Meeting Title: Data Service Standup Date: 2026-02-17 Meeting participants: Awaish Kumar, Mustafa Raja, Ashwini Sharma, Brylle Girang, Demilade Agboola
WEBVTT
1 00:02:25.140 ⇒ 00:02:26.220 Brylle Girang: Hey guys!
2 00:02:28.150 ⇒ 00:02:29.059 Mustafa Raja: Hey, how are you?
3 00:02:30.300 ⇒ 00:02:32.470 Brylle Girang: Doing great! How are you doing?
4 00:02:33.400 ⇒ 00:02:34.520 Mustafa Raja: Yeah, doing good.
5 00:02:43.890 ⇒ 00:02:44.909 Awaish Kumar: Right.
6 00:02:47.790 ⇒ 00:02:48.460 Ashwini Sharma: Hello.
7 00:02:50.530 ⇒ 00:02:54.610 Awaish Kumar: Hello, yeah, I think everybody’s here, we can start.
8 00:02:55.320 ⇒ 00:02:59.210 Awaish Kumar: Let me share my screen.
9 00:03:09.650 ⇒ 00:03:10.480 Awaish Kumar: Okay.
10 00:03:11.380 ⇒ 00:03:14.790 Awaish Kumar: We can start with the Eden OS, I think.
11 00:03:15.490 ⇒ 00:03:22.049 Awaish Kumar: Mmm, oui… Started with some of the tables, like order summary, fake orders, which are…
12 00:03:22.200 ⇒ 00:03:29.449 Awaish Kumar: The, the base tables to… Actually build some, like.
13 00:03:29.680 ⇒ 00:03:39.850 Awaish Kumar: the core dashboards, and I think, like, these are ready, but they are in a PR right now. Ashwani, I think you have already started working on.
14 00:03:41.020 ⇒ 00:03:43.970 Ashwini Sharma: Yeah, I’ve started looking into these two,
15 00:03:44.230 ⇒ 00:03:49.320 Ashwini Sharma: Basically, right now, there is no data in any of those tables, right? At least the ones that are relevant.
16 00:03:49.540 ⇒ 00:03:54.300 Ashwini Sharma: But yeah, I’ll try to figure out if we can use the existing columns, and…
17 00:03:54.300 ⇒ 00:03:58.770 Awaish Kumar: That is the challenge here. We don’t have any data, we can’t validate.
18 00:03:58.960 ⇒ 00:04:02.670 Awaish Kumar: Stuff, so we just, based on the schema.
19 00:04:03.840 ⇒ 00:04:09.949 Awaish Kumar: We just build out the tables, and we can validate once the data arrives.
20 00:04:10.680 ⇒ 00:04:11.300 Ashwini Sharma: Yeah.
21 00:04:13.630 ⇒ 00:04:19.989 Awaish Kumar: And yeah, the existing… the logic exists in the current dashboards, because… or current models, because these are the…
22 00:04:20.800 ⇒ 00:04:22.540 Awaish Kumar: The same models.
23 00:04:23.260 ⇒ 00:04:29.699 Awaish Kumar: Which exist in the… current, like, W…
24 00:04:30.310 ⇒ 00:04:35.270 Awaish Kumar: grid structure which supports Tableau, so that’s why we can actually build some of it.
25 00:04:35.510 ⇒ 00:04:41.649 Awaish Kumar: Yeah, but I think we are on track. I think we will be done by today, at least.
26 00:04:42.360 ⇒ 00:04:47.570 Ashwini Sharma: No, today it won’t be, but I should be able to do it tomorrow, because I’m half-day today.
27 00:04:48.600 ⇒ 00:04:49.370 Awaish Kumar: Oh, okay.
28 00:04:50.090 ⇒ 00:04:56.350 Awaish Kumar: Okay, great. Moving on to… Magic Spoons.
29 00:05:00.180 ⇒ 00:05:05.090 Awaish Kumar: Yeah, Demi, you can go on. How is it going with, like, spins and stuff?
30 00:05:07.510 ⇒ 00:05:16.420 Demilade Agboola: So for Magic Spoons, we basically are just waiting for Spoons to reply. I know Ashwini is going to send them a message to nudge them today.
31 00:05:17.260 ⇒ 00:05:21.900 Demilade Agboola: But for the most part, no, like, we were just, like, that’s the major thing.
