kumaran: But
205 00:20:53.260 ⇒ 00:21:07.069 Uttam Kumaran: yeah, you don’t. We don’t for the for the analyst. They don’t need all this because they’re primarily be working in sequel, direct and stuff like. But for any engineer like data engineer or an analytics engineer. We have an inboard engineering, onboarding checklist.
206 00:21:07.823 ⇒ 00:21:26.349 Uttam Kumaran: The one thing that I will ask for any sort of internal documentation is, if you find anything that we’re missing. Please please add it onto there, or if you go through any steps, and you can add more contacts or more things that would be super helpful. Everybody has gone through this and kind of added more stuff. But that’s kind of the way these
207 00:21:26.370 ⇒ 00:21:30.370 Uttam Kumaran: documents really continue to improve and get better for the next person. So
208 00:21:30.480 ⇒ 00:21:32.470 Uttam Kumaran: oh, that’s a little bit of like
209 00:21:32.650 ⇒ 00:21:44.400 Uttam Kumaran: internal documentation 101 so I’m trying to push everybody to kind of like use these docs and and make them better as you go through and find that there’s things that need to be updated or things that need to be restructured. So.
210 00:21:44.718 ⇒ 00:21:49.620 Uttam Kumaran: these are Google Docs. We’ve just been moving to notion. So apologies. We’ll probably get this annoying.
211 00:21:49.620 ⇒ 00:21:51.420 Atharv Gudi: Oh, yeah, yeah, so.
212 00:21:53.312 ⇒ 00:21:56.919 Uttam Kumaran: And that’s great. Any questions
213 00:21:57.150 ⇒ 00:21:58.830 Uttam Kumaran: I can answer.
214 00:21:59.580 ⇒ 00:22:00.350 Uttam Kumaran: Nap.
215 00:22:02.980 ⇒ 00:22:10.289 Atharv Gudi: yeah. So the I think that another fee that I was disciplined that I was looking at was AI. I was wondering how that
216 00:22:10.480 ⇒ 00:22:16.279 Atharv Gudi: like to what extent that you possibly could. We are probably gonna do in Brain forge over the summer. Yeah.
217 00:22:16.280 ⇒ 00:22:17.270 Uttam Kumaran: Yeah.
218 00:22:17.270 ⇒ 00:22:18.260 Atharv Gudi: Oh!
219 00:22:18.540 ⇒ 00:22:25.880 Uttam Kumaran: Yeah, great question. It’s actually funny. I think, like you, Jared and Akshay are are all interested in AI stuff which is great because.
220 00:22:26.531 ⇒ 00:22:31.448 Uttam Kumaran: we are doing AI stuff both for clients and for
221 00:22:32.460 ⇒ 00:22:42.589 Uttam Kumaran: and for ourselves internally, like my goal. When I started, the company was to basically, you know. I started the company last
222 00:22:42.881 ⇒ 00:22:58.640 Uttam Kumaran: July, and honestly, still thinking about it the 2 months before, which is kind of like right when Chat Gbt and everything just came out. And you know, I’ve been, I use Chat Gbt and AI tools every day for work. And basically, one of my goals was to automate 50% of the business
223 00:22:59.036 ⇒ 00:23:16.689 Uttam Kumaran: basically trying trying to establish that, we can dog food, the AI tools and then basically go out into the market and also sell. You know, automations, whether it’s on the sales side technical side. And so there are several automations and process automation things that I want to do
224 00:23:16.740 ⇒ 00:23:29.339 Uttam Kumaran: for us internally. That basically helps streamline me, Nico and the rest of the teams work. This could be everything from like improving how we do code reviews to transcribing meetings to
225 00:23:30.124 ⇒ 00:23:34.389 Uttam Kumaran: improving how we structure our emails to clients.
