Meeting Title: Data Service Standup Date: 2026-02-25 Meeting participants: Brylle Girang, Mustafa Raja, Awaish Kumar
WEBVTT
1 00:00:35.330 ⇒ 00:00:36.610 Brylle Girang: Hi, Mustafa.
2 00:00:37.710 ⇒ 00:00:38.670 Mustafa Raja: How are you?
3 00:00:39.330 ⇒ 00:00:39.920 Awaish Kumar: Hello?
4 00:00:39.920 ⇒ 00:00:40.890 Brylle Girang: Doing great.
5 00:00:41.380 ⇒ 00:00:41.860 Mustafa Raja: Yeah.
6 00:00:41.860 ⇒ 00:00:42.580 Brylle Girang: OH.
7 00:00:43.350 ⇒ 00:00:59.050 Mustafa Raja: Hey, hey Wish, I need to quickly jump to, AI, one, so I’ll just quickly give my updates. On Eden, what I will be doing, I’ll be adding some more filters, in the dashboards. They enabled,
8 00:00:59.050 ⇒ 00:01:10.519 Mustafa Raja: us to be able to, add filters wherever on the dashboard. It’s a beta version, it’s not public yet, but we got it on, we got it on our Eden instance.
9 00:01:10.600 ⇒ 00:01:13.409 Mustafa Raja: And for default, we are pretty much on track.
10 00:01:15.170 ⇒ 00:01:18.100 Awaish Kumar: And what does you mean by pretty much on track? I…
11 00:01:18.100 ⇒ 00:01:23.929 Mustafa Raja: Yeah, so based on the, Gantt chart, what we need to do is we need to…
12 00:01:24.370 ⇒ 00:01:29.530 Mustafa Raja: you know, deliver some dashboards, and Demi… Demi is working on that.
13 00:01:31.520 ⇒ 00:01:32.380 Awaish Kumar: Okay.
14 00:01:37.320 ⇒ 00:01:37.709 Mustafa Raja: Yeah, I need…
15 00:01:37.710 ⇒ 00:01:43.699 Awaish Kumar: Okay, I’m not seeing the updates anymore. These were updated before this meeting.
16 00:01:43.880 ⇒ 00:01:45.260 Awaish Kumar: Okay.
17 00:01:47.030 ⇒ 00:01:47.970 Awaish Kumar: Yeah.
18 00:01:48.520 ⇒ 00:01:55.940 Awaish Kumar: Okay, yeah, I think we can then… I think I then maybe should do a thing, because nobody has actually joined.
19 00:01:56.690 ⇒ 00:01:57.510 Awaish Kumar: Wow.
20 00:01:57.800 ⇒ 00:02:02.149 Brylle Girang: I have some, few talking points for Element and CTA.
21 00:02:02.990 ⇒ 00:02:04.300 Brylle Girang: Okay, so…
22 00:02:04.300 ⇒ 00:02:12.740 Awaish Kumar: For CTA, we discussed about the four work streams, that was, the scanner data, which is already cleaned, per Ashwini.
23 00:02:12.740 ⇒ 00:02:27.229 Brylle Girang: The second one is identity stitching, which they’re still discussing through the group chat. The third one is ETL tool alternative, and then the fourth one is the Snowflake, or the Cortex AI. Third and fourth are still block.
24 00:02:28.200 ⇒ 00:02:31.100 Brylle Girang: So, for CTA… Yep, sure.
25 00:02:32.130 ⇒ 00:02:36.629 Awaish Kumar: Yeah, so, yeah, sorry, I was just, looking at linear. Can we…
26 00:02:36.790 ⇒ 00:02:40.129 Awaish Kumar: Okay, can you, like, repeat your last sentence?
27 00:02:40.430 ⇒ 00:02:51.580 Brylle Girang: Oh yeah, so for… to summarize, scanner data is already complete, it has been cleaned per Ashwini, it has been already ingested, so that’s good.
28 00:02:51.990 ⇒ 00:03:02.379 Brylle Girang: For identity stitching, still discussing, Ashwini and Otame are discussing that. The ETL tool alternative, I think Ashwini’s still on that.
29 00:03:02.650 ⇒ 00:03:06.839 Awaish Kumar: I just, like, we just… I’m just out of CTM meeting just now.