32 00:05:22.280 ⇒ 00:05:29.960 Demilade Agboola: I know Tom said he was going to send the, SOW that I made. I don’t know if he has done that, but I’ll follow up with him on that.
33 00:05:30.110 ⇒ 00:05:35.129 Demilade Agboola: And I know we have a meeting today with their current data vendor that we’ll be taking over from.
34 00:05:35.610 ⇒ 00:05:46.060 Demilade Agboola: So yeah, we’ll just meet them and find out what they do, how they handle things, and we’ll probably, like, have a takeover, like, documentation from the call.
35 00:05:46.680 ⇒ 00:05:47.360 Awaish Kumar: Okay.
36 00:05:50.260 ⇒ 00:05:52.579 Awaish Kumar: Okay, so you have a call today?
37 00:05:52.890 ⇒ 00:05:58.449 Demilade Agboola: Yes, I believe 1PM EST, but I will confirm from Mary, because I haven’t seen the invitation yet.
38 00:05:59.090 ⇒ 00:05:59.950 Awaish Kumar: Okay.
39 00:06:01.800 ⇒ 00:06:07.419 Awaish Kumar: Okay, then I think we are good here. And moving on to the next one, which is…
40 00:06:07.610 ⇒ 00:06:10.320 Awaish Kumar: Hedra, we have some of the tickets.
41 00:06:10.920 ⇒ 00:06:20.280 Awaish Kumar: Here, so… I think, we have… for some, we have PIs in review, which,
42 00:06:21.030 ⇒ 00:06:35.969 Awaish Kumar: which I’m reviewing, I can… it should be done, in a while, and after that, I think we are just basically building new models. We have a new team member here, Sri, which will be looking at, the…
43 00:06:36.280 ⇒ 00:06:40.859 Awaish Kumar: which we’ll be supporting on the strategy side, on HITRA, that how…
44 00:06:41.710 ⇒ 00:06:51.340 Awaish Kumar: they can view, basically, how they can start reporting their MRR and ERR stuff. So, and I will be kind of supporting, on the modeling side.
45 00:06:52.360 ⇒ 00:07:09.530 Awaish Kumar: So… and for now, we are just trying to build something, some dashboards for them, so they can easily see MRR, ER, and churn reports, and… and they basically want that… those dashboards to share that info with their investors.
46 00:07:10.470 ⇒ 00:07:15.390 Awaish Kumar: So, basically, yeah, we are… we are supporting that, and that’s all for… for the intro.
47 00:07:16.210 ⇒ 00:07:23.350 Awaish Kumar: Moving on to CTA… Yeah.
48 00:07:25.020 ⇒ 00:07:27.350 Awaish Kumar: How’s it going, Eshani, with the CTA?
49 00:07:27.630 ⇒ 00:07:28.590 Awaish Kumar: Tickets?
50 00:07:31.170 ⇒ 00:07:37.730 Ashwini Sharma: Sorry, yeah, for CTA, we need to identify some work items. Yesterday, I had asked a few questions to them.
51 00:07:38.200 ⇒ 00:07:45.510 Ashwini Sharma: I didn’t… in fact, he sent it out to CTA guys, but they were on leave yesterday, so we didn’t get any answers.
52 00:07:45.800 ⇒ 00:07:55.470 Ashwini Sharma: Some of the concrete work items that we can do with CTA is maybe ingest Shopify data, right? That’s one clear work item that I can think of.
53 00:07:55.690 ⇒ 00:07:58.620 Ashwini Sharma: The other work item would be the identity stitching part, which is.
54 00:07:58.620 ⇒ 00:07:58.970 Awaish Kumar: loop.
55 00:07:58.970 ⇒ 00:08:00.950 Ashwini Sharma: Work in progress, right?
56 00:08:01.510 ⇒ 00:08:07.229 Awaish Kumar: Okay, so, but that… did we send the request to get the Shopify credentials?
57 00:08:07.230 ⇒ 00:08:14.009 Ashwini Sharma: Otam did. Otam did. They were on leave yesterday, so we didn’t get any answers from them. Maybe we’ll get today.
58 00:08:14.900 ⇒ 00:08:19.300 Awaish Kumar: Okay, so we are starting with the ingestion and modeling for Shopify stuff.
59 00:08:20.230 ⇒ 00:08:26.799 Ashwini Sharma: Yeah, we can… we can do that, yeah, if they… they provide us the credentials, we can start with the ingestion.
