Meeting Title: DE-AE-AI Standup Date: 2025-12-09 Meeting participants: Awaish Kumar, Casie Aviles, Ashwini Sharma, Elizah Joy, Rico Rejoso, Gabriel Lam, Mustafa Raja, Demilade Agboola, Zoran Selinger, Uttam Kumaran
WEBVTT
1 00:05:39.690 ⇒ 00:05:41.420 Awaish Kumar: Hello, everyone.
2 00:05:44.300 ⇒ 00:05:45.400 Gabriel Lam: Morning.
3 00:05:45.880 ⇒ 00:05:46.840 Rico Rejoso: Morning, guys.
4 00:05:48.500 ⇒ 00:05:49.460 Ashwini Sharma: Hey, money.
5 00:06:04.740 ⇒ 00:06:06.830 Awaish Kumar: Yeah, we can maybe start,
6 00:06:07.580 ⇒ 00:06:11.180 Awaish Kumar: Start off with the projects where we have the people.
7 00:06:13.090 ⇒ 00:06:15.540 Awaish Kumar: And we can start with,
8 00:06:19.450 ⇒ 00:06:22.380 Awaish Kumar: basically… Eden?
9 00:06:22.730 ⇒ 00:06:29.799 Awaish Kumar: So, Casey… Have you worked on…
10 00:06:30.690 ⇒ 00:06:33.340 Awaish Kumar: Anything on, Alien last week?
11 00:06:33.490 ⇒ 00:06:34.750 Awaish Kumar: Or this week.
12 00:06:36.030 ⇒ 00:06:36.630 Casie Aviles: Yeah,
13 00:06:36.760 ⇒ 00:06:43.629 Casie Aviles: I was out yesterday, last week. What I did, work on was there was just a request
14 00:06:44.790 ⇒ 00:06:51.369 Casie Aviles: Matthias… And then I just made changes to, like, the spreadsheet.
15 00:06:51.970 ⇒ 00:06:59.990 Casie Aviles: That, you know, for November reconciliation, but that should be done For this week.
16 00:07:00.610 ⇒ 00:07:07.459 Casie Aviles: Yeah, I guess my… one of the open items I have was with… regarding the cancellation analysis.
17 00:07:07.910 ⇒ 00:07:09.100 Casie Aviles: So…
18 00:07:09.570 ⇒ 00:07:12.830 Awaish Kumar: Did you know if you are working on even this?
19 00:07:13.230 ⇒ 00:07:14.050 Awaish Kumar: Week?
20 00:07:16.280 ⇒ 00:07:18.250 Casie Aviles: I’m…
21 00:07:18.510 ⇒ 00:07:22.179 Awaish Kumar: Maybe, like, I think we just already changed a few things.
22 00:07:22.720 ⇒ 00:07:28.520 Casie Aviles: Oh, yeah, I wasn’t… I’m not aware if there were any changes to, like, the workload.
23 00:07:29.890 ⇒ 00:07:33.060 Casie Aviles: Or, like, yeah, the assignments, I mean, yeah.
24 00:07:34.020 ⇒ 00:07:37.439 Awaish Kumar: Okay, mostly I think you’re on ABC and Insomnia.
25 00:07:37.580 ⇒ 00:07:38.600 Awaish Kumar: So…
26 00:07:39.150 ⇒ 00:07:49.289 Awaish Kumar: Yeah, you can… you can, like, share the… whatever you have been working on on the agent with the team, like, the conclude, like, Aiden’s,
27 00:07:50.570 ⇒ 00:07:51.700 Awaish Kumar: Despite…
28 00:07:52.990 ⇒ 00:07:57.110 Casie Aviles: Yes, for the spike, I did test with…
29 00:07:58.420 ⇒ 00:08:05.789 Casie Aviles: the two tools that I have so far. I didn’t get to test, like, every tool that was suggested, I think.
30 00:08:06.000 ⇒ 00:08:09.930 Casie Aviles: That was gonna take up more time, so I just went with what we had.
31 00:08:10.850 ⇒ 00:08:14.690 Casie Aviles: And that would be Omni and…
32 00:08:15.510 ⇒ 00:08:23.910 Casie Aviles: the other two, Wabi, so I think the recommendation is still with Omni, because I managed to…
33 00:08:25.650 ⇒ 00:08:29.189 Casie Aviles: also get that looked by Demilade, and he said.
34 00:08:29.730 ⇒ 00:08:37.210 Casie Aviles: I’m not sure if you… yeah, yeah, I think the results were more positive, and we also briefly talked about
35 00:08:37.610 ⇒ 00:08:42.440 Casie Aviles: how we could also improve it by connecting… being able to connect dbt as well.
36 00:08:42.929 ⇒ 00:08:44.780 Casie Aviles: Too long, which is good.
37 00:08:45.390 ⇒ 00:08:47.210 Casie Aviles: So I guess…
38 00:08:47.690 ⇒ 00:08:53.920 Awaish Kumar: Yeah, yeah, but my point is that we have been connecting only with DPT, and, like, whatever your conclusions are.
39 00:08:54.380 ⇒ 00:09:02.229 Awaish Kumar: In terms of, like, how we are going to propose to our clients, like, when they…
40 00:09:03.060 ⇒ 00:09:09.979 Awaish Kumar: They want to, like, interact with the data using human language, like, natural language.
41 00:09:09.980 ⇒ 00:09:10.630 Casie Aviles: Hmm.
42 00:09:11.500 ⇒ 00:09:19.549 Awaish Kumar: Whatever the conclusion is, you can just, like, have a final document and share it with the team, and then, yeah.
43 00:09:19.990 ⇒ 00:09:28.680 Awaish Kumar: maybe, you know, we can decide on who’s going to work on the implementation part, but for now, I think, yeah, that’s the goal for you.
