Meeting Title: Omni Data Models Sync Date: 2026-05-04 Meeting participants: Awaish Kumar, Mustafa Raja, Demilade Agboola, Advait Nandakumar Menon
WEBVTT
1 00:00:25.710 ⇒ 00:00:26.430 Mustafa Raja: P.
2 00:00:27.710 ⇒ 00:00:28.410 Awaish Kumar: Hello.
3 00:00:29.930 ⇒ 00:00:30.449 Awaish Kumar: I don’t know.
4 00:00:30.450 ⇒ 00:00:31.200 Advait Nandakumar Menon: Oh my goodness.
5 00:00:32.920 ⇒ 00:00:37.460 Awaish Kumar: I, guys, thank you for joining.
6 00:00:38.990 ⇒ 00:00:43.760 Awaish Kumar: Yeah, Demi, I would like if you can… Stop dreaming.
7 00:00:45.510 ⇒ 00:00:49.920 Awaish Kumar: Orization here, like… So, I understand that we…
8 00:00:50.420 ⇒ 00:00:52.650 Awaish Kumar: I have to convert these to…
9 00:00:53.270 ⇒ 00:00:56.820 Awaish Kumar: Like, the more granular levels, but,
10 00:00:58.370 ⇒ 00:01:02.249 Awaish Kumar: How do you think is the best possible way to do that?
11 00:01:03.500 ⇒ 00:01:06.289 Demilade Agboola: So in terms of being able to build out
12 00:01:06.750 ⇒ 00:01:11.939 Demilade Agboola: In terms of being able to build out this table, I think what we need to do is…
13 00:01:12.140 ⇒ 00:01:27.880 Demilade Agboola: and consolidate certain parts or certain things. So, for instance, create, like, a DIM customer table, or, you know, where we put all the data from the different sources together, deploying, Salesforce and all of that into one spot.
14 00:01:28.330 ⇒ 00:01:35.320 Demilade Agboola: And start to create, like, fact models for the different actions that occur in the different systems, so things around…
15 00:01:35.860 ⇒ 00:01:39.330 Demilade Agboola: opportunities in Salesforce, things that aren’t transparent.
16 00:01:39.980 ⇒ 00:01:40.800 Demilade Agboola: Right.
17 00:01:42.610 ⇒ 00:01:43.229 Awaish Kumar: No, no, like.
18 00:01:43.230 ⇒ 00:01:43.650 Demilade Agboola: just.
19 00:01:45.730 ⇒ 00:01:49.660 Awaish Kumar: But is it possible to create a fact table?
20 00:01:50.510 ⇒ 00:01:52.140 Awaish Kumar: Across different systems?
21 00:01:53.370 ⇒ 00:02:01.970 Demilade Agboola: No, not across different systems, but from the different systems, we’ll create, fact tables that they can then use to,
22 00:02:02.340 ⇒ 00:02:08.310 Demilade Agboola: We can then use to join downstream. So we can say, hey, this will be the fact table for this.
23 00:02:08.680 ⇒ 00:02:14.879 Demilade Agboola: we can… we can join downstream in, like, Omni, and create even, like, wider tables. So, for instance.
24 00:02:15.160 ⇒ 00:02:17.740 Demilade Agboola: If we do something about fract opportunities.
25 00:02:18.720 ⇒ 00:02:28.550 Demilade Agboola: They can use that, join it to the film customer table, and start to see what’s going on with opportunities, when it was lost, and when it was won, and all that sort of thing.
26 00:02:28.670 ⇒ 00:02:35.739 Demilade Agboola: Same thing with payments. We have payments, we can create a fact table for that, and then you can join to…
27 00:02:35.970 ⇒ 00:02:49.009 Demilade Agboola: the same customer table. Payments data will come from Hyperline, so again, we will just have to specify the join keys in the topics that were created in Omni. So for, like, Hyperline ID, Salesforce ID,
28 00:02:49.650 ⇒ 00:02:55.300 Demilade Agboola: I think what we should do is we should create this separate to what we already have existing, so that things don’t break.
29 00:02:58.030 ⇒ 00:03:02.490 Demilade Agboola: And I think what we also need to do is, like, in terms of…
30 00:03:02.850 ⇒ 00:03:09.040 Demilade Agboola: some of the calculations that exist. We will just need to, add them as granular as possible.