60 00:08:30.570 ⇒ 00:08:33.530 Awaish Kumar: Okay, I think we got just one more ticket here.
61 00:08:34.490 ⇒ 00:08:39.329 Ashwini Sharma: Automate as in… pipeline via Snowflake to FTP.
62 00:08:40.770 ⇒ 00:08:41.400 Awaish Kumar: Okay, yeah.
63 00:08:41.409 ⇒ 00:08:42.989 Ashwini Sharma: Marketing Cloud.
64 00:08:43.530 ⇒ 00:08:45.660 Brylle Girang: I just updated that ticket.
65 00:08:46.370 ⇒ 00:08:54.800 Brylle Girang: Ashwini, I just want to understand where we currently are at for that specific ticket.
66 00:08:55.270 ⇒ 00:08:58.320 Ashwini Sharma: Because the last update was 9 weeks ago.
67 00:09:01.490 ⇒ 00:09:02.919 Ashwini Sharma: A snowflake.
68 00:09:06.430 ⇒ 00:09:10.839 Awaish Kumar: Is Salesforce Marketing Cloud, like, I don’t think we even started on this.
69 00:09:10.840 ⇒ 00:09:16.389 Ashwini Sharma: No, this is, like, we asked Polyatomic to create a connector for this, and they did not…
70 00:09:16.800 ⇒ 00:09:21.380 Ashwini Sharma: they have not yet created, right? At least, I haven’t got a go-ahead from them.
71 00:09:22.120 ⇒ 00:09:28.420 Ashwini Sharma: The idea was, like, to use Polyatomic to extract data from Salesforce Marketing Cloud into Snowflake.
72 00:09:28.990 ⇒ 00:09:33.310 Ashwini Sharma: pipeline via Snowflake to FTP?
73 00:09:39.700 ⇒ 00:09:43.769 Awaish Kumar: I don’t know, like, this… this is really… the title is really confusing.
74 00:09:43.940 ⇒ 00:09:47.410 Awaish Kumar: Somebody cloud, currently running in Postgres.
75 00:09:47.580 ⇒ 00:09:53.110 Awaish Kumar: by moving the processing to Snowflake and leveraging Spotify. Okay, there will be maybe some, like.
76 00:09:53.640 ⇒ 00:09:56.890 Awaish Kumar: Why is that on some FTP server, we want to move it to a…
77 00:09:57.070 ⇒ 00:09:59.990 Awaish Kumar: Salesforce Marketing… Marketing Cloud, is that… is that…
78 00:10:01.840 ⇒ 00:10:14.229 Ashwini Sharma: No, I think this is about, there is data in Postgres, we need to extract it into S3, and then from S3, using some polyatomic connector, we can move it to FTP. That is what I understand.
79 00:10:16.130 ⇒ 00:10:17.859 Ashwini Sharma: Sure. What is the priority for.
80 00:10:17.860 ⇒ 00:10:25.360 Awaish Kumar: Okay, we… Okay, let’s see… let’s talk about it at the end of the stand-up, for now.
81 00:10:25.800 ⇒ 00:10:30.420 Awaish Kumar: I think, on the CTS side, we need clarity. I will ask Utam.
82 00:10:30.560 ⇒ 00:10:35.020 Awaish Kumar: To see what tickets we should be doing this week.
83 00:10:35.370 ⇒ 00:10:42.460 Awaish Kumar: And maybe we have answer from CT team today, because they were leave… on leave yesterday.
84 00:10:42.580 ⇒ 00:10:47.060 Awaish Kumar: So… Yeah, let’s get back to it after, at the end of the stand-up.
85 00:10:50.100 ⇒ 00:10:52.039 Awaish Kumar: Then moving on to Element.
86 00:10:52.770 ⇒ 00:11:03.259 Awaish Kumar: So, on the element side, we basically have done, on the modeling side, we are kind of done.
87 00:11:03.830 ⇒ 00:11:11.569 Awaish Kumar: Mostly now it’s on… on Ember, embers and Robert Spray, that they are building some reports for…
88 00:11:12.100 ⇒ 00:11:14.609 Awaish Kumar: The retail and wholesale teams.
89 00:11:15.010 ⇒ 00:11:20.730 Awaish Kumar: And while doing that, if they have any modeling requirements, we will be supporting that.