44 00:09:30.210 ⇒ 00:09:38.069 Casie Aviles: Yeah, I think what Utam was asking is to also create, like, a slide deck already for this.
45 00:09:39.450 ⇒ 00:09:40.650 Casie Aviles: So…
46 00:09:41.340 ⇒ 00:09:49.260 Casie Aviles: I guess, for me, my next step is to create the slide deck already with the recommendations, and then I can also
47 00:09:49.730 ⇒ 00:09:55.299 Casie Aviles: ask marketing for some support there. I think that’s… that’s all I have for that.
48 00:09:56.010 ⇒ 00:09:56.690 Awaish Kumar: Okay.
49 00:09:57.150 ⇒ 00:10:01.459 Awaish Kumar: So, like, this have the final… you’re saying, a document? Yeah, yeah.
50 00:10:01.460 ⇒ 00:10:02.409 Casie Aviles: Yeah, that’s…
51 00:10:02.480 ⇒ 00:10:07.040 Awaish Kumar: Yeah, that’s… This one.
52 00:10:07.680 ⇒ 00:10:08.580 Awaish Kumar: Okay
53 00:10:11.370 ⇒ 00:10:18.550 Awaish Kumar: Okay, yeah, just wrap it up, and then… yeah, we can decide how we are going to work on
54 00:10:19.030 ⇒ 00:10:20.270 Awaish Kumar: Implementing it.
55 00:10:21.140 ⇒ 00:10:22.160 Awaish Kumar: Hmm. Okay.
56 00:10:22.720 ⇒ 00:10:30.589 Awaish Kumar: And then for Ashwini, so, like, where are we with monitoring set of… monitors set up?
57 00:10:30.770 ⇒ 00:10:31.980 Ashwini Sharma: Yeah, so…
58 00:10:32.350 ⇒ 00:10:38.830 Ashwini Sharma: Yes, so the freshness monitor is already set up, right? I’m working on other monitors, basically the row count and…
59 00:10:39.210 ⇒ 00:10:48.460 Ashwini Sharma: The custom logic, right? I think there is a bunch of monitors for calculating some,
60 00:10:49.030 ⇒ 00:10:52.740 Ashwini Sharma: Maybe, like, we’ll have to pause those monitors and then create,
61 00:10:53.500 ⇒ 00:10:56.709 Ashwini Sharma: Create more specific monitors that targets,
62 00:10:57.630 ⇒ 00:11:00.370 Ashwini Sharma: Yeah, we are more interested in…
63 00:11:00.540 ⇒ 00:11:05.890 Awaish Kumar: Setting up freshness monitors, and some monitors, or roll count.
64 00:11:06.020 ⇒ 00:11:11.040 Awaish Kumar: This week, on core tables, along with, whatever
65 00:11:11.160 ⇒ 00:11:24.419 Awaish Kumar: change you can make. For example, for each monitor, you can basically customize… like, there are two ways it spits the… like, it sends the alerts to Slack. One is automatic.
66 00:11:24.770 ⇒ 00:11:27.710 Awaish Kumar: Model the train and find the anomalies.
67 00:11:28.000 ⇒ 00:11:32.629 Awaish Kumar: Second one is, we can say, like, as you have already shared, like.
68 00:11:32.630 ⇒ 00:11:33.180 Ashwini Sharma: Yep.
69 00:11:34.240 ⇒ 00:11:36.220 Awaish Kumar: Right, right, right, yeah.
70 00:11:36.390 ⇒ 00:11:45.599 Ashwini Sharma: So, for those sum and row counts, we’ll rely on the machine learning algorithm that is there within Metaplane, and it decides when some
71 00:11:45.950 ⇒ 00:11:53.310 Ashwini Sharma: Row count or sum of a column goes beyond a certain limit. But if you look at the message that,
72 00:11:53.850 ⇒ 00:11:56.170 Ashwini Sharma: Somebody had sent, right? Mitheis, or…
73 00:11:56.510 ⇒ 00:11:59.340 Awaish Kumar: Yeah, but that’s… that’s not focused for this week.
74 00:11:59.510 ⇒ 00:12:09.140 Ashwini Sharma: Okay, okay. So this week is only freshness, and row count for core tables, and, what do you call it, sum for certain columns, right?
75 00:12:09.800 ⇒ 00:12:16.370 Awaish Kumar: And then, like, like, if you recall what Utam said, like, we need these monitors set up, and…
76 00:12:16.790 ⇒ 00:12:23.869 Awaish Kumar: I’m assuming that whatever allowed this and is P0 for us to action on it.
77 00:12:23.870 ⇒ 00:12:24.540 Ashwini Sharma: Yep.
78 00:12:24.550 ⇒ 00:12:27.679 Awaish Kumar: Right. Let’s just focus on that part of it.
79 00:12:29.970 ⇒ 00:12:35.090 Awaish Kumar: So, apart from that, so, did you work on anything?
80 00:12:35.500 ⇒ 00:12:43.289 Ashwini Sharma: No, I haven’t got a chance to work on other stuff. I have to refactor that CAPI metamodel.
81 00:12:43.580 ⇒ 00:12:50.230 Ashwini Sharma: I did a quick debugging for that order summary, right? There is a logic that needs to change, this one.
82 00:12:50.790 ⇒ 00:12:58.000 Ashwini Sharma: The current logic, which calculates the hours between ship date, sent to pharmacy date, and ship date.
83 00:12:58.120 ⇒ 00:13:01.390 Ashwini Sharma: That excludes the weekends. That… that is wrong.
84 00:13:01.680 ⇒ 00:13:04.089 Ashwini Sharma: So, we need to fix that.
85 00:13:10.990 ⇒ 00:13:13.619 Ashwini Sharma: So, yeah, I’ll take care of that.
