Meeting Title: Omni Data Exploration Sync Date: 2026-03-13 Meeting participants: Uttam Kumaran, Nandika Jhunjhunwala
WEBVTT
1 00:00:26.190 ⇒ 00:00:27.600 Uttam Kumaran: Hello!
2 00:00:28.260 ⇒ 00:00:29.660 Nandika Jhunjhunwala: Hi, how’s it going?
3 00:00:29.660 ⇒ 00:00:30.890 Uttam Kumaran: Good, how are you?
4 00:00:31.180 ⇒ 00:00:33.869 Nandika Jhunjhunwala: Good, yeah, I know you’re super busy, so thank you for your time.
5 00:00:33.870 ⇒ 00:00:38.100 Uttam Kumaran: Oh, of course! Yeah, let’s… let’s go through it. I know it can be, like, kind of weird to…
6 00:00:38.260 ⇒ 00:00:40.389 Uttam Kumaran: Where I also want to make sure that, like.
7 00:00:40.570 ⇒ 00:00:46.079 Uttam Kumaran: You’re… you’re not seeing, like, too much stuff in there, and that makes it hard to query, so…
8 00:00:46.080 ⇒ 00:00:49.099 Nandika Jhunjhunwala: Like, happy to help, yeah. Yeah.
9 00:00:49.270 ⇒ 00:01:06.090 Nandika Jhunjhunwala: The way I’m thinking about going about this is, like, I can share my screen and, like, show you, like, what I’ve been running into, like, common issues, how I’ve been, like, using the platform, and if you have any tips on, like, the best way to navigate the platform, and stuff like that, so… Cool.
10 00:01:06.670 ⇒ 00:01:09.470 Nandika Jhunjhunwala: Login, yeah. How’s your week?
11 00:01:09.830 ⇒ 00:01:27.000 Uttam Kumaran: It’s good! Yeah, I mean, I think, like, we… I’m just glad we… this… this GTM dashboard, we’re, like, lined up with equals, but it’s good that, like, people are like, well, was equals even right? I’m like, that’s good, that’s, like, a good thing. It’s like a good thing for us to, like, figure out that we’re all on the same page.
12 00:01:27.220 ⇒ 00:01:33.470 Uttam Kumaran: And then we’re, we’re on, we’re starting on all this, like, all the Salesforce stuff is in progress right now, too, so it’s good.
13 00:01:34.050 ⇒ 00:01:41.370 Nandika Jhunjhunwala: No, I think it’s great, like, it’s getting people internally aligned on metrics, because nobody has one source of truth they’re pulling from, so…
14 00:01:41.370 ⇒ 00:01:42.090 Uttam Kumaran: Yeah.
15 00:01:42.090 ⇒ 00:01:46.980 Nandika Jhunjhunwala: Anything people are figuring out that, oh, wait, like, this is, like, stuff we need to, like, talk about.
16 00:01:46.980 ⇒ 00:01:47.890 Uttam Kumaran: Yes.
17 00:01:47.890 ⇒ 00:01:48.850 Nandika Jhunjhunwala: Yeah.
18 00:01:50.620 ⇒ 00:01:55.250 Nandika Jhunjhunwala: Yeah, cool, so… I’ll go share my screen.
19 00:01:56.130 ⇒ 00:01:57.580 Nandika Jhunjhunwala: Okay…
20 00:02:03.030 ⇒ 00:02:04.430 Nandika Jhunjhunwala: There we go.
21 00:02:05.220 ⇒ 00:02:06.940 Nandika Jhunjhunwala: Let me know if you can see my screen.
22 00:02:07.340 ⇒ 00:02:08.160 Uttam Kumaran: Yes.
23 00:02:08.160 ⇒ 00:02:14.849 Nandika Jhunjhunwala: Okay. So the way I’ll show you, like, what I’ve been doing is, like, I click on this.
24 00:02:15.280 ⇒ 00:02:26.540 Nandika Jhunjhunwala: And then, because I know the Salesforce analysis is from, like, a raw export, which is, like, a little old data, I wanted to query, like, the main or, like, the raw data.
25 00:02:26.540 ⇒ 00:02:27.300 Uttam Kumaran: Yes.
26 00:02:27.630 ⇒ 00:02:30.269 Nandika Jhunjhunwala: So I just wanted to ask you all.
27 00:02:32.550 ⇒ 00:02:50.740 Nandika Jhunjhunwala: And I would see, like, two options, and, like, I would love, like, your input on this. Like, one is, like, querying with the interactive UI, and then the second is just, like, writing queries. So for me, querying with the interactive UI didn’t feel as intuitive, so I was just gonna, like, try and write, like, queries.
28 00:02:51.390 ⇒ 00:02:54.240 Nandika Jhunjhunwala: And then what happened here was, like.
29 00:02:55.540 ⇒ 00:02:59.940 Nandika Jhunjhunwala: So, I’m just trying to understand what the exact flow of, like.
30 00:03:00.360 ⇒ 00:03:00.860 Uttam Kumaran: Yeah.
31 00:03:00.860 ⇒ 00:03:05.119 Nandika Jhunjhunwala: It’s called Creating Dashboards off of, like, Data Should Look Like.
32 00:03:05.460 ⇒ 00:03:16.700 Uttam Kumaran: Yes, so, like, I think one thing that’s… that… and it’s kind of sort of what I think we were trying to convey, is the raw tables are just gonna have, like, way too much stuff. So…
33 00:03:18.260 ⇒ 00:03:35.870 Uttam Kumaran: for the most part, except for folks, like, on the data team, we really want people to be querying from, ideally, model topics, or from, like, the prod Marts schema. So you should see prod, like, in there, right? So prod Marts is, like, what we would prefer, because this…
34 00:03:35.870 ⇒ 00:03:47.759 Uttam Kumaran: has all of our, like, logic. I think you’re still… you’re starting to just look, like, is your intention on the raw side just to go see in some of those, or give me a sense of, like, what the outcome is, and I can kind of help you think about it.