226 00:23:34.858 ⇒ 00:23:38.439 Uttam Kumaran: So there’s a ton of like really, really like
227 00:23:39.005 ⇒ 00:23:52.200 Uttam Kumaran: low hanging fruit on the AI side for automation. Internally, the other thing is for clients. There are some really great opportunities to run AI tools within Snowflake and actually help
228 00:23:52.200 ⇒ 00:24:10.300 Uttam Kumaran: categorize, translate, and summarize, but free text. In the data warehouse for clients. So a good example of this is, we have a client that has a customer service desk and basically clients. Customers ask them several questions and they have customer service people that respond.
229 00:24:10.340 ⇒ 00:24:35.604 Uttam Kumaran: But the problem is like the customer service. People aren’t always great at categorizing the tickets, meaning like, Oh, this was a warranty issue. Oh, this was a like a broken product. Oh, this was a shipping delay. And so they have a hard time understanding, like really like what all the issues are. And so one of the things one of the open items we have is to basically use AI and use like a patch or the Openai
230 00:24:36.160 ⇒ 00:24:41.300 Uttam Kumaran: Api to basically pass in these tickets and get categorizations out.
231 00:24:41.420 ⇒ 00:25:03.990 Uttam Kumaran: So that’s like one clear example of like a customer facing issue that we want to solve using AI. So it’s like things like that. So I think it’s honestly going to be heavily on us internally automating things, and then also we will find opportunities to also use automation for our clients, and then also set the foundation for how we use AI internally. So
232 00:25:04.080 ⇒ 00:25:07.259 Uttam Kumaran: I think there’s a ton of opportunity. And I actually
233 00:25:07.500 ⇒ 00:25:15.760 Uttam Kumaran: like, I love, I think, like selfishly. It’s gonna help the company so much that I’m like, I’m really a fan of people. Take that. However.
234 00:25:15.790 ⇒ 00:25:21.719 Uttam Kumaran: like there’s there are like other things that people could be doing so. No hard feelings if that’s not interesting.
235 00:25:23.980 ⇒ 00:25:25.250 Atharv Gudi: Yeah, I think that
236 00:25:25.680 ⇒ 00:25:32.889 Atharv Gudi: I mean AI is quite broad. So I I was just wondering how that fits in here. And now I really get that? I think.
237 00:25:32.890 ⇒ 00:25:33.540 Uttam Kumaran: Yeah.
238 00:25:35.240 ⇒ 00:25:36.930 Atharv Gudi: Maybe one step at a time. So I think I’ll just
239 00:25:37.520 ⇒ 00:25:43.069 Atharv Gudi: start off with the analytics engineering discipline and then maybe do the AI part later.
240 00:25:43.370 ⇒ 00:25:57.109 Uttam Kumaran: Yeah. And I also think you know that one customer facing example that I gave is something that fits pretty squarely within a mix of like data, engineering and analytics engineering. So that may be like a good, a good like project to take on
241 00:25:57.110 ⇒ 00:26:17.869 Uttam Kumaran: like throughout the summer is that one. And then we basically have the whole thing scoped. Project wise. So but there’s a lot of things that I don’t even know how to do it, snowflake that like we need to figure out basically so we would be like learning. I’d be learning pretty much alongside you, so that may be a great that honestly may be a great like bridge between everything. So maybe we drive towards.
242 00:26:18.000 ⇒ 00:26:21.910 Uttam Kumaran: But we could drive towards that and I’m just gonna put that in the notes here.
243 00:26:22.460 ⇒ 00:26:23.090 Atharv Gudi: Oh, yeah.
244 00:26:47.210 ⇒ 00:26:48.716 Uttam Kumaran: Okay, cool.
245 00:26:49.520 ⇒ 00:27:06.330 Uttam Kumaran: So again, I know you mentioned that like, you’re, you operate a lot better working directly with folks and shadowing. So go through these as as you wish, like, I think these are really great, and some of these you’re going to need to know the fundamentals of Dbt, otherwise it’s going to be like we’re we’re speaking Spanish.