86 00:13:13.920 ⇒ 00:13:16.880 Awaish Kumar: That excludes… so, why is that, like…
87 00:13:16.990 ⇒ 00:13:24.419 Awaish Kumar: That, right now, only excludes weekends, and we also wanted to exclude these holidays. That’s… that’s what the task is.
88 00:13:24.640 ⇒ 00:13:31.890 Ashwini Sharma: Right, yes, yes. So, the weekend exclusion part, that is also wrong, right? It’s not correct.
89 00:13:32.310 ⇒ 00:13:42.340 Ashwini Sharma: So, for example, like, if both of them are falling on a weekend, the hours between sent to pharmacy and shipped becomes a negative number.
90 00:13:42.470 ⇒ 00:13:44.050 Ashwini Sharma: So.
91 00:13:44.500 ⇒ 00:13:44.880 Awaish Kumar: Okay.
92 00:13:44.880 ⇒ 00:13:49.730 Ashwini Sharma: Yeah, we need to fix that. And, the additional holidays, right?
93 00:13:49.890 ⇒ 00:13:53.880 Ashwini Sharma: So, maybe, like, I’ll just take a few minutes of your time, right?
94 00:13:54.130 ⇒ 00:13:59.599 Ashwini Sharma: When, when we say that something… for example, like, let’s say,
95 00:14:00.020 ⇒ 00:14:04.819 Ashwini Sharma: Something was sent to pharmacy, an order was sent to pharmacy on a weekend, Saturday, right?
96 00:14:05.380 ⇒ 00:14:06.630 Awaish Kumar: Yeah, we can take it.
97 00:14:06.840 ⇒ 00:14:09.779 Ashwini Sharma: Or, or, let’s take it offline, let’s use this one, yeah.
98 00:14:12.180 ⇒ 00:14:16.090 Awaish Kumar: Okay, yeah, Damalade, I think this is done well.
99 00:14:16.400 ⇒ 00:14:17.220 Awaish Kumar: Nope.
100 00:14:18.860 ⇒ 00:14:29.209 Demilade Agboola: Not particularly. I’m still trying to test it, but my focus here still is default, because that’s kind of what I needed to do. But,
101 00:14:29.760 ⇒ 00:14:33.739 Demilade Agboola: This should be done today, like, unfainly, it’s…
102 00:14:34.470 ⇒ 00:14:37.439 Demilade Agboola: It was just hard to get that over at the line yesterday.
103 00:14:38.390 ⇒ 00:14:39.180 Awaish Kumar: Okay.
104 00:14:40.350 ⇒ 00:14:45.569 Awaish Kumar: Yeah, and for… modeling, I don’t know.
105 00:14:51.150 ⇒ 00:14:52.190 Demilade Agboola: Hmm…
106 00:14:57.030 ⇒ 00:14:59.079 Demilade Agboola: Sorry, do we have cogs?
107 00:14:59.550 ⇒ 00:15:01.989 Demilade Agboola: And we have the values for it.
108 00:15:03.250 ⇒ 00:15:08.190 Awaish Kumar: So, only values which are coming for COGS are from that product mapping sheet, right?
109 00:15:09.260 ⇒ 00:15:13.759 Demilade Agboola: Yeah, for some of them, but, I mean, some of them, we also get…
110 00:15:15.520 ⇒ 00:15:18.740 Demilade Agboola: Where is con… it’s labeled as Contigo.
111 00:15:23.530 ⇒ 00:15:27.279 Demilade Agboola: So, is this… is this a request from Henry?
112 00:15:27.810 ⇒ 00:15:33.439 Awaish Kumar: Seems like it. He just created it yesterday and assigned it to me.
113 00:15:36.090 ⇒ 00:15:39.219 Demilade Agboola: I… I’m not sure I understand what he’s, like, where…
114 00:15:40.090 ⇒ 00:15:43.440 Demilade Agboola: The… what he’s referring to and what the data is.
115 00:15:46.630 ⇒ 00:15:52.730 Awaish Kumar: Okay, yeah, I think he… So, okay, do we have Eden Pharmacy now?
116 00:15:54.810 ⇒ 00:15:58.169 Demilade Agboola: I would have to look into the data. I have online.
117 00:15:59.160 ⇒ 00:16:03.840 Demilade Agboola: essentially been on top of Eden’s data any minute, in that sense, like the products.
118 00:16:04.040 ⇒ 00:16:05.250 Demilade Agboola: A pharmaceutical.
119 00:16:06.680 ⇒ 00:16:13.619 Awaish Kumar: Yeah, like, we had pharmacy data, and we had product information, and the COGS is from… coming from product sheet.
120 00:16:15.780 ⇒ 00:16:19.499 Awaish Kumar: And I don’t think we have any calls coming from… directly from…
121 00:16:22.480 ⇒ 00:16:28.810 Demilade Agboola: Yeah, I know some or… I know there is a COGS… column.
122 00:16:29.000 ⇒ 00:16:38.300 Demilade Agboola: But I also know that it’s very sparsely populated, like, it’s very rarely populated, so… Let me see…
123 00:16:39.030 ⇒ 00:16:42.479 Demilade Agboola: Okay. Yeah, I can look at this offline.
124 00:16:43.780 ⇒ 00:16:45.530 Awaish Kumar: Okay, should I assign it to you then?
125 00:16:46.130 ⇒ 00:16:46.800 Demilade Agboola: Yeah, sure.
126 00:16:57.740 ⇒ 00:17:01.090 Awaish Kumar: Apart from that, like, again, I…
127 00:17:02.880 ⇒ 00:17:10.109 Awaish Kumar: like, we have some, like, meta stuff to push on the Zoran’s plate, and for that, he might need help,
128 00:17:10.520 ⇒ 00:17:13.910 Awaish Kumar: Ashwini from us on the modeling side.
129 00:17:16.160 ⇒ 00:17:18.210 Awaish Kumar: And the… yeah.