90 00:11:21.730 ⇒ 00:11:23.359 Awaish Kumar: Apart from that…
91 00:11:23.530 ⇒ 00:11:34.360 Awaish Kumar: there are some requirements for connectors, I think Tom is not here, but yeah, we should be also sending some of the messages to tech team here to get credentials for some.
92 00:11:34.360 ⇒ 00:11:34.890 Mustafa Raja: What?
93 00:11:35.610 ⇒ 00:11:36.870 Awaish Kumar: Add connectors.
94 00:11:39.550 ⇒ 00:11:44.389 Awaish Kumar: But overall, the health is good, and I think we are making progress here.
95 00:11:44.860 ⇒ 00:11:53.759 Awaish Kumar: And then moving on to… ABC, I think we don’t have anything there, and then default.
96 00:11:56.200 ⇒ 00:11:57.630 Awaish Kumar: Yeah, Nami.
97 00:12:00.320 ⇒ 00:12:04.640 Demilade Agboola: So for default, we were able to sync yesterday, Mustafa and I.
98 00:12:04.870 ⇒ 00:12:11.950 Demilade Agboola: So we’ve come up with some new tickets and things we need to do, so, prior to the meeting we have with them on Thursday.
99 00:12:14.060 ⇒ 00:12:20.260 Demilade Agboola: And so, that is kind of what the focus is. Oh, for ingesting data to Mother Doc, we can…
100 00:12:20.390 ⇒ 00:12:21.959 Demilade Agboola: Close our tickets, by the way.
101 00:12:23.170 ⇒ 00:12:31.019 Demilade Agboola: Yeah, so that’s kind of what we were sinking on yesterday. We should be able to…
102 00:12:32.030 ⇒ 00:12:39.380 Demilade Agboola: get these things over to them, at least show them some of… some proof of concept before Thursday, or by Thursday.
103 00:12:39.670 ⇒ 00:12:43.300 Demilade Agboola: And then we can, I think that’ll make them, like, really happy, because…
104 00:12:43.720 ⇒ 00:12:46.289 Demilade Agboola: They’ve been wanting to see progress.
105 00:12:46.450 ⇒ 00:12:51.889 Demilade Agboola: The only other blocker is that Postgres… we’re trying to, ingest Postgres into…
106 00:12:53.370 ⇒ 00:13:02.880 Demilade Agboola: Mother Doc, and their CTO, Victor, is kind of delaying that, because he… he says his engineering team is… the bandwidth has been stretched.
107 00:13:03.100 ⇒ 00:13:08.440 Demilade Agboola: And he doesn’t have anyone who can just ensure that things are going
108 00:13:08.630 ⇒ 00:13:14.000 Demilade Agboola: Well, because he’s worried about connecting directly to the prod instance.
109 00:13:14.740 ⇒ 00:13:20.830 Demilade Agboola: So, we’re trying to… I’ve shared documentation about how we plan to do with, CDC replication.
110 00:13:21.570 ⇒ 00:13:28.890 Demilade Agboola: With polyatomic, but even that, he still wants an engineer to go over everything, so… it’s kind of… that’s kind of the delay with that.
111 00:13:30.220 ⇒ 00:13:30.990 Awaish Kumar: Okay.
112 00:13:32.500 ⇒ 00:13:51.809 Mustafa Raja: So, from my side, yeah, we realigned our Gantt chart, our plan, and according to that, we, we so far are on track. And then for SEMrush data, I didn’t get a chance yesterday, I was working on Eden and ABC stuff.
113 00:13:52.080 ⇒ 00:13:54.890 Mustafa Raja: So… I will be focusing on that.
114 00:13:56.550 ⇒ 00:13:58.489 Awaish Kumar: Okay, but, like…
115 00:14:00.530 ⇒ 00:14:09.629 Awaish Kumar: Okay, so, yeah, like, I think, like, that’s… we should plan it a little bit better, instead of saying every day that I will be done today.
116 00:14:09.630 ⇒ 00:14:10.290 Mustafa Raja: Yeah.
117 00:14:10.290 ⇒ 00:14:13.179 Awaish Kumar: Let’s try to come up with some rate which is really.
118 00:14:13.180 ⇒ 00:14:13.830 Mustafa Raja: Interesting.
119 00:14:14.620 ⇒ 00:14:15.420 Mustafa Raja: Okay.
120 00:14:15.860 ⇒ 00:14:16.410 Awaish Kumar: Yep.