35 00:03:48.210 ⇒ 00:04:01.670 Nandika Jhunjhunwala: Absolutely. I actually created some, like, queries, so I’ll show you those as well. Great. It was off of raw data, not the marts, because I think the data in the marts is missing the data we needed.
36 00:04:01.670 ⇒ 00:04:02.000 Uttam Kumaran: S.
37 00:04:02.000 ⇒ 00:04:05.709 Nandika Jhunjhunwala: went to raw data, because I’m sure you’re, like, in the process of modeling things.
38 00:04:05.710 ⇒ 00:04:06.350 Uttam Kumaran: Yes.
39 00:04:07.190 ⇒ 00:04:08.159 Uttam Kumaran: Okay, makes sense.
40 00:04:08.160 ⇒ 00:04:09.510 Nandika Jhunjhunwala: Yes, which is why.
41 00:04:09.890 ⇒ 00:04:27.149 Nandika Jhunjhunwala: But yeah, this is, like, this was, like, a good way for me to, like, also, like, call check with the sales team to figure out, like, are we having the model that we care about? So, yeah, so I was just, like, so suppose, like, I write a query, like, select…
42 00:04:27.590 ⇒ 00:04:29.620 Nandika Jhunjhunwala: All prone.
43 00:04:33.690 ⇒ 00:04:36.460 Nandika Jhunjhunwala: user, or something, and then I run it.
44 00:04:40.470 ⇒ 00:04:41.020 Nandika Jhunjhunwala: So, like.
45 00:04:41.020 ⇒ 00:04:58.830 Uttam Kumaran: And then I guess, like, every step of the way, give me a… like, give me a first sense of, like, what… what your… like, what your ask is, or, like, give me a sense of the challenge you’re trying to solve. Is it, like, purely exploratory? Is it like, okay, it’s not modeled yet, but I think I can still get to this question? Like, that would just help me frame it.
46 00:04:59.180 ⇒ 00:05:14.269 Nandika Jhunjhunwala: Yeah, no, great question. So, my approach at Omni is, like, okay, it’s not modeled yet, but I want to go and explore it from the sense of, like, getting familiar with the platform, and exploring the data. I’m okay with, like, seeing too many things like that.
47 00:05:14.270 ⇒ 00:05:25.090 Uttam Kumaran: Okay, okay, great. Doesn’t bother me, that’s okay. Okay, so I think, like, I think this is, like, a good place to start. I mean, I almost may even suggest, like, you could go do this in Mother Duck. I think the.
48 00:05:25.090 ⇒ 00:05:25.490 Nandika Jhunjhunwala: Yeah.
49 00:05:25.730 ⇒ 00:05:26.900 Uttam Kumaran: Teachers are…
50 00:05:27.020 ⇒ 00:05:44.830 Uttam Kumaran: are a little bit nicer. It’s… it’s sort of your… it’s like, if you’re just querying raw data, it’s kind of, like, up to your ergonomics, yeah, like, what you prefer. The nice thing about doing it at Omni is, like, you can get it into a dashboard, but again, like, for this exploratory thing, like.
51 00:05:45.400 ⇒ 00:05:58.519 Uttam Kumaran: I would say it’s not as relevant, because you’re not gonna, like, create the dashboard on, like, the raw data. So, like, yeah, if you have, like, I can… so, I don’t know if you… did you try Mother Duck at all? Did you find it, like, any…
52 00:05:59.020 ⇒ 00:06:00.319 Uttam Kumaran: Like, nicer at all, or…
53 00:06:00.320 ⇒ 00:06:04.280 Nandika Jhunjhunwala: It’s pretty, like… it’s like notebooks on…
54 00:06:04.280 ⇒ 00:06:04.810 Uttam Kumaran: Yes.
55 00:06:04.810 ⇒ 00:06:06.180 Nandika Jhunjhunwala: Warehouse.
56 00:06:06.510 ⇒ 00:06:09.859 Uttam Kumaran: Okay. Put a notebooks on the warehouse. Yeah, yeah, yeah.
57 00:06:09.860 ⇒ 00:06:12.730 Nandika Jhunjhunwala: So, I don’t think that’s, like, a challenge for me to navigate.
58 00:06:12.730 ⇒ 00:06:13.390 Uttam Kumaran: Okay.
59 00:06:13.530 ⇒ 00:06:20.480 Nandika Jhunjhunwala: But more so, like, going back to my question, like, suppose I want to save this query and come back to it for future use.
60 00:06:20.480 ⇒ 00:06:20.860 Uttam Kumaran: Yeah.
61 00:06:20.860 ⇒ 00:06:27.230 Nandika Jhunjhunwala: I think, like, I asked Demi also previously, like, so if I say save as a query view, and I save it, like, test…
62 00:06:31.410 ⇒ 00:06:36.089 Nandika Jhunjhunwala: And then I save it in my documents.
63 00:06:36.840 ⇒ 00:06:41.349 Nandika Jhunjhunwala: Or, I guess it’s asking me to, like, I don’t know if we’re getting saved.
64 00:06:41.550 ⇒ 00:06:47.330 Nandika Jhunjhunwala: like, will it just, like, show up here? Because, like, that’s previously what I was having issues with.
65 00:06:47.450 ⇒ 00:06:50.900 Nandika Jhunjhunwala: Like, my documents.
66 00:06:51.900 ⇒ 00:06:53.760 Uttam Kumaran: Yeah, you should see it there, yes.
67 00:06:53.760 ⇒ 00:06:54.470 Nandika Jhunjhunwala: Thanks.
68 00:06:54.730 ⇒ 00:06:58.570 Nandika Jhunjhunwala: Okay, and then this is what I was doing yesterday.
69 00:06:59.200 ⇒ 00:07:00.060 Nandika Jhunjhunwala: Perfect.
70 00:07:00.540 ⇒ 00:07:03.300 Nandika Jhunjhunwala: Yeah, just, like, just very basic stuff.