130 00:17:19.109 ⇒ 00:17:21.339 Awaish Kumar: Same for Uploons University.
131 00:17:21.349 ⇒ 00:17:25.939 Ashwini Sharma: So, sorry, which one is this? The Cappy?
132 00:17:25.940 ⇒ 00:17:27.950 Awaish Kumar: Yeah, for KP.
133 00:17:28.230 ⇒ 00:17:33.190 Ashwini Sharma: Yeah, yeah, yeah, yeah, I have that on my plate. I’ll get it done as soon as I’m out of this.
134 00:17:34.310 ⇒ 00:17:36.190 Ashwini Sharma: Metaplane.
135 00:17:37.590 ⇒ 00:17:44.030 Awaish Kumar: Yeah, but… like, Metaplan can… can be done by the end of the week.
136 00:17:44.750 ⇒ 00:17:46.840 Awaish Kumar: This one is…
137 00:17:47.150 ⇒ 00:17:48.450 Ashwini Sharma: Higher priority, okay.
138 00:17:49.660 ⇒ 00:18:02.539 Awaish Kumar: So, like, this… Zoran’s work is priority, because he’s blocking Zoran to basically… Okay. So we need to finish it, maybe today, and focus on Metaplan tomorrow. That’s also okay.
139 00:18:03.000 ⇒ 00:18:04.749 Ashwini Sharma: Yeah, okay, alright.
140 00:18:10.830 ⇒ 00:18:13.429 Awaish Kumar: Yeah, Musta, like.
141 00:18:14.190 ⇒ 00:18:16.220 Mustafa Raja: Yeah, so,
142 00:18:16.470 ⇒ 00:18:32.070 Mustafa Raja: For the, for supporting the, dashboard requirements that Caitlin gave us, Demilade, worked on it and has, has a few… has a CSV of the integrations that we are verifying, verifying with Victor.
143 00:18:32.130 ⇒ 00:18:38.240 Mustafa Raja: So he has texted, Victor, regarding that, and apart from that, I shipped
144 00:18:38.400 ⇒ 00:18:42.200 Mustafa Raja: The comparison doc, and then the master list yesterday.
145 00:18:42.370 ⇒ 00:18:48.719 Mustafa Raja: And then what I’m going to do today is I’m going to work on 178.
146 00:18:52.180 ⇒ 00:18:52.960 Awaish Kumar: Okay.
147 00:18:53.070 ⇒ 00:18:54.410 Awaish Kumar: Analyzing.
148 00:18:55.120 ⇒ 00:18:56.519 Mustafa Raja: Yeah, this one, yeah.
149 00:18:57.500 ⇒ 00:18:58.210 Awaish Kumar: Okay.
150 00:18:59.790 ⇒ 00:19:03.390 Awaish Kumar: So, we are done with this. Can we, like…
151 00:19:04.110 ⇒ 00:19:08.520 Mustafa Raja: Yeah, we can move these… both of these to… Done.
152 00:19:09.580 ⇒ 00:19:10.459 Awaish Kumar: And this one.
153 00:19:11.590 ⇒ 00:19:13.110 Mustafa Raja: No, no…
154 00:19:13.500 ⇒ 00:19:25.380 Mustafa Raja: This one, yeah, so Demolati is working on the requires data modeling one. We are verifying, if we have all of the integrations correct.
155 00:19:25.540 ⇒ 00:19:34.820 Mustafa Raja: And then I’ll work on the dashboard updates. So this one needs to stay here. We can move the, master sheet one to done.
156 00:19:35.470 ⇒ 00:19:36.900 Mustafa Raja: The one that’s already…
157 00:19:36.900 ⇒ 00:19:44.779 Awaish Kumar: Camelare, like, we already, like, kind of initiated the DVD project for this, or how are you…
158 00:19:45.420 ⇒ 00:19:49.800 Demilade Agboola: So right now, It seems to be of the utmost urgency.
159 00:19:50.040 ⇒ 00:19:54.260 Demilade Agboola: So, I’m trying to get the numbers out to them,
160 00:19:54.830 ⇒ 00:20:04.530 Demilade Agboola: Like, even if it’s going to be a stored procedure, because it seems we really need it, but I just want to get context of it, but, like, while all that’s going on, I’m also creating dbt, in the background for it.
161 00:20:04.650 ⇒ 00:20:08.379 Demilade Agboola: And I will link it to our GitHub.
162 00:20:08.510 ⇒ 00:20:11.660 Demilade Agboola: And then, initialize dbt for it.
163 00:20:13.160 ⇒ 00:20:13.800 Awaish Kumar: Okay.
164 00:20:13.950 ⇒ 00:20:18.030 Demilade Agboola: So there are two aspects to it. I think one is setting up the whole dbt infrastructure.
165 00:20:18.280 ⇒ 00:20:29.159 Demilade Agboola: For them, and the other aspect is literally giving them the data that they need, because apparently it was, you know, I was talking to Mustaf, and he said he ideally wanted the numbers last week, Friday.
166 00:20:29.580 ⇒ 00:20:35.409 Demilade Agboola: So I’m just trying to see how fast I can get the numbers and the reports across to them.
167 00:20:37.440 ⇒ 00:20:48.630 Awaish Kumar: Okay. So, like, we are working in parallel on a dbt project, right? So, are we using our own GitHub repo, or do they already have one?
168 00:20:49.220 ⇒ 00:20:58.410 Demilade Agboola: I don’t know if they have one, I’ll ask… I’ll ask the team today, but, I normally would, you could just use our repo. But if they have one, we could just integrate with them.
169 00:20:59.070 ⇒ 00:20:59.780 Awaish Kumar: Okay.
170 00:21:01.120 ⇒ 00:21:09.330 Demilade Agboola: So, can we create a separate ticket for… so this modeling is for the dashboard updates, but can we create, like, a dbt ticket?