246 00:27:06.900 ⇒ 00:27:07.400 Atharv Gudi: Okay.
247 00:27:08.050 ⇒ 00:27:08.700 Uttam Kumaran: But
248 00:27:09.370 ⇒ 00:27:24.810 Uttam Kumaran: I would say at the same time, both me and Brian have been using Dbt. For years, and both of us have taught Dbt. Several, several several times to people. So you’re in good hands there. But make sure your your local environment is all set up.
249 00:27:26.090 ⇒ 00:27:30.919 Uttam Kumaran: The other thing that I’m going to tell to all the team today is to send me
250 00:27:31.331 ⇒ 00:27:34.649 Uttam Kumaran: github usernames set up github with your brain for gmail.
251 00:27:34.680 ⇒ 00:27:45.670 Uttam Kumaran: But also, I’m gonna be I’m gonna be asking. I’m gonna be mentioning. I know some people have asked like, how do I wanna put brain forge on linkedin or brain forge on the resume. So I’ll be sending a note about that.
252 00:27:45.920 ⇒ 00:27:46.300 Atharv Gudi: No i-.
253 00:27:46.300 ⇒ 00:27:58.549 Uttam Kumaran: As well for a resume for linkedin. We’re gonna do a big like marketing push in, maybe like 2 weeks. So I’m kind of gonna wait for that to kind of hit so that everybody can do update at the same time and
254 00:27:58.580 ⇒ 00:28:02.380 Uttam Kumaran: have something to share about like, hey, go to the website to check us out. And things like that.
255 00:28:03.090 ⇒ 00:28:03.780 Atharv Gudi: So him.
256 00:28:04.020 ⇒ 00:28:04.920 Uttam Kumaran: But yeah.
257 00:28:05.900 ⇒ 00:28:07.770 Uttam Kumaran: that’s that’s basically it.
258 00:28:09.520 ⇒ 00:28:10.730 Atharv Gudi: Well, yeah, till
259 00:28:11.150 ⇒ 00:28:11.900 Atharv Gudi: I’m
260 00:28:12.300 ⇒ 00:28:16.710 Atharv Gudi: just to like recap. I just wanna read. Make sure everything I’ve got everything in
261 00:28:18.360 ⇒ 00:28:22.059 Atharv Gudi: There’s an engineering onboarding that’s with for Vs code.
262 00:28:22.480 ⇒ 00:28:24.400 Atharv Gudi: And just yeah.
263 00:28:24.400 ⇒ 00:28:26.491 Uttam Kumaran: Yeah, has Vs code has like,
264 00:28:27.490 ⇒ 00:28:32.290 Uttam Kumaran: as like basically installing Github desktop. The Dbt cli which
265 00:28:32.330 ⇒ 00:28:36.270 Uttam Kumaran: you’ll go through about. You’ll go through this in the Dbt fundamentals. Course.
266 00:28:36.973 ⇒ 00:28:37.800 Uttam Kumaran: And then.
267 00:28:38.300 ⇒ 00:28:41.709 Uttam Kumaran: like, I have to get everybody onto one password for credentials.
268 00:28:42.760 ⇒ 00:28:47.249 Uttam Kumaran: The stuff on the bottom. It’s it’s probably more for full time. Folks
269 00:28:47.940 ⇒ 00:28:50.459 Uttam Kumaran: so. But there is some helpful stuff on here.
270 00:28:52.910 ⇒ 00:28:54.480 Atharv Gudi: Okay. So
271 00:28:55.470 ⇒ 00:29:04.480 Atharv Gudi: so if I had to approach this, so the SQL. The thresher will be having tomorrow. I think I’ll be fine with that because I’m already comfortable with SQL. As still to view it.
272 00:29:04.930 ⇒ 00:29:09.331 Atharv Gudi: and then the rest of the the Snowflake Dbt, and the engineering thing.
273 00:29:10.140 ⇒ 00:29:13.030 Atharv Gudi: in what order. Do you recommend that I go.