121 00:14:17.380 ⇒ 00:14:22.439 Awaish Kumar: Moving on to Eden,
122 00:14:23.620 ⇒ 00:14:30.519 Awaish Kumar: I think the analytics tasks are done here. I think I’m concerned about this upfront task.
123 00:14:31.790 ⇒ 00:14:33.380 Awaish Kumar: How’s it going, Ishwani?
124 00:14:35.510 ⇒ 00:14:36.530 Ashwini Sharma: Udu, which one?
125 00:14:37.030 ⇒ 00:14:43.080 Ashwini Sharma: No, this has not yet started. Right now, the focus is on Magic Spoon getting the pipeline out.
126 00:14:43.350 ⇒ 00:14:46.130 Ashwini Sharma: The Eden, Mart stuff?
127 00:14:46.130 ⇒ 00:14:50.120 Awaish Kumar: Magic Spoon is kind of, blunt, right?
128 00:14:50.410 ⇒ 00:14:58.699 Ashwini Sharma: No, I’m sort of not totally blocked. I’m still working on refactoring that pipeline and testing it out. Today, it was mainly testing this pipeline.
129 00:14:59.000 ⇒ 00:15:02.640 Ashwini Sharma: For the historical data sync, right? So…
130 00:15:02.640 ⇒ 00:15:03.450 Awaish Kumar: Okay.
131 00:15:03.450 ⇒ 00:15:10.599 Ashwini Sharma: Yeah, on the modeling side, maybe we’re blocked, but from the pipeline refactoring side, I’m not yet blocked.
132 00:15:12.030 ⇒ 00:15:12.650 Awaish Kumar: Okay.
133 00:15:14.060 ⇒ 00:15:22.569 Ashwini Sharma: This one, yeah, I’ll take a look at this one tomorrow and see if we are in a ready state to send out the data to UpFluence.
134 00:15:22.800 ⇒ 00:15:28.870 Ashwini Sharma: I doubt because, like, we have started gathering the state data from middle of February, right? So…
135 00:15:29.080 ⇒ 00:15:31.390 Awaish Kumar: And we don’t have…
136 00:15:31.590 ⇒ 00:15:34.440 Ashwini Sharma: Like, for February, even I can ask Zoran to…
137 00:15:34.590 ⇒ 00:15:49.819 Awaish Kumar: to do that manually, and until we have this pipeline. But the thing is, are we… did we have a… like, when you and Damalare met, that, like, do we think that the approach that you were taking, will that be sufficient to get the correct plan?
138 00:15:49.820 ⇒ 00:16:01.170 Ashwini Sharma: Right, yeah, that is a sufficient. So, we need to… we’re capturing this daily snapshot whenever it changes. For each change, we are going to send the record to, Fluence.
139 00:16:01.530 ⇒ 00:16:10.449 Ashwini Sharma: About the… with the changed amount, right? So that… that will track all the spend that has happened, for these influencers.
140 00:16:11.590 ⇒ 00:16:13.140 Ashwini Sharma: On these influences.
141 00:16:13.140 ⇒ 00:16:13.820 Awaish Kumar: Okay.
142 00:16:15.030 ⇒ 00:16:19.900 Awaish Kumar: Okay, let’s… let’s then try to close that out tomorrow, and
143 00:16:20.390 ⇒ 00:16:28.790 Awaish Kumar: after that, we’ll see, like, if we are missing some data in February, we can try to sync with Zoran and see if we can
144 00:16:29.260 ⇒ 00:16:30.399 Awaish Kumar: Fill it out, man.
145 00:16:30.400 ⇒ 00:16:36.960 Demilade Agboola: Ashwini, is the dbt model snapshot, like, the snapshot, is it not in production yet? Is it in production already?
146 00:16:36.960 ⇒ 00:16:44.690 Ashwini Sharma: No, it is in production, but what I was saying is, like, for February, we… I posted probably last week, or…
147 00:16:44.900 ⇒ 00:16:48.779 Ashwini Sharma: Maybe on Friday? Maybe Thursday, right?
148 00:16:49.320 ⇒ 00:17:01.030 Ashwini Sharma: Now, the thing is, like, on Thursday, it will create one snapshot that does not contain incremental data, right? It just contains the data that was there on Thursday, which is, like, somewhere mid-February.