31 00:03:09.870 ⇒ 00:03:18.320 Demilade Agboola: Only worry will be if some of those things are, like, you know, by month, or by… a week…
32 00:03:18.970 ⇒ 00:03:22.149 Demilade Agboola: But we might need to recalculate it, but again.
33 00:03:22.280 ⇒ 00:03:28.230 Demilade Agboola: I think, ultimately, they just want to have flexibility to do what they want to do. I think we should just give them the opportunity.
34 00:03:28.770 ⇒ 00:03:30.539 Demilade Agboola: No, for example… this is possible.
35 00:03:30.970 ⇒ 00:03:37.500 Awaish Kumar: The last model week… last week, we worked on a customer enablement dashboard, right? So we…
36 00:03:37.740 ⇒ 00:03:42.660 Awaish Kumar: Create a more granular, tables, right? Fact tables.
37 00:03:42.660 ⇒ 00:03:43.180 Demilade Agboola: Sure.
38 00:03:43.890 ⇒ 00:03:45.470 Awaish Kumar: that,
39 00:03:45.600 ⇒ 00:03:51.540 Awaish Kumar: that you can use. I know he added the filter and everything in the dashboard, it’s ready to go for that. But the…
40 00:03:52.310 ⇒ 00:03:56.569 Awaish Kumar: The thing is, we still have a lot of fake tables, and we…
41 00:03:56.750 ⇒ 00:03:59.359 Awaish Kumar: still have a lot of dim tables, and
42 00:03:59.620 ⇒ 00:04:05.360 Awaish Kumar: what… when they… what they mean by unification, like, when they say unified by DIM customer only.
43 00:04:05.550 ⇒ 00:04:08.350 Awaish Kumar: That’s just an example, right? So there might be.
44 00:04:08.350 ⇒ 00:04:08.730 Demilade Agboola: Okay.
45 00:04:09.220 ⇒ 00:04:11.229 Awaish Kumar: More unification of the tables.
46 00:04:13.000 ⇒ 00:04:24.620 Demilade Agboola: Yeah, I think… yeah, I think we… we might need to just redefine certain tables, or… which is why I said, like, we should not maybe… what we might need to do is build new tables, rather than…
47 00:04:25.850 ⇒ 00:04:28.919 Demilade Agboola: disrupt what we have, so at least they still have their dashboards.
48 00:04:29.480 ⇒ 00:04:33.209 Demilade Agboola: I think the focus for the first couple of days this week should be that.
49 00:04:33.560 ⇒ 00:04:39.579 Demilade Agboola: So that once we can test that the models that we have and the new topics we’ve created work well.
50 00:04:40.720 ⇒ 00:04:45.559 Demilade Agboola: Okay, and we can now look at migrating the dashboards to the new topics.
51 00:04:47.860 ⇒ 00:04:56.510 Awaish Kumar: Yeah, but the thing is, you have to rework on the dashboards right now. We are saying it’s not required by the customer, but if we create new tables.
52 00:04:56.630 ⇒ 00:05:03.329 Awaish Kumar: How these dash… these deal… these, dashboard’s going to read data.
53 00:05:08.130 ⇒ 00:05:23.650 Demilade Agboola: If you create new tables, I think, ultimately, I don’t know, I think that it may be a lot of advice to create all the dashboards. I think we might have to prioritize certain dashboards and say, hey, these ones will be reworked using the new, like, data from the tables created.
54 00:05:24.620 ⇒ 00:05:30.099 Awaish Kumar: So you are saying we keep the current tables and just create a few new tables?
55 00:05:31.500 ⇒ 00:05:37.750 Demilade Agboola: Yes, so I’m saying, yes, we create the… we keep the same tables that exist, then…
56 00:05:38.080 ⇒ 00:05:44.909 Demilade Agboola: create some Pioneer tables. I think, ultimately, because, again, we’re handing over to them in, like, 2 weeks, I don’t want a situation around where we have
57 00:05:45.250 ⇒ 00:05:57.420 Demilade Agboola: Well, they don’t seem to have any tables, so let them have the tables that we built for them, they work, it’s fine. But we’re also just trying to create a way in which they can also then do whatever they feel is necessary to do with the data that they have.