30 00:03:07.730 ⇒ 00:03:23.179 Awaish Kumar: And so there are… now the pillar… like, we have got a few new… new priorities, right? Identity switching is part of it, so we have to close it. Like, it… it’s like, that we have… I had a
31 00:03:23.380 ⇒ 00:03:31.260 Awaish Kumar: Already had a document on how to do that, and now we just have to assign it, maybe to,
32 00:03:31.380 ⇒ 00:03:32.640 Awaish Kumar: Tractionally.
33 00:03:32.750 ⇒ 00:03:42.579 Awaish Kumar: Okay. That ticket, so he can actually implement that, so that’s number one thing. Second thing, there is a priority, there is a CES data.
34 00:03:42.660 ⇒ 00:03:57.639 Awaish Kumar: So she will be, like, she means Catherine will be sending some reports to us, maybe she will upload just on S3. So this is, like, reports for CES event.
35 00:03:58.010 ⇒ 00:04:00.919 Awaish Kumar: And it… it has a lot of modeling and,
36 00:04:01.550 ⇒ 00:04:05.439 Awaish Kumar: modeling work. So we will be working on that this week.
37 00:04:05.440 ⇒ 00:04:06.729 Brylle Girang: Okay, gotcha.
38 00:04:06.960 ⇒ 00:04:11.820 Awaish Kumar: Yeah, so, like, maybe we can use a transcript from our
39 00:04:11.980 ⇒ 00:04:15.549 Awaish Kumar: meeting with CTA, and create the tickets.
40 00:04:15.820 ⇒ 00:04:17.410 Brylle Girang: Okay, okay.
41 00:04:17.440 ⇒ 00:04:24.870 Awaish Kumar: Yeah, so… yeah, so she… like, Catherine was giving a walkthrough of all the tables and things in the report.
42 00:04:24.940 ⇒ 00:04:38.480 Awaish Kumar: And maybe, you… obviously, you… the… with the… from the transcript, like, LRM can’t see it, but I think with the words, maybe it can pick it up, so it might have different table names, and…
43 00:04:38.580 ⇒ 00:04:46.390 Awaish Kumar: Something like that, and we can create tickets. So, there will be a lot of modeling work out of it, and maybe that is the target for this week.
44 00:04:46.580 ⇒ 00:04:49.439 Brylle Girang: Okay. Is that for wholesale or retail?
45 00:04:50.340 ⇒ 00:04:51.760 Awaish Kumar: I’m talking about CTA.
46 00:04:52.320 ⇒ 00:04:57.299 Brylle Girang: Oh, sorry, sorry, I got confused, I was talking about Element. Okay, gotcha, CTA, okay.
47 00:04:57.300 ⇒ 00:05:02.340 Awaish Kumar: ATA or CES audit report, you can say, so there are… Okay.
48 00:05:02.460 ⇒ 00:05:07.020 Awaish Kumar: Two different reports we talked about, and then there will be a lot of modeling work out of it.
49 00:05:07.020 ⇒ 00:05:10.940 Brylle Girang: Okay, gotcha. Okay, I’m going to create linear tickets for that.
50 00:05:11.340 ⇒ 00:05:12.430 Awaish Kumar: Perfect.
51 00:05:12.430 ⇒ 00:05:20.219 Brylle Girang: Alright, so that’s it for Element. I’m just going to share my screen. I’m going to clarify with you the
52 00:05:20.610 ⇒ 00:05:21.709 Brylle Girang: the progress…
53 00:05:23.880 ⇒ 00:05:25.800 Awaish Kumar: Okay, I can do that.
54 00:05:26.760 ⇒ 00:05:28.050 Brylle Girang: Can you see my screen now?
55 00:05:30.630 ⇒ 00:05:31.909 Awaish Kumar: Nope.
56 00:05:32.930 ⇒ 00:05:34.949 Brylle Girang: Oh, let me try it again.
57 00:05:38.580 ⇒ 00:05:39.280 Brylle Girang: How about now?
58 00:05:39.280 ⇒ 00:05:39.980 Awaish Kumar: Okay.
59 00:05:40.330 ⇒ 00:05:41.730 Brylle Girang: Yeah, I can sign up.