71 00:07:03.300 ⇒ 00:07:04.400 Uttam Kumaran: Yeah, yeah, yeah.
72 00:07:05.240 ⇒ 00:07:07.140 Nandika Jhunjhunwala: Yeah, so…
73 00:07:07.140 ⇒ 00:07:10.919 Uttam Kumaran: This is actually, like, awesome, because this is where, like, I think my hesitation is, like.
74 00:07:11.080 ⇒ 00:07:28.260 Uttam Kumaran: I just wanna, like, to hear that you’re like, yeah, I’m just gonna go poke around. And I actually don’t mind you, like, building it off raw, because it’s… it’s just gonna actually just… you’re gonna kind of see… you’re gonna be able to do the joins and, like, find some nuance that, like, we’re gonna end up either skipping over and coming back to in the modeling phase.
75 00:07:28.260 ⇒ 00:07:32.859 Uttam Kumaran: Or, like, we’re just gonna, like, make our best guess. So, like, I have actually no problem…
76 00:07:33.090 ⇒ 00:07:38.439 Uttam Kumaran: I have no problem with this at all, like, and I… it’s just… I just wanted to know that this is what we’re doing.
77 00:07:39.150 ⇒ 00:07:47.339 Nandika Jhunjhunwala: Sounds good. So… so, one thing about Omni I see is, like, oh, safety workbook. So, I was trying to understand, like, how.
78 00:07:47.340 ⇒ 00:07:50.670 Uttam Kumaran: Yeah, the, like, taxonomy of the different objects, so…
79 00:07:50.670 ⇒ 00:07:51.010 Nandika Jhunjhunwala: S.
80 00:07:51.010 ⇒ 00:07:54.660 Uttam Kumaran: It’s a little bit confusing, like, I’m not sure if you’re, like, a…
81 00:07:55.040 ⇒ 00:08:01.180 Uttam Kumaran: I’m not, like, a very big, like, I’ll read all the docs first, I just sort of, like, go mess around, and then I, like, come back, so…
82 00:08:01.420 ⇒ 00:08:09.519 Uttam Kumaran: for me, it’s helpful to know, like, the terminology, but basically, have you used, like, Tableau before, by chance?
83 00:08:09.520 ⇒ 00:08:10.740 Nandika Jhunjhunwala: Briefly, yeah.
84 00:08:10.740 ⇒ 00:08:23.689 Uttam Kumaran: So, like, think about a workbook. I think, like, explanation of a good workbook is, like, almost like an Excel workbook, where you have, like, sheets, and then you have, like, the dashboard. And so, the way Omni works is each of these is, like,
85 00:08:23.780 ⇒ 00:08:41.539 Uttam Kumaran: it’s like a view within a larger dashboard project, and so you can actually edit the dashboard, edit some of these things, but when you go into a view, it’s almost like editing a sheet. So if you click on edit at the top right, and then you go ahead and just, like.
86 00:08:41.780 ⇒ 00:08:44.119 Uttam Kumaran: You can hover over…
87 00:08:45.020 ⇒ 00:08:54.500 Uttam Kumaran: If you hover over one of the cells that calls by month, you’ll see that there is, like, a little edit, but there’s a little three things at the top right, but you’re gonna see Edit Chart and Edit and Workbook.
88 00:08:54.540 ⇒ 00:09:12.379 Uttam Kumaran: So this is, like, purely cosmetic, but when you go to Edit in Workbook, this is really gonna be more about, like, editing the raw SQL, right? And so, basically what you’re seeing here is, yes, like, you can go from SQL, or you can go from joining things together, and all that ends up into this, like.
89 00:09:12.520 ⇒ 00:09:20.689 Nandika Jhunjhunwala: the workbook, like, the dashboard. Oh, so the workbook just has multiple, like, SQL queries, and each SQL query.
90 00:09:20.690 ⇒ 00:09:29.140 Uttam Kumaran: Yeah, so they want… they make it easy for you to pull in, like, a view that’s written by SQL, or a view that’s, like, selecting the metrics. So…
91 00:09:29.440 ⇒ 00:09:34.529 Uttam Kumaran: in this… in this sense, right now, you wrote… I think you… you must have wrote… wrote this query.
92 00:09:34.590 ⇒ 00:09:53.729 Uttam Kumaran: So now that is just a sequel, but, like, you can also create new, like, views where you’re just selecting the metrics, right? So if you go to… in the GTM dashboard, you’ll see all of those are actually built by selecting things. Like, we’re selecting these views, creating these metrics, and bringing them in. You can also just
93 00:09:53.830 ⇒ 00:10:03.219 Uttam Kumaran: take a raw SQL that works and just, like, create a viz on top of it. Ultimately, though, in the backend, yes, everything gets compiled to SQL that’s hitting Mother Duck.
94 00:10:03.380 ⇒ 00:10:05.519 Uttam Kumaran: But it’s sort of… this is more about, like.
95 00:10:05.670 ⇒ 00:10:14.239 Uttam Kumaran: again, it’s sort of ergonomics. There’s a lot of flexibility, so they make it open, whether you want to just click on the metrics you want, or… right? Because… because this isn’t modeled, right?
96 00:10:14.420 ⇒ 00:10:19.320 Uttam Kumaran: it’s… this is probably the primary way that you’re going to be able to do it through SQL.
97 00:10:20.670 ⇒ 00:10:24.660 Nandika Jhunjhunwala: Okay, so this… sorry, I’m still wrapping my head around.
98 00:10:24.660 ⇒ 00:10:25.890 Uttam Kumaran: No, no, no, no, please, yeah.
99 00:10:25.890 ⇒ 00:10:30.499 Nandika Jhunjhunwala: Yeah, so when I click on this, like, top workbook.
