Meeting Title: Data Service Standup Date: 2026-03-06 Meeting participants: Awaish Kumar, Brylle Girang, Mustafa Raja, Demilade Agboola, Ashwini Sharma


WEBVTT

1 00:01:24.500 00:01:25.650 Brylle Girang: Hi, Amish!

2 00:01:30.220 00:01:31.760 Awaish Kumar: Hi, Bill, how are you?

3 00:01:33.020 00:01:34.820 Brylle Girang: Doing great! Happy Friday!

4 00:01:35.120 00:01:36.529 Awaish Kumar: Yeah, I prefer that.

5 00:02:23.250 00:02:24.939 Brylle Girang: Any plans for the weekend?

6 00:02:27.490 00:02:28.260 Awaish Kumar: Nope.

7 00:02:28.450 00:02:34.089 Awaish Kumar: I got here, I don’t think… I’m going to go anywhere.

8 00:02:34.440 00:02:35.010 Mustafa Raja: Hey, honey.

9 00:02:35.010 00:02:35.600 Brylle Girang: Okay.

10 00:02:37.350 00:02:39.149 Brylle Girang: Hi, Mustafa. Hi, Demi.

11 00:02:43.250 00:02:44.010 Mustafa Raja: A.

12 00:02:45.840 00:02:48.020 Awaish Kumar: Okay, how’s it going?

13 00:02:48.560 00:02:49.940 Mustafa Raja: Good.

14 00:02:50.500 00:02:51.800 Awaish Kumar: Yeah, I’m good.

15 00:02:53.190 00:02:55.130 Awaish Kumar: Pursuit for a sec.

16 00:02:55.710 00:02:57.350 Awaish Kumar: Kashuna’s joining.

17 00:03:04.440 00:03:08.319 Awaish Kumar: Okay, let’s… Start the standoff.

18 00:03:12.260 00:03:16.880 Awaish Kumar: Let me share my screen, and… It can start.

19 00:03:17.520 00:03:20.789 Awaish Kumar: Okay, starting with Magic Spoons,

20 00:03:21.870 00:03:25.119 Awaish Kumar: Demi, can you, like, update us?

21 00:03:26.860 00:03:32.929 Demilade Agboola: So, in terms of Magic Spoon, it appears like we’ve been able to make some progress.

22 00:03:33.320 00:03:34.790 Demilade Agboola: This week.

23 00:03:34.910 00:03:37.010 Demilade Agboola: However,

24 00:03:37.990 00:03:47.500 Demilade Agboola: based on Ashwini’s hours, Ashwini has just about 15 hours, so I’m gonna have conversations with Otam about just… because I mentioned it to Otam, I just said, like, we need to…

25 00:03:48.240 00:03:53.750 Demilade Agboola: see if this is, like, a one-week VIN, or if it’s a pattern. If it’s a pattern, we’ll definitely push for them to…

26 00:03:54.180 00:04:07.830 Demilade Agboola: upgrade the contract. But yeah, other than that, I think we’ve been able to make progress. I will clear up some of the data errors that they’ve had, this week, and I think we can… it’ll be a good week for that.

27 00:04:09.990 00:04:10.750 Awaish Kumar: Okay.

28 00:04:10.960 00:04:17.199 Awaish Kumar: So… Yes, Sashuni, like, what is the difference between these two tickets?

29 00:04:18.110 00:04:24.990 Ashwini Sharma: It’s the same digit, man. Delete one of them.

30 00:04:31.270 00:04:34.490 Awaish Kumar: Okay, so how long, like…

31 00:04:34.490 00:04:38.919 Ashwini Sharma: The scope for 39 increased, because they increased the number of fields to extract.

32 00:04:39.780 00:04:55.450 Ashwini Sharma: As well as, the timeframes, for which we need to do the extraction. So earlier, it was only the current time frame, and then going back in the history, but now it is, like, for every time frame that exists in the system, we are doing an extraction and going back up to one year.