60 00:05:42.150 ⇒ 00:05:47.389 Brylle Girang: Okay, so stored in Gorgeous, you mentioned that we have already kicked off ingestion, I mark it as done.
61 00:05:47.610 ⇒ 00:05:51.989 Brylle Girang: Amazon and Spins are blocked, since we’re waiting for credentials.
62 00:05:52.300 ⇒ 00:05:55.200 Awaish Kumar: Amazon is blog until Tuesday next week.
63 00:05:55.200 ⇒ 00:05:56.660 Brylle Girang: Yeah, so…
64 00:05:56.660 ⇒ 00:05:57.829 Awaish Kumar: Then we will have it.
65 00:05:58.230 ⇒ 00:06:00.320 Brylle Girang: Gotcha. Spins is also block.
66 00:06:00.690 ⇒ 00:06:01.330 Brylle Girang: It’s been…
67 00:06:01.330 ⇒ 00:06:08.810 Awaish Kumar: sure what to… like, I need maybe Utam’s direction here, because, like, they…
68 00:06:08.990 ⇒ 00:06:17.559 Awaish Kumar: their executives, like, Elements executives, also bumped the email that we were sending, and they didn’t respond.
69 00:06:18.350 ⇒ 00:06:19.620 Brylle Girang: Okay, gotcha.
70 00:06:20.620 ⇒ 00:06:26.000 Awaish Kumar: So… It’s kind of blocked because Spin’s team is not replying to our email.
71 00:06:26.360 ⇒ 00:06:31.180 Brylle Girang: Okay, okay, so I’m just going to ask Utam to jump in on this.
72 00:06:31.390 ⇒ 00:06:34.910 Brylle Girang: For reportings, I’m going to confirm this with…
73 00:06:35.380 ⇒ 00:06:43.980 Brylle Girang: with Amber, if these are already done, because this is overdue, but I think on… what I need help from you is with the retail modeling.
74 00:06:44.830 ⇒ 00:06:45.190 Awaish Kumar: Really?
75 00:06:45.190 ⇒ 00:06:46.140 Brylle Girang: retail model.
76 00:06:46.350 ⇒ 00:06:49.629 Awaish Kumar: We already have retail model done, you can say.
77 00:06:49.630 ⇒ 00:06:50.170 Brylle Girang: Okay.
78 00:06:50.170 ⇒ 00:07:00.460 Awaish Kumar: Retail sales modeling is done for both, Walmart and… then there is some inventory modeling, like, I already done that, like.
79 00:07:00.620 ⇒ 00:07:09.790 Awaish Kumar: For the retail inventory data models, that is also, like, base models are done. I don’t know how to segregate them.
80 00:07:10.020 ⇒ 00:07:26.459 Awaish Kumar: like, I’m talking about Immersion. Immersion is a source which has data for both Walmart and Target, which we just said done, right? And there is two pieces in that modeling, like, line number 45 and 46. I’m still talking about those. Yeah.
81 00:07:26.710 ⇒ 00:07:29.679 Awaish Kumar: So in this modeling, there is,
82 00:07:30.110 ⇒ 00:07:34.310 Awaish Kumar: Like, sales data and inventory data, like, two different types of data.
83 00:07:34.310 ⇒ 00:07:34.650 Brylle Girang: Okay.
84 00:07:34.650 ⇒ 00:07:48.719 Awaish Kumar: Sales is what stores are selling to their customers. We have modeled out. Then there’s inventory data, like what sales… what those stores have in their stock. I have some models, but…
85 00:07:48.810 ⇒ 00:07:55.839 Awaish Kumar: I think Amber or Jasmine is going to work on the reporting, hence there will be some new requests come.
86 00:07:55.970 ⇒ 00:07:58.300 Awaish Kumar: And I have to support them.
87 00:07:58.530 ⇒ 00:07:59.990 Brylle Girang: Okay, gotcha.
88 00:08:02.040 ⇒ 00:08:10.299 Brylle Girang: Just going to adjust this. Okay, and then, since you mentioned that modeling is done for Walmart and Target, is that going to affect the where to go?
89 00:08:10.520 ⇒ 00:08:11.540 Brylle Girang: Modeling?