171 00:21:09.470 ⇒ 00:21:10.300 Demilade Agboola: Specifically.
172 00:21:11.770 ⇒ 00:21:16.800 Awaish Kumar: Oh, yeah, I can… Yeah, there was one assigned to… no.
173 00:21:17.220 ⇒ 00:21:17.810 Awaish Kumar: That was amazing.
174 00:21:17.810 ⇒ 00:21:23.900 Mustafa Raja: Again… In terms of repositories, we have two repositories linked with,
175 00:21:24.810 ⇒ 00:21:33.890 Mustafa Raja: default, one is in their GitHub, named Brainforce BI, and then one is in our GitHub, named Default Browser Base.
176 00:21:36.420 ⇒ 00:21:41.630 Demilade Agboola: Okay, I think we can integrate with them for default… default BI.
177 00:21:42.600 ⇒ 00:21:43.160 Mustafa Raja: Yeah.
178 00:21:43.200 ⇒ 00:21:49.990 Demilade Agboola: I’ll look at what you have there, and then maybe we can create our own, like, a separate repo within…
179 00:21:51.170 ⇒ 00:21:51.790 Demilade Agboola: Yes.
180 00:21:53.250 ⇒ 00:21:58.149 Awaish Kumar: So, I’ve created a ticket for you, like, demo RDA for dbt initialization, this one.
181 00:21:58.150 ⇒ 00:21:58.759 Demilade Agboola: Oh, okay.
182 00:21:59.750 ⇒ 00:22:04.980 Awaish Kumar: dashboarding, and then I also created… yesterday…
183 00:22:05.610 ⇒ 00:22:08.669 Awaish Kumar: One for product data modeling, so…
184 00:22:08.800 ⇒ 00:22:11.670 Awaish Kumar: This is basically creating a data model.
185 00:22:11.990 ⇒ 00:22:15.179 Awaish Kumar: of the data, which is going to come in Superbase, so…
186 00:22:15.530 ⇒ 00:22:18.179 Awaish Kumar: Do we have any updates, Mustava, on…
187 00:22:18.370 ⇒ 00:22:21.400 Awaish Kumar: from Thomas on this data, supervisor, from Supervisors.
188 00:22:21.400 ⇒ 00:22:32.239 Mustafa Raja: Yeah, we do not have any updates regarding that, but let me know if I should ping Thomas, just to see where we are at with this stuff.
189 00:22:32.500 ⇒ 00:22:33.340 Awaish Kumar: Okay, did we…
190 00:22:33.340 ⇒ 00:22:36.269 Mustafa Raja: It’s been a week, though, so should I… should I ping him?
191 00:22:36.710 ⇒ 00:22:38.040 Awaish Kumar: Yeah, you can ask.
192 00:22:38.210 ⇒ 00:22:39.859 Awaish Kumar: For updates.
193 00:22:39.860 ⇒ 00:22:47.500 Mustafa Raja: Yeah, yeah, okay, okay. Then I’ll ping him today, right after this meeting, and update this ticket with whatever his response would be.
194 00:22:47.900 ⇒ 00:22:48.560 Awaish Kumar: Okay.
195 00:22:53.060 ⇒ 00:22:59.899 Awaish Kumar: Then for… ABC, Casey, like, very…
196 00:23:00.220 ⇒ 00:23:02.190 Awaish Kumar: Where are we with this,
197 00:23:04.110 ⇒ 00:23:08.549 Awaish Kumar: Like, the consolidating all the logs, and the migration work.
198 00:23:09.590 ⇒ 00:23:13.280 Casie Aviles: Yeah, for the consolidation of logs, I have,
199 00:23:13.810 ⇒ 00:23:19.140 Casie Aviles: document, a Notion document, that is, in progress. I can share it.
200 00:23:19.580 ⇒ 00:23:20.880 Casie Aviles: In the channel.
201 00:23:21.490 ⇒ 00:23:22.620 Awaish Kumar: Yeah, please.
202 00:23:24.640 ⇒ 00:23:29.950 Casie Aviles: Yeah, it’s mostly just a summary for now of, like, areas that are…
203 00:23:30.480 ⇒ 00:23:35.470 Casie Aviles: That we constantly get feedback on, so… Oh my god.
204 00:23:35.610 ⇒ 00:23:39.369 Awaish Kumar: Like, kind of what we need to do in that document is, like, have a…
205 00:23:40.040 ⇒ 00:23:46.669 Awaish Kumar: Summary of, like, what component of our The workflow is failing.
206 00:23:46.930 ⇒ 00:23:48.829 Awaish Kumar: And how frequently?
207 00:23:49.350 ⇒ 00:23:58.489 Awaish Kumar: And then, like… We can identify, like, you can propose, like, these are the components which fail regularly, like.
208 00:23:59.060 ⇒ 00:24:02.849 Awaish Kumar: One or two, whatever you feel like, and then…
209 00:24:03.220 ⇒ 00:24:06.590 Awaish Kumar: Then resume, like, what do you propose as a solution?
210 00:24:06.840 ⇒ 00:24:11.500 Awaish Kumar: And, like, and then you can share it with an internal… Jenna.
211 00:24:13.500 ⇒ 00:24:15.569 Casie Aviles: Okay. Yeah, I’ll just…
212 00:24:16.100 ⇒ 00:24:23.709 Casie Aviles: Yeah, I’ll add that and make sure those questions are also covered. I’ll also just share the doc for now, as I work on it.
213 00:24:24.390 ⇒ 00:24:30.440 Awaish Kumar: Okay, and apart from that, regarding migration, have you been working on that?
214 00:24:32.740 ⇒ 00:24:43.279 Casie Aviles: for the migration, that was a bit… yeah, that was delayed a little bit, because I was working on… more on, like, addressing, like, the immediate issues, so…
215 00:24:45.260 ⇒ 00:24:48.750 Awaish Kumar: Okay. This week. Tickets, like, what?