33 00:04:55.660 00:05:01.919 Ashwini Sharma: For the QA data, right? So, right now, the extraction is in progress,

34 00:05:02.900 00:05:10.830 Ashwini Sharma: 1 week, 4 week, and 12 week are done. It’s loaded as well in the, what do you call it? In the, in the…

35 00:05:12.020 00:05:12.780 Awaish Kumar: Yeah, my…

36 00:05:12.780 00:05:13.910 Ashwini Sharma: In the warehouse, yeah.

37 00:05:14.830 00:05:20.960 Awaish Kumar: Yeah, I just would like to make a point here, that if you need any support, or

38 00:05:21.130 00:05:29.070 Awaish Kumar: Anything here to just close this out? You feel free to schedule a meeting with anyone you think will be able to help you.

39 00:05:29.410 00:05:34.420 Awaish Kumar: Yeah, we should, like, at least we should be able to run these,

40 00:05:34.550 00:05:36.859 Awaish Kumar: a sink? Like, these are, like, the…

41 00:05:37.250 00:05:40.769 Awaish Kumar: Once you make the changes, we should be able to run these async, right?

42 00:05:41.010 00:05:42.730 Awaish Kumar: Through the Prefect, so…

43 00:05:42.920 00:05:50.840 Awaish Kumar: Maybe using some kind of configuration or something, so that you don’t have to be involved in all these things, like managing.

44 00:05:50.840 00:06:02.459 Ashwini Sharma: Yeah, so yesterday I tried doing that only, right? Like, triggering a run and let it run, but since the data volume was so huge that it used to fail after several hours, right?

45 00:06:02.500 00:06:13.069 Ashwini Sharma: And then that, I was not able to load any data yesterday, right? Even though, like, I was trying for the whole day. So today, I broke it down into smaller chunks, and then I’m loading the data.

46 00:06:13.130 00:06:17.890 Ashwini Sharma: And that’s why, like, I’m giving periodic updates on what has been done.

47 00:06:18.010 00:06:25.699 Ashwini Sharma: Yeah, so basically, this has to be scheduled at a specific interval of, during the day.

48 00:06:25.950 00:06:28.130 Ashwini Sharma: somewhere during ISTD time.

49 00:06:28.340 00:06:32.560 Ashwini Sharma: Where the warehouse is also low, and the spin CPI is also available.

50 00:06:34.270 00:06:41.559 Ashwini Sharma: So, let’s talk in detail if you want to discuss with me. Otherwise, yeah, we can move on. Yeah, let’s move on.

51 00:06:44.970 00:06:46.940 Awaish Kumar: Moving on to CTA.

52 00:06:47.540 00:06:51.570 Awaish Kumar: We… yeah, here, I just want to close this pre-order report, like…

53 00:06:52.650 00:06:55.919 Awaish Kumar: I think, we are doing okay here.

54 00:06:56.090 00:07:04.200 Awaish Kumar: But I’m also concerned that we are… we are not able to close this report, but I think we have enough updates for the client.

55 00:07:04.200 00:07:11.340 Ashwini Sharma: Yeah, I’ll create queries now. I’m going to sit for a couple of hours, and then I’ll write queries and raise a PR for these things.

56 00:07:13.270 00:07:19.310 Awaish Kumar: Okay, but yeah, just like, in today’s meeting, we just have to… Or make, like, make other…

57 00:07:19.730 00:07:24.930 Awaish Kumar: We have to talk about other things so that we can cover, one-hour session.

58 00:07:25.100 00:07:28.290 Awaish Kumar: But otherwise, we are good here.

59 00:07:28.570 00:07:36.970 Awaish Kumar: And then, for the next weeks, like, priorities are closing out identity stitching, closing out this report, And…

60 00:07:37.710 00:07:41.229 Awaish Kumar: And start on, like, the cortex, snowflake Cortex.

61 00:07:41.630 00:07:42.260 Ashwini Sharma: Okay.

62 00:07:46.540 00:07:51.410 Awaish Kumar: Then moving on to Element, like, there’s, yeah, obviously.

63 00:07:52.370 00:07:56.739 Awaish Kumar: We don’t have any, active modeling work here right now.