90 00:08:11.790 ⇒ 00:08:17.850 Awaish Kumar: No, so… Affect… what do you mean by affecting, like, the lake, or…
91 00:08:18.250 ⇒ 00:08:22.830 Brylle Girang: You mentioned that… wait, just a moment, let me just bring that up.
92 00:08:26.460 ⇒ 00:08:29.969 Awaish Kumar: Yeah, okay, so you’re referring to my message when I say.
93 00:08:29.970 ⇒ 00:08:30.450 Brylle Girang: Yeah, yeah.
94 00:08:30.890 ⇒ 00:08:33.529 Awaish Kumar: That’s what I’m… I was… I’m just saying, that…
95 00:08:34.030 ⇒ 00:08:50.779 Awaish Kumar: or, like, as I just mentioned, that for retail, we have inventory models ready, right? But when Ember is going to work on that, or Jasmine is going to work on that, then… then I’m going to know, like, what exactly…
96 00:08:52.220 ⇒ 00:09:07.450 Awaish Kumar: I have, like, base model, like, customers, stores, inventory, but they might need it in a different format, they might ask me to create new metrics, or change the format of the table, so I have to do that to support them.
97 00:09:07.550 ⇒ 00:09:17.219 Brylle Girang: Okay, okay, gotcha. So, basically, you’re waiting for Amber and Jasmine instead of you for the retail inventory modeling for you to proceed with where to go?
98 00:09:18.060 ⇒ 00:09:20.619 Awaish Kumar: No, to proceed with the retail reporting.
99 00:09:20.620 ⇒ 00:09:21.740 Brylle Girang: Very detailed reporting.
100 00:09:21.740 ⇒ 00:09:25.429 Awaish Kumar: Yeah, where to go is just… we didn’t start it on that yet, because…
101 00:09:25.430 ⇒ 00:09:27.629 Brylle Girang: You are busy with all the other morning.
102 00:09:27.960 ⇒ 00:09:28.360 Brylle Girang: Okay.
103 00:09:28.710 ⇒ 00:09:29.660 Awaish Kumar: detail.
104 00:09:29.770 ⇒ 00:09:40.430 Awaish Kumar: Right now, like, I’m still getting some requests from Amber to help her with wholesale, like, we are, like, iterating our models, like, we create models.
105 00:09:40.430 ⇒ 00:09:40.800 Brylle Girang: Yeah.
106 00:09:40.800 ⇒ 00:09:46.379 Awaish Kumar: But then straight over it to fix a few things, fix definitions, how… so…
107 00:09:46.620 ⇒ 00:09:55.940 Awaish Kumar: So we spent time on that, so we didn’t start it where to go, because where to go is actually kind of, tied with e-comm Data Mart.
108 00:09:56.470 ⇒ 00:10:06.319 Awaish Kumar: Where to Go is e-commerce data modeling, where we… like, Where2Go is a shipping com… like, company, or what you can say. So…
109 00:10:06.440 ⇒ 00:10:10.749 Awaish Kumar: For the online orders we get through e-commerce platforms, where to go
110 00:10:10.920 ⇒ 00:10:24.910 Awaish Kumar: does the fulfillment, right? And we have fulfilled the data where to go. So it will go… it is going to be started with e-com data modeling, and for the e-comm, we can, I think,
111 00:10:25.240 ⇒ 00:10:32.109 Awaish Kumar: since we are… we don’t have any… I think, we can start now as we,
112 00:10:33.140 ⇒ 00:10:40.030 Awaish Kumar: We are almost done with retail and wholesale. Yeah, we can start with e-com.
113 00:10:40.220 ⇒ 00:10:41.010 Brylle Girang: We do commerce.
114 00:10:41.730 ⇒ 00:10:43.920 Awaish Kumar: So, all what that means is…
115 00:10:44.020 ⇒ 00:10:49.250 Awaish Kumar: for e-com, we only have Shopify data right now. I can…
116 00:10:49.640 ⇒ 00:11:03.670 Awaish Kumar: And we already have that. So I can start with where to go, but yeah, we just want to extend the rates. Like, I don’t… we don’t want to do it, right, in parallel… parallel with other stuff, because…
117 00:11:03.860 ⇒ 00:11:04.390 Brylle Girang: Yeah.