100 00:10:30.680 ⇒ 00:10:38.329 Nandika Jhunjhunwala: it just opens, like, one SQL query, which just, like, calls total BDR calls,
101 00:10:38.710 ⇒ 00:10:43.750 Nandika Jhunjhunwala: So, should I add more SQL queries here, or, like, what is the…
102 00:10:44.560 ⇒ 00:10:58.270 Uttam Kumaran: Though, I think it’s two things. If you want… if you want to create a net new view, then you create a new thing at the bottom. So you can hit plus at the bottom, the bottom left, and then just add a new, query.
103 00:10:58.520 ⇒ 00:11:01.989 Nandika Jhunjhunwala: Oh, okay. And these are all queries in this workflow.
104 00:11:01.990 ⇒ 00:11:03.919 Uttam Kumaran: In this workbook, correct.
105 00:11:04.860 ⇒ 00:11:05.180 Nandika Jhunjhunwala: God.
106 00:11:05.180 ⇒ 00:11:16.860 Uttam Kumaran: So ideally, like, if you think about it, like, one even step further, you may use a view in multiple workbooks, right? And so it allows for this, like, composability of things.
107 00:11:16.860 ⇒ 00:11:27.469 Uttam Kumaran: But yes, like, once you’re… once one query is… I assign, like, one query to one tile. Like, tile view, like, those are all… assign one query, and then if you wanted to do another.
108 00:11:27.530 ⇒ 00:11:28.490 Uttam Kumaran: Viz?
109 00:11:28.590 ⇒ 00:11:30.630 Uttam Kumaran: Just create a new view.
110 00:11:31.510 ⇒ 00:11:39.589 Nandika Jhunjhunwala: Okay, so that’s, like, the other thing I noticed as well, like, when I was, like, trying to write SQL queries, like, I didn’t know what the fields were named as.
111 00:11:39.590 ⇒ 00:11:48.659 Uttam Kumaran: Yeah, so that’s gonna be the… that’s the… that, this is where I’m… I’m almost, like… I would suggest writing it in Mother Duck first.
112 00:11:48.660 ⇒ 00:11:49.390 Nandika Jhunjhunwala: Yeah.
113 00:11:49.390 ⇒ 00:11:52.400 Uttam Kumaran: because it’s easier to write SQL in that environment.
114 00:11:52.400 ⇒ 00:11:53.290 Nandika Jhunjhunwala: Yeah.
115 00:11:53.290 ⇒ 00:12:04.830 Uttam Kumaran: and then just bring it into here to do the visualization, especially if you’re modeling off raw data, because you’ll have to do that transition either way. Because, yes, like, some of these fields
116 00:12:04.910 ⇒ 00:12:17.599 Uttam Kumaran: they don’t have any of the sort of… like, Salesforce, again, they’ll have these double underscores, and C, and all this nonsense. We delete… we, like, rename all that as it gets up, you know? So, that’s just the perils of, like.
117 00:12:18.220 ⇒ 00:12:33.679 Uttam Kumaran: not having the model data, but again, like, if you just have, like, a pinpoint thing that you’re, like… for example, even if you’re like, hey, you guys are modeling, but I want to join accounts and opportunities together, you can just say, like, what’s the join key, or, like, can someone review this query? Like, because we’ll… that’s…
118 00:12:33.850 ⇒ 00:12:37.779 Uttam Kumaran: Basically, we are writing that in order to build the models anyway, so…
119 00:12:38.130 ⇒ 00:12:38.690 Nandika Jhunjhunwala: Yeah.
120 00:12:38.690 ⇒ 00:12:39.250 Uttam Kumaran: Yeah.
121 00:12:39.990 ⇒ 00:12:44.089 Nandika Jhunjhunwala: No, that makes sense, and, like, I know I’m not interacting with it, like, the way you intended.
122 00:12:44.090 ⇒ 00:12:50.990 Uttam Kumaran: No, no, no, no, no, and again, like, I would rather people in this phase actually use it like this. It’s not often times that we…
123 00:12:51.090 ⇒ 00:13:09.339 Uttam Kumaran: have clients… it’s usually there’s, like, everything just waits until the end. I actually prefer people to be trying things in raw data. I think my only caution, and this is just, like, scar tissue, is, like, if something gets published from raw data and, like, gets into the business, and it’s missing, like.
124 00:13:09.760 ⇒ 00:13:11.469 Uttam Kumaran: Something we would have modeled.
125 00:13:11.470 ⇒ 00:13:11.820 Nandika Jhunjhunwala: Yep.
126 00:13:11.820 ⇒ 00:13:17.899 Uttam Kumaran: And that’s, like, that’s just why we kind of try to think about, like, a governed layer. But again, like, I know that
127 00:13:17.990 ⇒ 00:13:35.889 Uttam Kumaran: you’re scrappy, and we’re figuring it out. So, like, it’s, like, not as much of a worry, because also, it’s not like the data is as complex, but for example, we’re talking about, like, ARR contraction, right? Who… you wouldn’t go to the raw data and be like, yeah, like, we needed to add a 6-month overlap, and this could, like…
128 00:13:35.890 ⇒ 00:13:43.449 Uttam Kumaran: none of that logic is present in the raw data, so if you would have just said sum of ARR column, it would be totally off.
129 00:13:43.560 ⇒ 00:13:50.219 Uttam Kumaran: And if that ends up in a dashboard, and then there’s two numbers, now people, like, just lose trust. So that’s, like, the biggest thing.
130 00:13:50.680 ⇒ 00:13:56.450 Nandika Jhunjhunwala: For sure. Got it. That makes sense. The other thing that I was, like, looking at was…
131 00:13:56.450 ⇒ 00:14:00.130 Uttam Kumaran: I know you talked about adding these toggles. Yes.
132 00:14:00.130 ⇒ 00:14:05.799 Nandika Jhunjhunwala: So, I wasn’t sure how to, like, marry that with my queries, because I just added this and it doesn’t mean anything.
133 00:14:05.800 ⇒ 00:14:06.870 Uttam Kumaran: Yeah, so.