64 00:07:56.950 00:07:59.960 Awaish Kumar: The client is also on, kind of, leave.

65 00:08:00.840 00:08:03.159 Awaish Kumar: So we are, like,

66 00:08:03.920 00:08:11.919 Awaish Kumar: slow progressing here for this week, and I did a little bit of eco modeling, but that’s it. And, yeah, we are going to…

67 00:08:12.030 00:08:15.679 Awaish Kumar: maybe go Like, in full…

68 00:08:16.400 00:08:23.400 Awaish Kumar: development made more, like, the next week, but for this week, I think it’s all good here.

69 00:08:25.140 00:08:29.899 Awaish Kumar: And hopefully we are going to get unblocked on Amazon also, by next week.

70 00:08:33.320 00:08:37.650 Awaish Kumar: And then, moving on to… default.

71 00:08:38.789 00:08:43.740 Awaish Kumar: Yeah, it’s… How we are doing with the default terminology?

72 00:08:47.760 00:08:49.909 Demilade Agboola: Show some of the work we’re…

73 00:08:52.910 00:08:53.670 Awaish Kumar: Sorry?

74 00:08:57.840 00:08:58.160 Demilade Agboola: Sir.

75 00:08:58.160 00:08:58.670 Mustafa Raja: Stop talking with me.

76 00:08:58.670 00:09:08.740 Demilade Agboola: I’m muting myself, sorry. I think we’ve been able to show some of the work we’ve been doing behind the scenes, because they were getting a bit uncomfortable that we were not yet showing anything yet.

77 00:09:09.000 00:09:13.240 Demilade Agboola: So they seem excited about some of the work we’ve been able to do so far.

78 00:09:13.930 00:09:24.440 Demilade Agboola: But in light, so that we can be on the same page on, like, expectations, we’ve had to rework on… rework the Gantt chart, as well as rework on some of the other…

79 00:09:24.590 00:09:29.340 Demilade Agboola: Platform documentation so that they can have more visibility into what’s going on.

80 00:09:29.440 00:09:33.720 Demilade Agboola: And have, like, clear expectations on when to…

81 00:09:33.970 00:09:40.829 Demilade Agboola: expect some of the outcomes from us. But yeah, that’s… that’s what we had to do over the last, like, 24 hours.

82 00:09:41.960 00:09:44.140 Brylle Girang: Demi, so I know that we…

83 00:09:44.550 00:09:50.740 Brylle Girang: We shared with default that we will also be completing the second dashboard, Customer Reporting and Enablement.

84 00:09:51.170 00:09:54.139 Brylle Girang: Or do you think that we can still pull it off this week?

85 00:09:55.120 00:10:10.310 Demilade Agboola: Yeah, I think, like, the numbers are there, and it’s just basically trying to show them the numbers. I don’t think we can do anything beyond just, like, hey, this is the dashboard, this is how it looks like, but in terms of, like, just showing something, yes, we can show them something.

86 00:10:10.820 00:10:12.000 Brylle Girang: Okay, perfect.

87 00:10:13.500 00:10:14.389 Brylle Girang: Thank you.

88 00:10:14.680 00:10:16.640 Awaish Kumar: Okay, Liz, what’s fault.

89 00:10:17.810 00:10:31.779 Mustafa Raja: Yeah, so, I had, tickets for, for dashboard metrics, and then, GitHub Actions for DBD. Both of them are done, and now, moving forward, I’ll be working on this

90 00:10:32.230 00:10:35.240 Mustafa Raja: Setting up Slack notifications for DVD failure.

91 00:10:37.470 00:10:38.330 Awaish Kumar: Okay.

92 00:10:40.830 00:10:42.620 Awaish Kumar: So, are you, like…

93 00:10:43.120 00:10:48.130 Awaish Kumar: Have you, like, prepared the plan for the next week? Are you good with Gantt chart?

94 00:10:48.590 00:10:57.839 Mustafa Raja: Yes, I have created projects per stream, in default, so we’ll be using them moving forward.

95 00:10:58.000 00:10:59.309 Mustafa Raja: And next week.