149 00:17:02.990 ⇒ 00:17:13.019 Demilade Agboola: So the reason I ask that is maybe we need a different ticket, because, like, right now, this ticket shows that this should have been done, and it’s not done, or… but it’s done, we’re just waiting for…
150 00:17:13.339 ⇒ 00:17:16.169 Demilade Agboola: Like, you’ve done the PR, it’s been…
151 00:17:16.170 ⇒ 00:17:22.840 Ashwini Sharma: Yeah, yeah, that part is done. So, let’s close this ticket, I’ll create a new one that can, that will,
152 00:17:23.319 ⇒ 00:17:25.640 Ashwini Sharma: You know, highlight what we need to do next.
153 00:17:26.810 ⇒ 00:17:27.579 Awaish Kumar: Okay.
154 00:17:27.960 ⇒ 00:17:35.640 Awaish Kumar: Apart from that, I think this roadmap thing is done, and… for…
155 00:17:37.260 ⇒ 00:17:40.000 Awaish Kumar: For… then we have for migration.
156 00:17:40.000 ⇒ 00:17:42.639 Demilade Agboola: Oh, by the way, you can close 1421.
157 00:17:42.970 ⇒ 00:17:45.640 Demilade Agboola: the… I figured I’d fix the daddy.
158 00:17:48.590 ⇒ 00:17:53.950 Awaish Kumar: Okay, yeah, let’s then talk about migration, Mustwa, how is it going for… with… with Omar?
159 00:17:53.950 ⇒ 00:17:54.850 Mustafa Raja: Oh, yeah.
160 00:17:55.610 ⇒ 00:17:57.420 Mustafa Raja: So,
161 00:17:58.120 ⇒ 00:18:19.460 Mustafa Raja: Firstly, our topics had, summary tables, that weren’t able to join, with a lot of other tables, right? So, what Deminade suggested is we should expand that, look into dbt, and, how we are building those summary tables and reflect that in the topics themselves, so I was able to do that.
162 00:18:19.460 ⇒ 00:18:24.279 Mustafa Raja: And then, apart from that, what I’m working right now is semantic layer.
163 00:18:25.040 ⇒ 00:18:27.690 Awaish Kumar: So, like, when…
164 00:18:27.920 ⇒ 00:18:33.329 Mustafa Raja: Yeah, we are building that in Omnitopics, do you really mean that we…
165 00:18:34.610 ⇒ 00:18:43.710 Mustafa Raja: We are just, creating joins, that are already in, dbt for the summary tables only.
166 00:18:44.930 ⇒ 00:18:54.060 Awaish Kumar: I get it, but there are some of the tables which actually require more than just a join, like, they may require some of the calculations.
167 00:18:54.390 ⇒ 00:18:57.430 Awaish Kumar: How… how are we… how are we handling that?
168 00:18:59.030 ⇒ 00:19:05.839 Mustafa Raja: I had Kersha go over them, and, I, I didn’t, you know, see any of that come up.
169 00:19:07.220 ⇒ 00:19:12.309 Awaish Kumar: Okay, so, like… Do you have anything to say, add, like, Demlade?
170 00:19:14.750 ⇒ 00:19:19.370 Mustafa Raja: I can have Demilade, you know, review those topics.
171 00:19:21.220 ⇒ 00:19:24.300 Demilade Agboola: I’m sorry, what calculations are you referring to? I just want to have a…
172 00:19:24.300 ⇒ 00:19:27.869 Awaish Kumar: Like, there are then, like, there are cohort tables, right?
173 00:19:28.000 ⇒ 00:19:33.419 Awaish Kumar: I just looked at the… the screenshot that was shared, like, there are some cohort tables, right?
174 00:19:33.970 ⇒ 00:19:35.780 Mustafa Raja: Yeah, so…
175 00:19:35.780 ⇒ 00:19:51.159 Awaish Kumar: So if you join them together, if that is just a join or thing, that is okay. But, like, if we are trying to use base tables, how that is going to work in Omnia? That’s my question, like, if you’re trying to use, like, maybe order somebody…
176 00:19:51.740 ⇒ 00:19:59.049 Awaish Kumar: and then build cohorting… cohort tables on top of it. Are we doing it in SQL, or we are trying to do it in…
177 00:19:59.300 ⇒ 00:20:00.710 Awaish Kumar: Omni itself.