134 00:14:06.870 ⇒ 00:14:07.220 Nandika Jhunjhunwala: So, if you…
135 00:14:07.220 ⇒ 00:14:10.429 Uttam Kumaran: Yeah, if you go to add, and let’s just try to add a new filter.
136 00:14:10.430 ⇒ 00:14:11.220 Nandika Jhunjhunwala: Yep.
137 00:14:11.390 ⇒ 00:14:15.790 Uttam Kumaran: What this is gonna do is, right now,
138 00:14:15.890 ⇒ 00:14:28.190 Uttam Kumaran: this filter is going to be… so, this filter… I have to… I should actually just check whether you can do filters on the raw data, but basically, how this is gonna work is, if your…
139 00:14:28.350 ⇒ 00:14:34.869 Uttam Kumaran: If your view has that field in it, then it will get filtered by the filter.
140 00:14:35.970 ⇒ 00:14:42.069 Uttam Kumaran: Right, so… It’s asking you to pick right now. Yeah, it’s gonna ask you to pick, like, something from our modeled
141 00:14:42.230 ⇒ 00:14:43.300 Uttam Kumaran: tables.
142 00:14:43.300 ⇒ 00:14:46.479 Nandika Jhunjhunwala: And not from raw. I don’t see raw data in here, because it’s not…
143 00:14:46.480 ⇒ 00:14:47.090 Uttam Kumaran: Yeah.
144 00:14:47.640 ⇒ 00:14:49.040 Nandika Jhunjhunwala: Okay, okay.
145 00:14:49.230 ⇒ 00:14:49.780 Uttam Kumaran: Dap.
146 00:14:50.010 ⇒ 00:14:52.320 Nandika Jhunjhunwala: Because it doesn’t exist in a topic.
147 00:14:52.410 ⇒ 00:14:54.570 Uttam Kumaran: It won’t let you,
148 00:14:54.980 ⇒ 00:15:10.829 Uttam Kumaran: it won’t let you filter for it. And then, as you know, like, you can use a topic in multiples, so typically you’ll have, like, month, and then, like, customer ID, and ideally, if you want to filter the whole dashboard, those two fields need to be in every single tile, every single view.
149 00:15:12.100 ⇒ 00:15:20.899 Uttam Kumaran: And so that’s… that’s basically, like, what happens is you just make sure that column is there, and then it’ll… it’ll start to affect the… the ones that you want, yeah.
150 00:15:20.900 ⇒ 00:15:24.260 Nandika Jhunjhunwala: But if… And…
151 00:15:24.260 ⇒ 00:15:34.889 Uttam Kumaran: But one way of doing it, like, if you’re still testing, is, like, just filter everything to, like, 2026, or, like, and just put that in the SQL query. That way, you can sort of hardcode, like, while you’re exploring, and you don’t need to, like.
152 00:15:34.960 ⇒ 00:15:44.309 Uttam Kumaran: have to do the… think about, like, doing the dashboard pieces. You can be like, this is just 2026, I’m just exploring, or you can pick a month, or, like, one client, and always just use that throughout.
153 00:15:45.710 ⇒ 00:15:52.679 Nandika Jhunjhunwala: Cool. And then, what’s the difference between, like, Maine and the marts? Is Maine more so, like.
154 00:15:53.140 ⇒ 00:15:59.420 Uttam Kumaran: Yeah, I also need to go check. That’s a good question. Like, I will take that back, because that… you should only be…
155 00:15:59.680 ⇒ 00:16:03.030 Uttam Kumaran: seeing… Prawn marts.
156 00:16:03.520 ⇒ 00:16:11.420 Nandika Jhunjhunwala: Because I see, like, in Maine, I think there’s, like… maybe this is, like, more raw, raw data that you’ve modeled slightly.
157 00:16:11.990 ⇒ 00:16:14.960 Uttam Kumaran: Yeah, I’m just wondering why… yeah, I need to check…
158 00:16:15.660 ⇒ 00:16:23.390 Uttam Kumaran: you should ideally just see, prod more… can you click on views… all views and fields at the top, like, the little drop arrow?
159 00:16:23.550 ⇒ 00:16:30.579 Uttam Kumaran: To the left. Probably to the left, yeah. Still on the add a filter, but it says all views and fields.
160 00:16:30.580 ⇒ 00:16:31.940 Nandika Jhunjhunwala: Oh, yes, sorry.
161 00:16:34.210 ⇒ 00:16:38.280 Uttam Kumaran: Okay. Alright, yeah, I think… let me see why this is…
162 00:16:39.070 ⇒ 00:16:40.820 Uttam Kumaran: Why this is the way it is.
163 00:16:43.240 ⇒ 00:16:47.420 Uttam Kumaran: So yeah, I can take that and clean that up.
164 00:16:51.310 ⇒ 00:16:55.000 Nandika Jhunjhunwala: I just, like, I know Demi did tell me, I just, like.
165 00:16:55.300 ⇒ 00:17:01.140 Nandika Jhunjhunwala: I think I forgot what exactly the difference was, yeah.
166 00:17:01.140 ⇒ 00:17:06.780 Uttam Kumaran: Yeah, I think I was just bias to… to use… Prawn marts.
167 00:17:06.780 ⇒ 00:17:07.899 Nandika Jhunjhunwala: And I can check.
168 00:17:07.900 ⇒ 00:17:08.910 Uttam Kumaran: And clean that up.
169 00:17:10.790 ⇒ 00:17:12.880 Nandika Jhunjhunwala: And then the other question was, like.
170 00:17:14.040 ⇒ 00:17:17.359 Nandika Jhunjhunwala: how far are you in, like, your modeling process? Like.
171 00:17:18.099 ⇒ 00:17:22.899 Nandika Jhunjhunwala: How can we help, like, facilitate, like, context on, like, what needs to be modeled?