216 00:24:49.040 ⇒ 00:24:52.649 Awaish Kumar: On where… on what, like, what things you have been working on?
217 00:24:53.350 ⇒ 00:24:58.200 Casie Aviles: Yeah, so for… I have one ticket there, which is for, like.
218 00:24:58.340 ⇒ 00:25:04.639 Casie Aviles: the migration of Andy into code. And, yeah, that one I haven’t really finished yet.
219 00:25:07.570 ⇒ 00:25:09.420 Awaish Kumar: Hmm… Which one?
220 00:25:09.860 ⇒ 00:25:21.760 Casie Aviles: Oh, sorry, it’s… it should be in progress, it’s, andy, I believe… Any end-to-master migration.
221 00:25:21.760 ⇒ 00:25:22.130 Awaish Kumar: Okay.
222 00:25:22.130 ⇒ 00:25:22.830 Casie Aviles: this one.
223 00:25:24.550 ⇒ 00:25:25.800 Casie Aviles: Yeah, that one.
224 00:25:26.240 ⇒ 00:25:29.470 Awaish Kumar: Is this one for migration, right?
225 00:25:29.840 ⇒ 00:25:30.540 Casie Aviles: Yes.
226 00:25:31.130 ⇒ 00:25:36.020 Awaish Kumar: But the kind of things you have been working on right now, like, immediate things.
227 00:25:36.180 ⇒ 00:25:40.070 Awaish Kumar: You can… you can add the tickets here for those as well.
228 00:25:42.430 ⇒ 00:25:43.100 Casie Aviles: Okay.
229 00:25:43.410 ⇒ 00:25:47.710 Awaish Kumar: Yeah, some of those were triage tickets that were already…
230 00:25:47.710 ⇒ 00:25:48.760 Casie Aviles: resolved.
231 00:25:49.540 ⇒ 00:25:54.410 Casie Aviles: These ones I will… yeah, I still need to work on these ones and clear this out.
232 00:25:56.610 ⇒ 00:26:05.149 Awaish Kumar: Okay, so did you have a talk with, like, Sam on how we are going to Support the migration?
233 00:26:06.350 ⇒ 00:26:11.660 Casie Aviles: No, not yet. I was hoping that we could also talk about that after…
234 00:26:11.890 ⇒ 00:26:15.609 Casie Aviles: After my call with Tim, who’s the…
235 00:26:16.840 ⇒ 00:26:21.440 Awaish Kumar: Yeah, maybe you can also look at operating now, like, we have…
236 00:26:22.150 ⇒ 00:26:30.360 Awaish Kumar: UTAM has increased, like, your allocation for this project, so you can, like, spend more time on ABC.
237 00:26:31.240 ⇒ 00:26:32.360 Casie Aviles: Okay, sure.
238 00:26:35.850 ⇒ 00:26:37.530 Awaish Kumar: Sam is not.
239 00:26:38.180 ⇒ 00:26:39.110 Awaish Kumar: You?
240 00:26:41.710 ⇒ 00:26:44.959 Casie Aviles: Okay, I’ll talk to Sam later. I’ll ping him.
241 00:26:45.530 ⇒ 00:26:51.740 Awaish Kumar: You can ping him offline, and maybe also then share the updates in the Slack, whatever you decided, or…
242 00:26:52.300 ⇒ 00:26:54.689 Awaish Kumar: Whatever the next steps are, like…
243 00:26:54.950 ⇒ 00:26:57.950 Awaish Kumar: Like, conducting a meeting, or whatever.
244 00:26:58.740 ⇒ 00:26:59.590 Casie Aviles: Sure, sure.
245 00:27:03.510 ⇒ 00:27:07.669 Awaish Kumar: Then on OpenStems, I don’t think we got anything.
246 00:27:09.900 ⇒ 00:27:13.670 Awaish Kumar: For README, it’s mostly the… only the analysis.
247 00:27:14.270 ⇒ 00:27:22.990 Awaish Kumar: So, we can just move on to Element. So, I’ve been working on that, client, yesterday.
248 00:27:23.110 ⇒ 00:27:24.490 Awaish Kumar: The fun food is known.
249 00:27:24.640 ⇒ 00:27:35.020 Awaish Kumar: So, mostly, we are just working to generate Create some documentation on our… ETL assessment, or warehousing Assessment.
250 00:27:36.710 ⇒ 00:27:38.760 Awaish Kumar: Tailored to the client’s needs.
251 00:27:39.000 ⇒ 00:27:47.749 Awaish Kumar: I’m trying to create some documentation, and maybe we will be working more on documentation for this client, creating some executive-level docs.
252 00:27:49.430 ⇒ 00:27:50.420 Awaish Kumar: with them.
253 00:27:50.620 ⇒ 00:27:52.609 Awaish Kumar: For a few more weeks.
254 00:27:52.960 ⇒ 00:27:56.379 Awaish Kumar: Before starting the implementation.
255 00:27:59.700 ⇒ 00:28:12.230 Awaish Kumar: Yeah, that’s roughly it, like, on Element, and for CTA, Ashwini, like… What are the updates?
256 00:28:12.620 ⇒ 00:28:18.100 Ashwini Sharma: So for CTA, yesterday, I had a discussion with, Catherine?
257 00:28:18.360 ⇒ 00:28:23.989 Ashwini Sharma: She said she’ll get back to me, so I’m just waiting for that. Kind of blocked on.
258 00:28:24.530 ⇒ 00:28:30.160 Ashwini Sharma: Creating that… Automating that report for active members.
259 00:28:30.820 ⇒ 00:28:33.180 Awaish Kumar: So this exploration is still ongoing.