178 00:20:02.840 ⇒ 00:20:08.790 Demilade Agboola: I think… I think it’s a combination of both. I think we’re trying to build out some summary tables in Omni directly.
179 00:20:09.190 ⇒ 00:20:12.919 Demilade Agboola: But as much as possible, if there are calculations that…
180 00:20:13.360 ⇒ 00:20:17.159 Demilade Agboola: Also trying to see what calculations we can do, what calculations we can do.
181 00:20:17.610 ⇒ 00:20:22.530 Demilade Agboola: So, like, the cohorts… The cohort table is basically a summary table.
182 00:20:22.930 ⇒ 00:20:30.559 Demilade Agboola: And so we’ll try and replicate that as well. So we might have, like, a, customer retention or customer retention topic.
183 00:20:30.730 ⇒ 00:20:33.300 Demilade Agboola: And then we’ll have things about cohorts in there as well.
184 00:20:33.680 ⇒ 00:20:39.259 Demilade Agboola: And it’ll be summary tables that we’ve built off of the fact and dim tables in BigQuery.
185 00:20:40.310 ⇒ 00:20:41.220 Awaish Kumar: Okay.
186 00:20:45.950 ⇒ 00:20:47.540 Awaish Kumar: Okay,
187 00:20:48.680 ⇒ 00:21:00.540 Awaish Kumar: Okay, let’s… then I think, maybe I’ll also take a look how is it… how it’s happening there. But apart from that, I think we are on track, right, on the migration lab projects.
188 00:21:00.540 ⇒ 00:21:01.240 Mustafa Raja: Yep.
189 00:21:01.240 ⇒ 00:21:02.260 Awaish Kumar: It’s going well, yeah.
190 00:21:02.880 ⇒ 00:21:03.690 Awaish Kumar: Apart from this.
191 00:21:03.690 ⇒ 00:21:15.639 Mustafa Raja: Yeah, I’m also working on the semantic layer, right? So, I have a script that’s running, it’s almost 90% done, so yeah, that’s pretty much… that’s pretty much it.
192 00:21:17.270 ⇒ 00:21:18.020 Awaish Kumar: Okay.
193 00:21:21.160 ⇒ 00:21:26.790 Mustafa Raja: Yeah, this is working on, for P0 topics, and all of the tables that we have in dbt.
194 00:21:27.460 ⇒ 00:21:28.200 Awaish Kumar: Okay.
195 00:21:28.870 ⇒ 00:21:38.239 Awaish Kumar: Yeah, apart from that, I have some… one project which is, like, regarding… Having a connector between,
196 00:21:38.350 ⇒ 00:21:41.950 Awaish Kumar: Jay Chern’s noti, that may… might get delayed.
197 00:21:42.590 ⇒ 00:21:49.930 Awaish Kumar: due to, like, the features they need out of it, we… we don’t support it as a… Like, that’s…
198 00:21:50.400 ⇒ 00:22:05.070 Awaish Kumar: there’s not a data engineering work, but, like, we are supporting Eden on that, so it might just get delayed a little bit, but yeah, we are trying to, handle that as well, which does not reflect here. I will try to ask Robert if you can add some.
199 00:22:05.460 ⇒ 00:22:07.000 Awaish Kumar: Tickets here for that.
200 00:22:08.620 ⇒ 00:22:13.230 Awaish Kumar: Apart from that, I think we are… Yeah, we are good here.
201 00:22:13.410 ⇒ 00:22:16.429 Awaish Kumar: That’s the end of the stand-up, but we can…
202 00:22:16.600 ⇒ 00:22:21.379 Awaish Kumar: I think, go back to… CTA ticket, I think…
203 00:22:21.700 ⇒ 00:22:28.299 Awaish Kumar: Ashwini Weak and Brill, we can discuss that. Everybody else, yeah, free to… Get back to work.
204 00:22:36.010 ⇒ 00:22:44.850 Awaish Kumar: Yeah, so… for this ticket, I don’t know what… actually… Happen.
205 00:22:44.850 ⇒ 00:22:50.840 Ashwini Sharma: Yeah, I also lost track. Let’s read through the comments or details over there.
206 00:22:51.530 ⇒ 00:22:54.679 Ashwini Sharma: Run SQL, there’s an existing S3 integration tags.
207 00:22:55.770 ⇒ 00:22:56.579 Awaish Kumar: Right on this list.
208 00:22:56.580 ⇒ 00:22:58.610 Ashwini Sharma: 3 instead of post from this.