172 00:17:23.619 ⇒ 00:17:29.539 Uttam Kumaran: Yeah, so we have, I mean, the way it’s sort of working on,
173 00:17:30.029 ⇒ 00:17:34.039 Uttam Kumaran: context for modeling is, like, we’ve worked on these…
174 00:17:34.459 ⇒ 00:17:38.719 Uttam Kumaran: docs, and I can show you which has kind of the requirements for the dashboards.
175 00:17:39.129 ⇒ 00:17:41.089 Uttam Kumaran: Let me share one.
176 00:17:47.789 ⇒ 00:17:52.049 Uttam Kumaran: So, like, this is the second one that we’re, working on right now.
177 00:17:59.920 ⇒ 00:18:02.339 Nandika Jhunjhunwala: The users logged in.
178 00:18:03.870 ⇒ 00:18:05.769 Uttam Kumaran: So, there’s a couple ways, like…
179 00:18:06.260 ⇒ 00:18:08.740 Uttam Kumaran: I think this… this sort of view helps, because it…
180 00:18:08.740 ⇒ 00:18:09.230 Nandika Jhunjhunwala: Hmm.
181 00:18:09.230 ⇒ 00:18:10.679 Uttam Kumaran: There’s outlines and metrics.
182 00:18:10.680 ⇒ 00:18:12.129 Nandika Jhunjhunwala: Yeah. I kind of…
183 00:18:12.690 ⇒ 00:18:16.110 Uttam Kumaran: Preferred spreadsheet, but, like, this is basically what we need.
184 00:18:16.250 ⇒ 00:18:24.100 Uttam Kumaran: And so when we… when Demi and we met with, sort of, some people in the company, like, we kind of gathered these, but this is the main thing that we need.
185 00:18:24.250 ⇒ 00:18:36.459 Uttam Kumaran: So we just need, like, what are the nuances and, like, what are the questions we’re trying to answer? And then, as soon as, like, we have those models, which today we should have a few of the customer reporting ones out.
186 00:18:36.490 ⇒ 00:18:55.880 Uttam Kumaran: It’s sort of like, we just need to go through, like, QA together, which is like, you kind of look at a number, show, and then whoever is, like, owns that metric internally, they kind of give the stamp, which is sort of, like, what our conversation with Ryan was today, which is like, okay, Laura gave her stamp because it matches equals, but it’s clear that Ryan probably didn’t…
187 00:18:56.200 ⇒ 00:19:03.999 Uttam Kumaran: agree with what Equal said, but until, like, we pushed something out, there was no impetus for, sort of, like, even a discussion, right? So…
188 00:19:04.720 ⇒ 00:19:05.950 Nandika Jhunjhunwala: Makes sense.
189 00:19:05.950 ⇒ 00:19:12.560 Uttam Kumaran: But also, like, when the models are there, we can sort of… we could also push to you to do some of the dashboarding, because we also have…
190 00:19:12.750 ⇒ 00:19:23.570 Uttam Kumaran: we were gonna take liberty and do the dashboarding for this, like, so that’s part of, like, the reason I wanted to also chat is, like, I think it’s gonna be helpful for you to be able to take some of that
191 00:19:23.790 ⇒ 00:19:31.670 Uttam Kumaran: As well, especially because people are going to start asking for, like, I want to see this view, a little bit different, and it’s really easy. So we can, like, do the first pass.
192 00:19:31.910 ⇒ 00:19:46.610 Uttam Kumaran: But, like, that’s not a block or meaning. I’ll tell you as soon as… I’ll just be sure to tell you as soon as the models are ready for you to, like, query and look at, and then we can, like, work on the dashboard together, and really what I’m trying to do is push the team to get all the models out.
193 00:19:47.070 ⇒ 00:20:00.060 Nandika Jhunjhunwala: For sure. The other dashboard, I don’t know, like, where… what the timeline for that is, or if this has been, like, on your radar, but I think there’s, like, some Salesforce modeling that the go-to-market team,
194 00:20:00.060 ⇒ 00:20:00.590 Uttam Kumaran: Yes.
195 00:20:00.590 ⇒ 00:20:07.259 Nandika Jhunjhunwala: would love, and that’s, like, what I was trying to do, but obviously just, like, a very draft version of it. And…
196 00:20:08.000 ⇒ 00:20:23.759 Nandika Jhunjhunwala: my dashboard is private, but I can share it with you. But this is just, like, purely, like, Salesforce data that I’m, like, querying. It doesn’t require joins on anything, so that’s why I was using, like, also using the raw data, and, like, just wondering, like, how, like.
197 00:20:23.900 ⇒ 00:20:29.779 Nandika Jhunjhunwala: some of the tables that don’t require joins, how is that gonna sit in the data warehouse? And, like, are we.
198 00:20:29.780 ⇒ 00:20:37.429 Uttam Kumaran: Yeah, but I think the thing is, these tables do require joins. Like, we have to join between opportunity, contacts, accounts.
199 00:20:38.620 ⇒ 00:20:40.319 Nandika Jhunjhunwala: Okay. Yeah.
200 00:20:40.320 ⇒ 00:20:45.589 Uttam Kumaran: So they do require, like, a bit of modeling. Yeah. I mean, we are gonna connect this to…
201 00:20:45.710 ⇒ 00:20:49.480 Uttam Kumaran: We’re gonna connect this to our, like,
202 00:20:49.610 ⇒ 00:20:53.249 Uttam Kumaran: Our, like, user metrics to be, like, this is the default team.
203 00:20:53.420 ⇒ 00:21:02.319 Uttam Kumaran: But, like, yeah, I mean, I think this is, like, the next thing, so what I can do is, like, if that’s the most pressing thing, then I can just try to have our team push
204 00:21:02.420 ⇒ 00:21:14.409 Uttam Kumaran: Some type of clean versions of, like, a few of these, and, like, not worry… not, like, wait until we have, like, every single perfect metric, but just try to get, like, clean modeled versions of some of these out.
205 00:21:14.520 ⇒ 00:21:17.040 Uttam Kumaran: So that you can start to, like, build on top of them.