274 00:29:13.790 ⇒ 00:29:18.100 Uttam Kumaran: Yeah, I would. I would start with Snowflake first.st
275 00:29:18.370 ⇒ 00:29:19.460 Uttam Kumaran: Okay, I’m
276 00:29:20.050 ⇒ 00:29:23.299 Uttam Kumaran: and then as soon as you’re able to get into Snowflake
277 00:29:23.390 ⇒ 00:29:25.729 Uttam Kumaran: kind of create tables and databases.
278 00:29:25.940 ⇒ 00:29:28.019 Uttam Kumaran: Just jump into the Dbt. Learn.
279 00:29:28.120 ⇒ 00:29:31.589 Uttam Kumaran: So let me let me put that here at the bottom.
280 00:29:31.780 ⇒ 00:29:32.950 Uttam Kumaran: So
281 00:29:52.830 ⇒ 00:29:58.299 Uttam Kumaran: so these are the big things. And I also need to gather user names.
282 00:30:09.650 ⇒ 00:30:10.340 Atharv Gudi: Okay.
283 00:30:11.200 ⇒ 00:30:12.220 Uttam Kumaran: General action.
284 00:30:12.510 ⇒ 00:30:16.320 Uttam Kumaran: Yeah, you. If you have a github, I can use that also.
285 00:30:17.010 ⇒ 00:30:17.720 Atharv Gudi: Oh, Amy.
286 00:30:18.280 ⇒ 00:30:21.530 Atharv Gudi: I do have a data, but I don’t remember its password, so I might.
287 00:30:22.716 ⇒ 00:30:23.670 Uttam Kumaran: Hi, guys.
288 00:30:24.210 ⇒ 00:30:27.701 Uttam Kumaran: either way or not. I think it’s I think I think it’s I think it’s like,
289 00:30:29.470 ⇒ 00:30:37.250 Uttam Kumaran: it’s nice, because if you want to keep, like all of your commit history in one place, but otherwise people people here like
290 00:30:37.890 ⇒ 00:30:43.459 Uttam Kumaran: Alright just create one for brain forge. So that’s also fine doesn’t really matter.
291 00:30:46.000 ⇒ 00:30:46.610 Atharv Gudi: Okay.
292 00:30:46.860 ⇒ 00:30:49.110 Atharv Gudi: I’ll try to get the Github username.
293 00:30:49.660 ⇒ 00:30:56.079 Atharv Gudi: I’ll try to see if I can get my own account and the Zendesk AI project.
294 00:30:56.740 ⇒ 00:31:03.139 Uttam Kumaran: Yeah. So this one will take us something, maybe, like, maybe early next week, like, I think it’ll be a little bit.
295 00:31:03.290 ⇒ 00:31:07.600 Uttam Kumaran: I want you to have a good understanding of Snowflake and Dbt first, st
296 00:31:08.107 ⇒ 00:31:10.939 Uttam Kumaran: before I kind of like give you the overview of this.
297 00:31:10.970 ⇒ 00:31:12.420 Uttam Kumaran: because
298 00:31:12.440 ⇒ 00:31:14.289 Uttam Kumaran: this involves stuff that’s like
299 00:31:14.730 ⇒ 00:31:19.339 Uttam Kumaran: on top of Snowflake. That’s like brand brand new that just came out like, maybe like 3 weeks ago.
300 00:31:19.590 ⇒ 00:31:27.470 Uttam Kumaran: So I want you to. I mean, I’m not. I’m not worried in your picking up Snowflake and things like that. But I I don’t want to inundate you with like everything right now.
301 00:31:27.920 ⇒ 00:31:34.149 Uttam Kumaran: but I’ll just make sure that everything’s ready for this, and me and me. You and Nico and Brian will go through this.
302 00:31:35.900 ⇒ 00:31:36.530 Atharv Gudi: Oh, yeah.