260 00:28:33.400 ⇒ 00:28:36.759 Ashwini Sharma: Exploration, yeah, that will ongoing for…
261 00:28:37.130 ⇒ 00:28:41.440 Ashwini Sharma: some more time, right? And we were also trying to, you know,
262 00:28:43.090 ⇒ 00:28:49.960 Ashwini Sharma: You know, confirm which tools you would be using for data acquisition, data ingestion.
263 00:28:50.140 ⇒ 00:28:54.919 Ashwini Sharma: We were initially suggesting Fibetran, and she’s saying that we should utilize
264 00:28:55.090 ⇒ 00:28:58.450 Ashwini Sharma: things that are there in AWS by default.
265 00:28:58.890 ⇒ 00:29:04.979 Ashwini Sharma: So, nothing is fixed yet. I’ll, you know, get in touch with Utam and then see what we can do.
266 00:29:05.590 ⇒ 00:29:10.720 Awaish Kumar: No, no, like, my point is, like, did we recommend any tools? And…
267 00:29:10.720 ⇒ 00:29:16.859 Ashwini Sharma: We said that, for the initial historical think, and to…
268 00:29:17.230 ⇒ 00:29:20.079 Ashwini Sharma: You know, calculate the volume.
269 00:29:20.400 ⇒ 00:29:20.790 Awaish Kumar: Weekend.
270 00:29:20.790 ⇒ 00:29:30.589 Ashwini Sharma: use Fivetran, and then figure out how much volume of data is there, and then we can decide, based on the volume, whether we can go with polyatomic, or whether we have to
271 00:29:30.970 ⇒ 00:29:35.059 Ashwini Sharma: write our own script… I don’t know, like.
272 00:29:35.360 ⇒ 00:29:35.910 Awaish Kumar: Okay.
273 00:29:35.910 ⇒ 00:29:39.899 Ashwini Sharma: Yeah, I mean, it’s not very clear on what we’ll be doing.
274 00:29:39.900 ⇒ 00:29:42.600 Awaish Kumar: Is Amazon and Walmart are the sources?
275 00:29:43.570 ⇒ 00:29:47.700 Ashwini Sharma: Amazon and Walmart… No.
276 00:29:49.260 ⇒ 00:29:49.960 Awaish Kumar: Yeah. Shopping?
277 00:29:49.960 ⇒ 00:29:53.630 Ashwini Sharma: Shopify? Yes, there is some Shopify… store.
278 00:29:54.070 ⇒ 00:29:56.270 Ashwini Sharma: Where they sell some digital assets.
279 00:29:56.510 ⇒ 00:29:59.909 Ashwini Sharma: Other than that, there is a Salesforce CRM.
280 00:30:00.190 ⇒ 00:30:05.310 Ashwini Sharma: sorry, Salesforce Marketing Cloud, which is one of the most important data sources.
281 00:30:06.700 ⇒ 00:30:09.689 Awaish Kumar: Is there any connector for that in Polyatomic?
282 00:30:10.560 ⇒ 00:30:13.350 Ashwini Sharma: Yeah, Polyatomic has a Salesforce Marketing Cloud connector.
283 00:30:13.350 ⇒ 00:30:13.930 Awaish Kumar: Okay.
284 00:30:14.970 ⇒ 00:30:23.610 Awaish Kumar: is, like, it seems like for Atomic will be cheaper, Since the pricing for, like.
285 00:30:24.290 ⇒ 00:30:29.119 Awaish Kumar: Potomic price is, like, around 500 for 6 million rows in a month.
286 00:30:29.550 ⇒ 00:30:31.050 Ashwini Sharma: How much? 6 connectors.
287 00:30:31.800 ⇒ 00:30:34.200 Awaish Kumar: No, no, 6 million rows.
288 00:30:34.600 ⇒ 00:30:36.810 Awaish Kumar: for $500.
289 00:30:36.810 ⇒ 00:30:37.620 Ashwini Sharma: Okay.
290 00:30:38.030 ⇒ 00:30:43.100 Awaish Kumar: Yeah, and it doesn’t matter how many connector you use. It just,
291 00:30:43.320 ⇒ 00:30:48.160 Awaish Kumar: charges you based on the… the MER, like, monthly active rows.
292 00:30:48.160 ⇒ 00:30:49.390 Ashwini Sharma: Okay, okay, yep.
293 00:30:49.860 ⇒ 00:30:58.010 Awaish Kumar: So, and it has the connector for Shopify, and it also has the connector for Stripe, so I think, most… Polyatomic will have
294 00:30:58.220 ⇒ 00:31:03.770 Awaish Kumar: Almost all the… collectors they need, and then we can maybe use Who’s that?
295 00:31:04.510 ⇒ 00:31:09.779 Ashwini Sharma: Yeah, but a lot of connectors are not there in polyatomic, right? I had prepared that P0 sheet.
296 00:31:09.920 ⇒ 00:31:14.230 Ashwini Sharma: There are more things with Fivetran.
297 00:31:14.360 ⇒ 00:31:19.129 Ashwini Sharma: And lesser with polyatomic, and a lot of data sources didn’t have any.
298 00:31:19.450 ⇒ 00:31:20.599 Ashwini Sharma: Yeah, but we can…
299 00:31:20.730 ⇒ 00:31:24.829 Awaish Kumar: We can suggest a hybrid approach, like, a mix of tools.
300 00:31:25.850 ⇒ 00:31:31.069 Awaish Kumar: To have the coverage and the cost of efficiency.
301 00:31:31.750 ⇒ 00:31:36.919 Ashwini Sharma: Yeah, I’ll drop a message to Catherine, and then see if she has finalized on anything.
302 00:31:37.920 ⇒ 00:31:41.189 Awaish Kumar: Yeah, so you can suggest that, and…
303 00:31:41.870 ⇒ 00:31:50.469 Awaish Kumar: Yeah, maybe you can also let us know in internal channel, like, whatever you have proposed and what the responses are.