58 00:05:57.720 ⇒ 00:06:02.140 Demilade Agboola: So, we’ll just create topics that are, you know, more expansive and have more details.
59 00:06:02.590 ⇒ 00:06:05.460 Demilade Agboola: you know, they can use AI to…
60 00:06:05.720 ⇒ 00:06:09.340 Demilade Agboola: Questions much easily across the data.
61 00:06:09.970 ⇒ 00:06:13.579 Awaish Kumar: Yeah, but now the thing is, if we do that, like.
62 00:06:13.970 ⇒ 00:06:17.410 Awaish Kumar: What will be our validation step? So…
63 00:06:17.710 ⇒ 00:06:25.459 Awaish Kumar: from dbt, you can also… you can use a cursor, create some tables, and… Bring into Omni, what…
64 00:06:26.260 ⇒ 00:06:36.080 Awaish Kumar: how we will validate that they are going to return correct result without us creating a dashboard or playing with AI?
65 00:06:37.530 ⇒ 00:06:44.630 Demilade Agboola: I mean, since we already have tables that work, we can always, like, try and, you know, do… we can ask questions.
66 00:06:44.830 ⇒ 00:06:51.630 Demilade Agboola: About if there were aggregated data that, you know, from the tables that were already already exist, much…
67 00:06:51.860 ⇒ 00:06:54.709 Demilade Agboola: The ugly… the type of aggregates and cranky.
68 00:06:54.810 ⇒ 00:07:01.420 Demilade Agboola: So if we say, like, ARR should be whatever amount, and, or we’re saying, you know, this is the number of opportunities.
69 00:07:01.530 ⇒ 00:07:02.819 Demilade Agboola: At the last light.
70 00:07:04.470 ⇒ 00:07:11.069 Demilade Agboola: 10 days, then we check the aggregated amount, and it’s different. We know that something is wrong somewhere, so we can investigate that.
71 00:07:11.600 ⇒ 00:07:16.210 Awaish Kumar: Okay, okay, so… Okay.
72 00:07:16.210 ⇒ 00:07:31.919 Demilade Agboola: We’ll just be different dimensions. So for opportunities, we’ll look at the account owner, the rep owners, all of that. So we can have customers, we can have, like, deem, you know, like, owners, or deem, like, you know, the owners would be, like, internal people, like, so it could be the reps, it could be the…
73 00:07:32.120 ⇒ 00:07:33.540 Demilade Agboola: and PTRs.
74 00:07:34.090 ⇒ 00:07:38.160 Demilade Agboola: You use that to… to give them that context.
75 00:07:38.940 ⇒ 00:07:42.610 Awaish Kumar: Yeah, okay, so can we, like, divide the…
76 00:07:45.210 ⇒ 00:07:49.660 Awaish Kumar: Different, divide different, kind of, like, whatever mods you have.
77 00:07:50.100 ⇒ 00:07:51.569 Awaish Kumar: So that we can usually…
78 00:07:53.390 ⇒ 00:08:00.680 Demilade Agboola: Okay, sure. I think what we can do… Is… in terms of…
79 00:08:05.300 ⇒ 00:08:08.820 Awaish Kumar: So, if we are just working on dbt, and I’m creating Omni.
80 00:08:09.750 ⇒ 00:08:13.110 Awaish Kumar: I don’t think we need, worth far or Edwin’s time.
81 00:08:14.380 ⇒ 00:08:15.230 Awaish Kumar: On it.
82 00:08:16.690 ⇒ 00:08:19.030 Demilade Agboola: No, I think we should be fine.
83 00:08:19.450 ⇒ 00:08:26.910 Demilade Agboola: by ourselves, I think what we just need to… we just need to create, like, again, just, like, facts models, so fact tasks, facts opportunities.
84 00:08:27.630 ⇒ 00:08:30.520 Demilade Agboola: Fact transactions, that sort of thing.
85 00:08:30.860 ⇒ 00:08:31.300 Awaish Kumar: No, but…
86 00:08:31.300 ⇒ 00:08:32.539 Demilade Agboola: We’ll just have the…
87 00:08:33.520 ⇒ 00:08:38.749 Awaish Kumar: What I’m saying is, we just need to create dbt models or omni topics, we don’t need…
88 00:08:39.030 ⇒ 00:08:43.799 Awaish Kumar: Most for Advia’s time, because that… that we can do outside.