209 00:23:05.010 ⇒ 00:23:09.730 Awaish Kumar: Okay, so this is… this seems like building a ETL and a reverse ETL?
210 00:23:09.840 ⇒ 00:23:18.530 Awaish Kumar: both, from what I can read from description, so… Was that part of any… So, like,
211 00:23:18.800 ⇒ 00:23:23.250 Awaish Kumar: like, sprints, but so far, I haven’t seen this.
212 00:23:23.650 ⇒ 00:23:30.069 Ashwini Sharma: No, it wasn’t part of any sprint. Can you scroll down? Let’s read the comments, down below.
213 00:23:34.230 ⇒ 00:23:35.959 Ashwini Sharma: They have to non-stop.
214 00:23:38.220 ⇒ 00:23:38.800 Awaish Kumar: Okay.
215 00:23:46.770 ⇒ 00:23:49.600 Ashwini Sharma: Yeah, it totally fell off my radar, yeah.
216 00:23:50.010 ⇒ 00:23:55.720 Ashwini Sharma: Okay, let’s get more context from Catherine, and then maybe we can work on this one.
217 00:23:55.720 ⇒ 00:24:01.240 Awaish Kumar: Let’s discuss with Dutam to see, as on this project, he’s the EP.
218 00:24:01.470 ⇒ 00:24:02.020 Ashwini Sharma: Oh my god.
219 00:24:02.020 ⇒ 00:24:07.490 Awaish Kumar: So let’s get… Let’s get his feedback on what he wants us to work on this week.
220 00:24:07.700 ⇒ 00:24:12.429 Awaish Kumar: So, yeah, until that is done, let’s just focus on what… whatever you’re doing.
221 00:24:12.660 ⇒ 00:24:16.990 Ashwini Sharma: Okay. And this, sorry, escalated needs SME.
222 00:24:18.340 ⇒ 00:24:21.350 Brylle Girang: Oh, that, that, that’s, that’s, that’s my, that’s my.
223 00:24:21.350 ⇒ 00:24:22.150 Ashwini Sharma: Okay.
224 00:24:22.150 ⇒ 00:24:26.850 Brylle Girang: Ashwini, so I just, I just tagged it as that so that we can discuss it during this meeting.
225 00:24:27.320 ⇒ 00:24:27.960 Ashwini Sharma: Okay.
226 00:24:28.230 ⇒ 00:24:34.120 Ashwini Sharma: Yeah. Was there any other ticket, similar to this one, that… that you saw in the… Backlog?
227 00:24:35.940 ⇒ 00:24:46.360 Brylle Girang: None so far. I’m still… I’m still trying to clear out and auditing the… the… the boards that we have here, but so far, this is the only one that I wanted to bring up.
228 00:24:46.650 ⇒ 00:24:47.220 Awaish Kumar: Yeah.
229 00:24:48.730 ⇒ 00:25:03.759 Awaish Kumar: for this, like, mainly the engagement report was the one which was in the sprints, and part of that is utility stitching, that is, like, kind of an in progress that also needs to be closed. I don’t know, like,
230 00:25:03.960 ⇒ 00:25:08.440 Awaish Kumar: Utam was the one handling that with Catherine, so…
231 00:25:09.320 ⇒ 00:25:14.850 Awaish Kumar: I just need to hear from him how it… Okay. And also then…
232 00:25:14.950 ⇒ 00:25:18.590 Awaish Kumar: For this week, what’s the plan? Because most of the data modeling ticket.
233 00:25:18.780 ⇒ 00:25:24.959 Awaish Kumar: Like, actually push some PRs and close that out, so we need to see what else we can add in this bit.
234 00:25:25.610 ⇒ 00:25:34.630 Brylle Girang: Okay, gotcha. So, I’ll be working with Utam here, so after we groom the tickets, Utam will be assigning the tickets that needs to be focused on for this cycle.
235 00:25:34.630 ⇒ 00:25:35.290 Awaish Kumar: Yeah.
236 00:25:35.910 ⇒ 00:25:38.770 Brylle Girang: Gotcha. Thank you. Thank you, Amish. Thank you, Ashvini.
237 00:25:39.030 ⇒ 00:25:40.009 Awaish Kumar: Thank you, bye.
238 00:25:40.010 ⇒ 00:25:40.690 Brylle Girang: Bye-bye.