304 00:31:50.470 ⇒ 00:31:51.430 Ashwini Sharma: Yeah, sure.
305 00:31:51.430 ⇒ 00:31:55.120 Awaish Kumar: And maybe we can also give our inputs.
306 00:31:55.560 ⇒ 00:32:00.800 Awaish Kumar: like, Demilade and Pai have been working on these things for some time.
307 00:32:01.870 ⇒ 00:32:02.980 Awaish Kumar: Yeah.
308 00:32:04.390 ⇒ 00:32:11.470 Awaish Kumar: So, yeah. So, like, these are still in progress, and that’s the main priority right now, right?
309 00:32:11.470 ⇒ 00:32:12.300 Ashwini Sharma: Alright, yeah.
310 00:32:15.400 ⇒ 00:32:18.980 Awaish Kumar: Yeah, we don’t have anything, for Hydra.
311 00:32:19.280 ⇒ 00:32:22.300 Awaish Kumar: Soon, but we are expecting 10 hours
312 00:32:22.470 ⇒ 00:32:26.990 Awaish Kumar: Per week for them, and yeah, but so far…
313 00:32:27.880 ⇒ 00:32:38.360 Awaish Kumar: No updates on that. And we also don’t have, I think, Sam or… Surf here, so yeah, hi.
314 00:32:39.420 ⇒ 00:32:43.469 Awaish Kumar: We can, like… discuss Lilo and Timo.
315 00:32:43.590 ⇒ 00:32:48.900 Awaish Kumar: It’s like… So, apart from that, Kev, do you have any updates on internal things?
316 00:32:50.480 ⇒ 00:32:57.850 Gabriel Lam: For internal, we are still gonna work on the migration, basically to…
317 00:32:58.370 ⇒ 00:33:14.649 Gabriel Lam: handle how we ingest new clients, so that migration from the old NA-to-end client hubs to Mastra is still happening this week. On the side, Utam and I are working on a contextual AI partnership, so that’s what I’ll be working on myself.
318 00:33:15.690 ⇒ 00:33:16.230 Awaish Kumar: Okay.
319 00:33:16.230 ⇒ 00:33:17.560 Gabriel Lam: That’s about it, yeah.
320 00:33:21.580 ⇒ 00:33:24.569 Awaish Kumar: Okay, that’s all, from my side.
321 00:33:27.790 ⇒ 00:33:33.279 Awaish Kumar: So, yeah, does anyone have anything to discuss, or…
322 00:33:34.220 ⇒ 00:33:37.879 Awaish Kumar: Who wants to discuss any blockers or things?
323 00:33:38.380 ⇒ 00:33:39.559 Awaish Kumar: Yeah, I’ve been working on.
324 00:33:39.560 ⇒ 00:33:49.409 Uttam Kumaran: I just wanted to, ask Demolade if you’re… feel… if you’re good on default, like, you’re able to onboard and stuff like that. Feel free to say hi in the
325 00:33:49.650 ⇒ 00:33:55.399 Uttam Kumaran: in the channel, if so, but I feel like if you end up chatting with Mustafa, then you just wanted to bring you in.
326 00:33:56.430 ⇒ 00:34:07.999 Demilade Agboola: Yeah, so I actually sent a message to Victor in the channel today, asking for some clarification on some points. But yeah, I’m on board, I mean, the channels,
327 00:34:08.250 ⇒ 00:34:11.269 Demilade Agboola: And I have already started looking at the data.
328 00:34:11.760 ⇒ 00:34:24.079 Demilade Agboola: I understand that, you know, we’re supposed to get the numbers to them, we’re supposed to get the numbers to them last week, so I’m just trying to ensure that we’re able to get some form of data across today, tomorrow.
329 00:34:24.300 ⇒ 00:34:35.500 Demilade Agboola: And then, in parallel, I’m also trying to set up the dbt so that, like, the whole orchestration process and the continuous data can come in,
330 00:34:35.500 ⇒ 00:34:36.110 Uttam Kumaran: Okay.
331 00:34:36.629 ⇒ 00:34:41.079 Demilade Agboola: But, you know, it’s sort of like a one-time send, I’m trying to figure that out today.
332 00:34:42.770 ⇒ 00:34:47.920 Uttam Kumaran: Yeah, one thing you can also take a look at is, like, how much we can do in…
333 00:34:48.170 ⇒ 00:34:49.960 Uttam Kumaran: Omni itself.
334 00:34:50.230 ⇒ 00:34:53.599 Uttam Kumaran: Because Omni has, like, a pretty tight coupling with dbt.
335 00:34:53.909 ⇒ 00:34:57.219 Uttam Kumaran: Like, as you can tell, there’s not, like, a ton of data, so I’m wondering.
336 00:34:57.220 ⇒ 00:34:57.600 Demilade Agboola: Yeah.
337 00:34:57.600 ⇒ 00:35:00.909 Uttam Kumaran: How, you know, this was the first client where we had that set up.
338 00:35:01.050 ⇒ 00:35:06.869 Uttam Kumaran: So, I don’t know, interesting for you to explore Omni and, like, what their system is with dbt.
339 00:35:08.040 ⇒ 00:35:09.349 Demilade Agboola: Okay, sounds good.
340 00:35:20.220 ⇒ 00:35:21.060 Awaish Kumar: Okay.
341 00:35:23.970 ⇒ 00:35:25.669 Uttam Kumaran: Okay, cool, that’s all I have.
342 00:35:27.400 ⇒ 00:35:29.299 Awaish Kumar: Okay, thank you, everyone.
343 00:35:30.730 ⇒ 00:35:34.479 Awaish Kumar: See you. Thank you. And Slack. Thank you. Bye.
344 00:35:34.480 ⇒ 00:35:35.920 Demilade Agboola: Chew. Bye.