89 00:08:43.809 ⇒ 00:08:47.019 Demilade Agboola: Yeah, yeah, definitely, definitely, yeah, we can do that, we can do that by ourselves.
90 00:08:47.840 ⇒ 00:08:55.100 Awaish Kumar: And then we can just try it out in our branch so that Omni doesn’t fail, and then we can merge it. Okay.
91 00:08:55.100 ⇒ 00:08:55.640 Demilade Agboola: Okay.
92 00:08:56.900 ⇒ 00:08:57.350 Awaish Kumar: Okay, so…
93 00:08:57.350 ⇒ 00:09:08.510 Mustafa Raja: One thing I want to add here is that Witt has pointed out that we may have missed a few models for default on Monday, or sorry, on Friday that we worked away, so…
94 00:09:08.910 ⇒ 00:09:14.170 Mustafa Raja: I think there’s, 2 or 3 more topics that, edwick wants us to add.
95 00:09:15.040 ⇒ 00:09:19.880 Awaish Kumar: Well, I mean, like, there’s… But I wanted to, like…
96 00:09:20.480 ⇒ 00:09:22.810 Awaish Kumar: How we missed it, like, for… on the…
97 00:09:22.810 ⇒ 00:09:32.750 Mustafa Raja: Yeah, so the charts were being made for those, you know? So the charts weren’t in production for those, so that is why we missed.
98 00:09:34.080 ⇒ 00:09:35.600 Awaish Kumar: So they’ve transferred?
99 00:09:36.130 ⇒ 00:09:42.929 Mustafa Raja: So the charts were in development for those, so the charts weren’t in production, you know?
100 00:09:45.440 ⇒ 00:09:54.409 Advait Nandakumar Menon: Yeah, so what happened is there was some feedback on that particular dashboard, and the PR was merged on Friday.
101 00:09:54.410 ⇒ 00:10:07.730 Advait Nandakumar Menon: And then we worked on the PR on Thursday, and it was merged on Friday, so the charts were being worked on, it was in progress, and it wasn’t published as such to the dashboard, in the production dashboard yet, so…
102 00:10:07.950 ⇒ 00:10:10.140 Advait Nandakumar Menon: Maybe that’s why it was a must.
103 00:10:11.730 ⇒ 00:10:12.480 Awaish Kumar: Okay.
104 00:10:12.950 ⇒ 00:10:17.689 Awaish Kumar: Yeah, okay, we can do that. So, for that part, like, we can work on it.
105 00:10:20.260 ⇒ 00:10:20.920 Awaish Kumar: Also…
106 00:10:20.920 ⇒ 00:10:21.710 Demilade Agboola: I think…
107 00:10:21.960 ⇒ 00:10:31.349 Demilade Agboola: I think our thing is… so, I just want to give advice a heads up that right now, we won’t be working at any, like, thing around feedback, so that we don’t…
108 00:10:31.710 ⇒ 00:10:34.590 Demilade Agboola: End of institutions where things break.
109 00:10:35.940 ⇒ 00:10:41.410 Demilade Agboola: Because… We’ve not incorporated, like, we’re just going to be doing new stuff, like, net new stuff.
110 00:10:41.580 ⇒ 00:10:43.190 Demilade Agboola: Are open to this.
111 00:10:43.710 ⇒ 00:10:46.040 Demilade Agboola: Also, I would want to,
112 00:10:47.000 ⇒ 00:10:52.629 Demilade Agboola: Steve, as much as possible, we will try and ensure that the new models we do can answer the questions that exist.
113 00:10:53.110 ⇒ 00:10:58.079 Demilade Agboola: But, because it’s just the raw data.
114 00:10:58.630 ⇒ 00:11:06.360 Demilade Agboola: Oh, that, that leads us to, like, questions, and we’ll figure that later down the line, because again, some of these things are, like.
115 00:11:10.050 ⇒ 00:11:16.240 Demilade Agboola: Some of the logic exists in the… in the way it has been aggregated, so we’ll try and break it down in such a way that they have the raw data.