206 00:21:18.070 ⇒ 00:21:28.720 Nandika Jhunjhunwala: Modeling would be great, but I don’t want to, like… there’s no push. Okay. I guess more metrics, so to give you more context, I think that’s, like, go-to-market stand, like.
207 00:21:28.720 ⇒ 00:21:29.160 Uttam Kumaran: Yeah.
208 00:21:29.160 ⇒ 00:21:37.410 Nandika Jhunjhunwala: day, dashboard, but what I think the sales team wants to report on is, like, we have, like, a few BDRs.
209 00:21:37.410 ⇒ 00:21:42.660 Uttam Kumaran: Yeah. And they, like, make calls, and they make dials, they do, like… Yes.
210 00:21:42.660 ⇒ 00:21:53.710 Nandika Jhunjhunwala: sequences, and there’s, like, we were talking about… this is not, like, any, like, the highest priority by any means, but we… we wanted a dashboard to, like, measure, like, their activity.
211 00:21:53.710 ⇒ 00:21:55.430 Uttam Kumaran: activity. Yes. So, so, like…
212 00:21:55.430 ⇒ 00:22:03.819 Nandika Jhunjhunwala: dials, total dials by BDR by month, or, like, accounts owned, accounts with activity grouped by BDRs, and stuff like that.
213 00:22:03.820 ⇒ 00:22:08.889 Uttam Kumaran: Okay, so do you think it falls into, like… because this is sort of the one that we just…
214 00:22:08.980 ⇒ 00:22:27.889 Uttam Kumaran: a little bit of, like, the next version of some of the ARR stuff. This is more about, like, broad Salesforce performance. I don’t think we had anything focused on sales member performance. What we can do, though, is, like, on this, like, I can just expand it so, like, maybe at the bottom, we just, like, break
215 00:22:28.560 ⇒ 00:22:29.759 Uttam Kumaran: this apart.
216 00:22:30.710 ⇒ 00:22:38.379 Uttam Kumaran: At the bottom of the dash, For BDR performance.
217 00:22:38.380 ⇒ 00:22:40.470 Nandika Jhunjhunwala: Then send you, like, the metrics, too.
218 00:22:40.470 ⇒ 00:22:58.890 Uttam Kumaran: Yeah, exactly, yeah. If you want to send me, like, it’s basically, like, activity, like, and it’s… but it’s a lot of the same stuff, like, what is the average, like, close, like, what is the amount of deals on their plate, like, things like that. So, we can add it as a filter to the top, and then the bottom can just be focused on, like.
219 00:22:59.800 ⇒ 00:23:02.930 Uttam Kumaran: If you were to filter, it’ll just be really focused on the people.
220 00:23:02.930 ⇒ 00:23:12.609 Nandika Jhunjhunwala: Nice, yeah. No, that, and like, I think there’s a few tables that these views will not use, but the BDR activity you would use, like, the task table, the Salesforce task table.
221 00:23:12.610 ⇒ 00:23:13.880 Uttam Kumaran: Yes, yeah.
222 00:23:14.920 ⇒ 00:23:15.390 Uttam Kumaran: Okay.
223 00:23:15.390 ⇒ 00:23:18.719 Nandika Jhunjhunwala: So, like, and again, like, opportunity, account, user tables.
224 00:23:18.720 ⇒ 00:23:19.759 Uttam Kumaran: Yeah, yeah, yeah.
225 00:23:19.760 ⇒ 00:23:20.190 Nandika Jhunjhunwala: Yeah.
226 00:23:20.190 ⇒ 00:23:26.280 Uttam Kumaran: Maybe I can tag you here if you want to just, like, toss, like, any ideas, and then I’ll… I’ll add it another line here.
227 00:23:26.490 ⇒ 00:23:27.959 Nandika Jhunjhunwala: That would be great, thank you.
228 00:23:28.800 ⇒ 00:23:30.359 Uttam Kumaran: Okay, I could do that.
229 00:23:30.370 ⇒ 00:23:31.400 Nandika Jhunjhunwala: Yeah.
230 00:23:31.560 ⇒ 00:23:40.479 Nandika Jhunjhunwala: Now, the data exploration was fun, so I could, like, pinpoint how data’s organized, so… I think, like, personally for me, if I don’t look at the data, I don’t know what’s going on.
231 00:23:40.480 ⇒ 00:23:52.390 Uttam Kumaran: No, no, no, I’m the same way, so that’s why I’m, like, I think just keep going, like, and we’ll… we’ll catch up to you, like, really shortly. I think we… this… getting this GTM thing out, and, like, getting people to start, like, aligning, because the ARR…
232 00:23:52.720 ⇒ 00:24:02.799 Uttam Kumaran: the ARR thing is gonna show up, like, everywhere, and so I’m just, like, want to solidify anything with a dollar sign, because everything is gonna cascade from, like, these definitions.
233 00:24:02.800 ⇒ 00:24:03.230 Nandika Jhunjhunwala: You’re fine.
234 00:24:03.310 ⇒ 00:24:06.090 Uttam Kumaran: So… okay.
235 00:24:06.090 ⇒ 00:24:09.090 Nandika Jhunjhunwala: Yeah. The other question, sorry.
236 00:24:09.090 ⇒ 00:24:09.530 Uttam Kumaran: Yeah.
237 00:24:09.530 ⇒ 00:24:10.449 Nandika Jhunjhunwala: How many full of questions.
238 00:24:10.450 ⇒ 00:24:11.340 Uttam Kumaran: No, no, no.
239 00:24:11.340 ⇒ 00:24:19.969 Nandika Jhunjhunwala: But I was chatting with Bobby, and I realized, like, the reason it’s not helpful to me right now, because I think Bobby goes off of, like, topics.
240 00:24:19.970 ⇒ 00:24:20.630 Uttam Kumaran: Yeah.
241 00:24:20.630 ⇒ 00:24:27.340 Nandika Jhunjhunwala: So, it was sort of ignoring the raw data, and to my frustration, because some of the fields that I needed only existed in raw data.