303 00:31:39.600 ⇒ 00:31:40.450 Atharv Gudi: hello!
304 00:31:40.590 ⇒ 00:31:42.740 Atharv Gudi: Think that’s all the questions I had.
305 00:31:43.390 ⇒ 00:31:53.270 Uttam Kumaran: Okay, cool and then slack in internal engineering, or me or Brian about anything on the dB side. They’ll be worried.
306 00:31:53.310 ⇒ 00:31:57.110 Uttam Kumaran: The internal engineering just for any sort of conversation, so don’t be worried about it.
307 00:31:57.110 ⇒ 00:31:57.480 Atharv Gudi: Okay.
308 00:31:57.480 ⇒ 00:31:59.060 Uttam Kumaran: Spam development or anything.
309 00:31:59.230 ⇒ 00:32:01.430 Uttam Kumaran: You should be totally fine.
310 00:32:02.000 ⇒ 00:32:09.239 Uttam Kumaran: And then I’m gonna go ahead and schedule that sequel to meeting for tomorrow morning. So you should see that pop up just after a call.
311 00:32:10.030 ⇒ 00:32:13.009 Atharv Gudi: Alright, and the meeting with us and Brian
312 00:32:13.380 ⇒ 00:32:14.940 Atharv Gudi: Friday tentatively.
313 00:32:15.250 ⇒ 00:32:18.020 Uttam Kumaran: Yeah, I’m going to plan that for
314 00:32:19.350 ⇒ 00:32:26.039 Uttam Kumaran: I’m gonna plan that for Thursday or Friday. I need to call him today about some stuff. He’s pretty heads down on some work.
315 00:32:26.090 ⇒ 00:32:27.530 Uttam Kumaran: but I just want to give him like
316 00:32:27.620 ⇒ 00:32:33.244 Uttam Kumaran: like at least a day or 2 to kind of like if he wants to prepare anything but either way I’ll
317 00:32:33.570 ⇒ 00:32:35.729 Uttam Kumaran: I’ll connect you all on slack.
318 00:32:36.090 ⇒ 00:32:37.110 Atharv Gudi: Alright, cool.
319 00:32:40.310 ⇒ 00:32:47.820 Uttam Kumaran: Okay, cool. You’re getting the I’m glad you picked the a stuff cause. That’s like, that’s my world. So it’s really fun. I think it’s like.
320 00:32:47.820 ⇒ 00:32:50.439 Atharv Gudi: Got my very beginning. So I think.
321 00:32:51.930 ⇒ 00:32:59.590 Uttam Kumaran: Yeah, I think you know, I just didn’t know where everybody was and like, does it on our sequel journey. And I’m like, you don’t know sequel. Then everything’s gonna be hard here.
322 00:32:59.600 ⇒ 00:33:09.719 Uttam Kumaran: So I’m basically like, Okay, people want to learn sequel. 1st do that, and then we’ll get them in. I think everybody’s going to be dirt, probably. Do they stuff after a month?
323 00:33:10.588 ⇒ 00:33:14.020 Uttam Kumaran: Follow any of your footsteps? So yeah.
324 00:33:16.530 ⇒ 00:33:17.340 Atharv Gudi: Perfect
325 00:33:18.360 ⇒ 00:33:21.119 Atharv Gudi: alright. Well, then, I’ll talk to you tomorrow. Then.
326 00:33:21.390 ⇒ 00:33:24.323 Uttam Kumaran: Yeah. Yeah. Get some rest. Welcome home.
327 00:33:25.340 ⇒ 00:33:26.270 Atharv Gudi: Thank you.
328 00:33:26.730 ⇒ 00:33:27.250 Atharv Gudi: Okay. I mean.
329 00:33:27.250 ⇒ 00:33:28.570 Uttam Kumaran: Okay. I’ll talk to you soon.
330 00:33:28.570 ⇒ 00:33:30.060 Atharv Gudi: See tomorrow. Bye.