116 00:11:16.380 ⇒ 00:11:27.559 Demilade Agboola: then maybe we might put AI context notes into, how, like, the AI should be able to model the data when they’re asking questions about it. I think that might be the way to go so that we don’t… we don’t…
117 00:11:28.460 ⇒ 00:11:30.179 Demilade Agboola: Blow ourselves down too much.
118 00:11:33.530 ⇒ 00:11:55.520 Advait Nandakumar Menon: I do want to ask one thing, like, are they… since they’re gonna take this modeling and development from here on, are they completely trying to avoid dbt? Because if they are not, there is this integration, right, between dbt and Omni, where we can just enable that integration, and they can directly edit the code of dbt or whatever within Omni itself, and just
119 00:11:55.520 ⇒ 00:12:01.940 Advait Nandakumar Menon: push it as a PR to GitHub, so there is that flexibility as well, if they are open to doing that.
120 00:12:01.940 ⇒ 00:12:04.200 Awaish Kumar: Yeah, but I don’t think they want to write it.
121 00:12:04.200 ⇒ 00:12:21.149 Demilade Agboola: They don’t… exactly. They don’t want to do anything with DVT. All they basically want to do is they want to have, like, big data sets that they can ask questions and say, you know, what is… what has happened over the last 30 days in regards payment, or this, and they just want to have, like, data that they can easily use.
122 00:12:22.400 ⇒ 00:12:33.320 Demilade Agboola: And so, they don’t… they don’t want to think about the dbt side of things, which is why I’m just saying, hey, you know what, let’s just create, like, large data sets for different… for different things, and then put.
123 00:12:34.080 ⇒ 00:12:48.580 Demilade Agboola: I put so that when they ask questions, Omni can… Blobby can easily say, hey, this is where the customers are, this is where the reps are, this is where the, accounts, like, the account owners are, and then I can join it to the different, you know.
124 00:12:49.270 ⇒ 00:12:53.569 Awaish Kumar: So, Demi, where we… you suggested that we should…
125 00:12:53.830 ⇒ 00:12:57.769 Awaish Kumar: Using raw data and the questions, try to model it, so do you think,
126 00:12:57.930 ⇒ 00:13:00.959 Awaish Kumar: Do you have any questions from the client?
127 00:13:02.310 ⇒ 00:13:07.980 Demilade Agboola: I don’t have any questions from the client, but Advait, can you reach out to Caitlin and just give, like.
128 00:13:08.380 ⇒ 00:13:15.220 Demilade Agboola: Get a sample of questions that they may want to ask to lobby, yeah, consistently.
129 00:13:15.800 ⇒ 00:13:18.239 Awaish Kumar: Okay, so let’s do that.
130 00:13:18.350 ⇒ 00:13:20.990 Awaish Kumar: Most of all, we… Oh…
131 00:13:22.530 ⇒ 00:13:27.630 Awaish Kumar: For the changes that are asked from you, let’s, we will work on that.
132 00:13:28.170 ⇒ 00:13:31.039 Awaish Kumar: Plus, Demi, if you can just create a…
133 00:13:31.330 ⇒ 00:13:34.470 Awaish Kumar: asking, like, tag Linear on Slack and ask.
134 00:13:34.700 ⇒ 00:13:37.760 Awaish Kumar: To create tickets, if you can divide, like, those parts.
135 00:13:38.620 ⇒ 00:13:49.469 Demilade Agboola: Yeah, that’s what I want to start doing now. I’ll create a quick overview of, like, what the different, like, fact tables and dim tables will look like, and then I would send it, and we can space it in linear.
136 00:13:51.260 ⇒ 00:13:51.910 Awaish Kumar: Okay.
137 00:13:53.660 ⇒ 00:13:54.560 Awaish Kumar: Okay.
138 00:13:58.160 ⇒ 00:14:01.800 Advait Nandakumar Menon: Okay, and for the questions to ask Globi, is there any…
139 00:14:01.860 ⇒ 00:14:18.600 Advait Nandakumar Menon: I know, Demi, you said they didn’t give us anything, like, questions or whatever, but, do you just want me to come up with it based on the data that’s there, or do they have any other document that could help in this? Like, any other context I could give Cursor to help in this formulation of questions?