242 00:24:27.340 ⇒ 00:24:28.010 Uttam Kumaran: Yeah.
243 00:24:28.190 ⇒ 00:24:30.719 Nandika Jhunjhunwala: So when I was querying, it was giving me queries, and I would, like.
244 00:24:30.720 ⇒ 00:24:36.800 Uttam Kumaran: Yes. And, like, drawn it, and I was like, wait, it says dispute does not exist. Yeah, so another thing you could do…
245 00:24:36.800 ⇒ 00:24:38.900 Nandika Jhunjhunwala: Is, like.
246 00:24:39.840 ⇒ 00:24:47.299 Uttam Kumaran: Mother Duck has an MCP server, so I’m wondering, like, potentially, if you’re using… if you guys are using Cursor or ChatGPT.
247 00:24:47.300 ⇒ 00:24:49.460 Nandika Jhunjhunwala: Yeah, I have my code, yeah.
248 00:24:49.460 ⇒ 00:24:52.089 Uttam Kumaran: Yeah, if you’re using Cloud Code, then you can hook into Mother Duck.
249 00:24:52.190 ⇒ 00:24:57.440 Uttam Kumaran: It’s still not gonna have, like… but at least it’ll have access to all the raw tables and help you do those joins.
250 00:24:57.440 ⇒ 00:24:58.280 Nandika Jhunjhunwala: Yeah.
251 00:24:58.280 ⇒ 00:25:00.749 Uttam Kumaran: Yeah, the Mother Duck MCP is really good.
252 00:25:00.750 ⇒ 00:25:07.870 Nandika Jhunjhunwala: For sure, okay. That’s a good tip, I will do that, thank you. So, I think you’re right, maybe I do do the modeling in Mother Doc, and then for the.
253 00:25:07.870 ⇒ 00:25:10.630 Uttam Kumaran: I just think it’s, like, a nicer environment to write SQL in.
254 00:25:10.630 ⇒ 00:25:12.910 Nandika Jhunjhunwala: Yeah, Omni is not… not a great environment.
255 00:25:12.910 ⇒ 00:25:21.979 Uttam Kumaran: Yeah, and then… and then that’s why, like, when you’re gonna go… when you’re gonna go visit, then just move there, because then at least it’s, like, small tweaks versus, like, having to…
256 00:25:22.570 ⇒ 00:25:25.170 Uttam Kumaran: Yeah, like, it’s just not… there’s not, like, any helpful auto.
257 00:25:25.170 ⇒ 00:25:25.650 Nandika Jhunjhunwala: Wow.
258 00:25:25.650 ⇒ 00:25:30.170 Uttam Kumaran: Correct, or, or, or, like… dialing at all for SQL writing, so…
259 00:25:30.440 ⇒ 00:25:41.199 Nandika Jhunjhunwala: And if I… so, just wanted to confirm, too, if I, like, write some queries off of, raw data, and sort of create, like, a few joins.
260 00:25:41.480 ⇒ 00:25:45.089 Nandika Jhunjhunwala: Can I push that to Omni via GitHub, or…
261 00:25:45.810 ⇒ 00:26:02.169 Uttam Kumaran: Yeah, well, I think there’s, like, two ways. One is, like, if it’s just views, then I don’t think you really have to do anything, because they’ll just sit as content. But what I want to do is, like, if you’re ending up writing some of those, like, when we… I want to go… I’ll go look at your dashboard to make sure that, like, we can…
262 00:26:02.460 ⇒ 00:26:11.290 Uttam Kumaran: basically reproduced exactly the same type of views with all the governed logic. So, like, you can keep building those, and then that’s what all sort of, like.
263 00:26:11.440 ⇒ 00:26:13.859 Uttam Kumaran: That’s what we’ll take to make sure it ends up in the models.
264 00:26:14.400 ⇒ 00:26:20.360 Nandika Jhunjhunwala: And then once I create that view, you’re saying I can just query that view to create dashboards?
265 00:26:20.570 ⇒ 00:26:26.909 Uttam Kumaran: Yeah, yeah, exactly. Like, you won’t have to push anything to GitHub, because it’s… all you’re doing is just, like, a view on top of, like, a SQL query.
266 00:26:26.910 ⇒ 00:26:28.140 Nandika Jhunjhunwala: Yay.
267 00:26:28.140 ⇒ 00:26:31.540 Uttam Kumaran: And then eventually, we’ll basically swap it with… like…
268 00:26:31.680 ⇒ 00:26:34.240 Uttam Kumaran: Picking from the topic to produce the same exact chart.
269 00:26:34.240 ⇒ 00:26:34.950 Nandika Jhunjhunwala: Okay.
270 00:26:35.090 ⇒ 00:26:43.589 Uttam Kumaran: So, like, literally what we’ll do is, like, even if you create that dashboard, later we’ll come in, edit it, and just swap it out, so it’s the same exact thing.
271 00:26:43.870 ⇒ 00:26:46.929 Nandika Jhunjhunwala: Got it. Okay, this is super helpful, thank you so much.
272 00:26:46.930 ⇒ 00:27:06.390 Uttam Kumaran: Yeah, of course, and then, like, keep… I’m gonna… also, I have on our plate to… to just prioritize some of the Salesforce pieces, just getting the basic models out, to fix that, like, that, like, filtering thing. And then I also… when Greg’s back, too, he’s gonna start doing some more stuff on Omni next week, so I think that’ll be, you know, start to get better, so…
273 00:27:07.290 ⇒ 00:27:08.949 Nandika Jhunjhunwala: No, amazing, thank you so much.
274 00:27:08.950 ⇒ 00:27:12.770 Uttam Kumaran: Okay. Yeah, this was helpful. Okay, perfect. Thank you.
275 00:27:13.280 ⇒ 00:27:15.489 Nandika Jhunjhunwala: See you, have a good one. Bye.