118 00:11:04.580 ⇒ 00:11:08.699 Awaish Kumar: There’s a lot of requests in retail, we are not going to do that, and then we have…
119 00:11:08.850 ⇒ 00:11:09.920 Awaish Kumar: Yeah, we don’t…
120 00:11:10.030 ⇒ 00:11:15.689 Awaish Kumar: want to be sound like we delayed things, like, instead of we take our time in the Gantt chart.
121 00:11:16.270 ⇒ 00:11:19.049 Brylle Girang: Okay, okay, gotcha. So I will be updating this.
122 00:11:19.290 ⇒ 00:11:23.430 Brylle Girang: This e-commerce Section, and then just move them.
123 00:11:23.860 ⇒ 00:11:24.520 Brylle Girang: Far away.
124 00:11:24.520 ⇒ 00:11:29.880 Awaish Kumar: Okay. For e-commerce, we will start now, but we didn’t start it, you can see.
125 00:11:30.100 ⇒ 00:11:41.779 Awaish Kumar: We started… we have ingested, you can say, we ingested Shopify, we ingested Where2Go, we ingested Stored, we ingested, we are… we will be ingesting Amazon next week.
126 00:11:43.760 ⇒ 00:11:57.600 Awaish Kumar: we also ingested some marketing, I don’t know where to put this, because, marketing, platforms, like Facebook, Google Ads, they’re currently in their…
127 00:11:57.760 ⇒ 00:12:00.140 Awaish Kumar: company, like, e-com…
128 00:12:01.000 ⇒ 00:12:09.620 Awaish Kumar: head is actually managing those platforms, so I’m not sure if that should be the part of e-com modeling, or it is just separate marketing modeling, marketing…
129 00:12:09.620 ⇒ 00:12:10.220 Brylle Girang: You know.
130 00:12:10.750 ⇒ 00:12:25.969 Awaish Kumar: So where should it go? Like, should we pair it with this, or should we keep it outside? We need to… and that we will know when, like, for example, Amber starts reporting, then we get the feedback from client, okay, I need these metrics. So we know, like.
131 00:12:26.600 ⇒ 00:12:41.849 Awaish Kumar: where those metrics are coming from. Are they coming from just the e-com sources, or they are also coming from marketing sources? So, you can just say that… in the injection, we can say that all these sources are done, but here we… we have to…
132 00:12:42.110 ⇒ 00:12:51.200 Awaish Kumar: Split our… e-com data model, yeah, then we split with buy source. Shopify modeling, where to go,
133 00:12:51.330 ⇒ 00:12:57.669 Awaish Kumar: stored, and then maybe we can say Facebook, Google, if we need.
134 00:12:58.680 ⇒ 00:13:00.190 Brylle Girang: Okay, gotcha.
135 00:13:02.350 ⇒ 00:13:13.720 Brylle Girang: Okay, okay. I think I’m all good here, and then the other projects, I think, are being blocked by Element themselves. For example, BI Evaluation, right? This is under Element.
136 00:13:16.200 ⇒ 00:13:20.430 Awaish Kumar: BI evaluation, evaluation, I think yes, yes.
137 00:13:20.430 ⇒ 00:13:20.950 Brylle Girang: Okay.
138 00:13:21.870 ⇒ 00:13:27.420 Brylle Girang: Alright, gotcha. Thank you so much for explaining those to me, Awash, that’s really helpful.
139 00:13:27.420 ⇒ 00:13:28.130 Awaish Kumar: Oh, no.
140 00:13:28.510 ⇒ 00:13:29.180 Awaish Kumar: Yep.
141 00:13:29.570 ⇒ 00:13:38.979 Brylle Girang: I think I’m all good, so that’s just LMNCTA, Magic Spoons, I haven’t heard from the Miladi yet. I don’t think the SOW has been signed.
142 00:13:39.110 ⇒ 00:13:41.599 Brylle Girang: And then… yeah, that’s it for me.
143 00:13:42.390 ⇒ 00:13:43.520 Awaish Kumar: Okay, thank you.
144 00:13:43.520 ⇒ 00:13:44.580 Brylle Girang: Thank you, bye-bye.