140 00:14:19.160 ⇒ 00:14:27.560 Demilade Agboola: A couple of things we could do is you can go… like, I know you can go to their history, like, AI questions, and see questions they’ve asked already, so you can put that there.
141 00:14:27.560 ⇒ 00:14:28.170 Advait Nandakumar Menon: Huh.
142 00:14:28.170 ⇒ 00:14:32.850 Demilade Agboola: And then we can share that with Caitlin and say, hey, we’ve seen some of the questions you have asked over the
143 00:14:34.340 ⇒ 00:14:41.420 Demilade Agboola: Like, over the last, like, one month or two months. And we’re trying to test our lobby. Are there any other questions you’d like to add to it? So…
144 00:14:41.730 ⇒ 00:14:48.300 Demilade Agboola: At least it shows that we’ve seen what they are looking for, and we just need more context in case there are more things they would like to add.
145 00:14:50.510 ⇒ 00:14:51.210 Advait Nandakumar Menon: Okay.
146 00:14:52.000 ⇒ 00:14:52.670 Demilade Agboola: Okay.
147 00:14:53.210 ⇒ 00:14:54.159 Awaish Kumar: Okay, thank you.
148 00:14:54.160 ⇒ 00:14:54.790 Advait Nandakumar Menon: So…
149 00:14:55.220 ⇒ 00:15:09.939 Advait Nandakumar Menon: you want me to work on these questions, and just that, what Avish is gonna work on, like, the feedback left for the CS reporting and enablement Dashboard, but you don’t want me working on any other feedback, right? That’s what you mentioned, Denny?
150 00:15:09.940 ⇒ 00:15:11.579 Awaish Kumar: Yeah, no net new work.
151 00:15:11.590 ⇒ 00:15:22.449 Demilade Agboola: No nets, no nets in your work, because things are changing really quickly. The only thing is, Mustafa can work on the other part, like, the thing that you need for the dashboard, so you can finish that up.
152 00:15:22.810 ⇒ 00:15:26.339 Demilade Agboola: But in terms of, like, other stuff right now, we’re not doing anything next year.
153 00:15:26.630 ⇒ 00:15:27.540 Demilade Agboola: We’ll just be working on.
154 00:15:27.540 ⇒ 00:15:28.500 Advait Nandakumar Menon: Okay, then.
155 00:15:29.090 ⇒ 00:15:33.010 Advait Nandakumar Menon: Okay, then, what about the BDR dashboard feedback?
156 00:15:33.280 ⇒ 00:15:36.229 Advait Nandakumar Menon: I know they won’t have a couple of…
157 00:15:36.410 ⇒ 00:15:37.290 Demilade Agboola: like, again.
158 00:15:37.290 ⇒ 00:15:37.820 Advait Nandakumar Menon: Yeah.
159 00:15:37.820 ⇒ 00:15:50.879 Demilade Agboola: I think this is what we’ll have to… I’ll tell Greg, after this call, we can tell Greg. It’s… we can’t work on all of this, be breaking it down into, like, the different models, testing that the different, different models are fine.
160 00:15:51.400 ⇒ 00:15:56.629 Demilade Agboola: My blog is asking, has the context any sort of questions that they would want to use?
161 00:15:57.050 ⇒ 00:16:06.309 Demilade Agboola: And also still be doing, like, BDR stuff, so they have to prioritize, and given that they are saying, like, they’re confident, like, they just need the tables to be fine, I think we’re focusing on that.
162 00:16:06.790 ⇒ 00:16:08.580 Demilade Agboola: And that will be the pushback.
163 00:16:09.740 ⇒ 00:16:10.670 Demilade Agboola: thoughts.
164 00:16:10.840 ⇒ 00:16:11.540 Advait Nandakumar Menon: Okay.
165 00:16:12.260 ⇒ 00:16:17.579 Advait Nandakumar Menon: Okay, yeah, I was just looking for some directions, and that’s clear, thanks for that.
166 00:16:18.270 ⇒ 00:16:19.750 Demilade Agboola: Okay, alright, sounds good.
167 00:16:21.870 ⇒ 00:16:23.590 Advait Nandakumar Menon: Alright. Thank you, Les.