96 00:11:00.900 00:11:01.660 Awaish Kumar: Okay.

97 00:11:02.780 00:11:03.360 Mustafa Raja: Yeah.

98 00:11:04.840 00:11:07.349 Awaish Kumar: Okay, and then moving on, finally, to…

99 00:11:07.350 00:11:16.669 Brylle Girang: Before we move on, just wanted to clarify, Mustafa, Demi, were you able to, like, sync on finalizing the data platform? Okay.

100 00:11:17.030 00:11:21.879 Mustafa Raja: Yeah, we were able to sync. You can take a look at that. Let me share a link with you.

101 00:11:22.300 00:11:24.669 Brylle Girang: Okay, I’m looking at it now, thank you.

102 00:11:24.670 00:11:25.400 Mustafa Raja: Okay.

103 00:11:25.620 00:11:28.530 Brylle Girang: Do you want to provide an update to Otam?

104 00:11:29.020 00:11:30.060 Mustafa Raja: Yeah.

105 00:11:30.060 00:11:30.700 Brylle Girang: Okay.

106 00:11:30.700 00:11:36.410 Mustafa Raja: I just need to, fill up the frequency, or double-check the frequency and duration.

107 00:11:36.560 00:11:39.180 Mustafa Raja: I’ll then, share, share this.

108 00:11:40.050 00:11:41.390 Brylle Girang: Okay, thank you.

109 00:11:43.980 00:11:46.180 Awaish Kumar: Okay, moving on to Eden,

110 00:11:47.550 00:11:53.129 Awaish Kumar: I… yeah, I saw the PR, is it… Is it done completely?

111 00:11:53.850 00:11:54.890 Awaish Kumar: Hi, Shanik.

112 00:11:54.890 00:11:59.769 Ashwini Sharma: Yeah, yeah, the PR… this will, like, send the data to our friends.

113 00:12:00.070 00:12:04.089 Ashwini Sharma: In the… in the format that… that we were always sending it out.

114 00:12:04.270 00:12:07.840 Ashwini Sharma: But the change is basically how we are calculating the spend amount.

115 00:12:08.030 00:12:10.830 Ashwini Sharma: Okay. Yeah, so that will…

116 00:12:11.040 00:12:24.499 Ashwini Sharma: On the 1st of every month, it will include the retainer amount plus the orders that were created on that particular day, and then going forward, for every new day, whatever orders are created, it will sum up the commission amount for that, and then

117 00:12:24.940 00:12:31.299 Ashwini Sharma: put it into the push table, and then for the… and then send it to, basically, North Beam.

118 00:12:33.300 00:12:37.730 Awaish Kumar: Then there are some tickets for Omni migration.

119 00:12:37.830 00:12:43.390 Awaish Kumar: So I closed our… closed two today, or yesterday, and there are still two pending on my…

120 00:12:43.790 00:12:47.520 Awaish Kumar: A plate, which I’m going to work today, and close it out.

121 00:12:47.650 00:12:51.740 Awaish Kumar: There are a few on Utam’s plate as well.

122 00:12:52.140 00:12:56.650 Awaish Kumar: So… let’s see, like, Musa, if you have any time…

123 00:12:57.100 00:12:59.939 Awaish Kumar: Let’s try to close these out, and also…

124 00:12:59.940 00:13:04.880 Mustafa Raja: Yeah, the issue with these ones is, I think these need dbt support.

125 00:13:05.390 00:13:10.190 Awaish Kumar: Let’s plan a working session between us.

126 00:13:10.190 00:13:11.210 Mustafa Raja: Okay, okay, yeah.

127 00:13:11.210 00:13:18.309 Awaish Kumar: for an hour, and we are just going to work on a call. So I’m going to close dbt things, and then we just… like, you can click on…

128 00:13:19.040 00:13:21.949 Awaish Kumar: Omnistop, and we just, like, moves these out.

129 00:13:22.520 00:13:23.210 Mustafa Raja: Okay.

130 00:13:23.540 00:13:24.220 Awaish Kumar: Okay.

131 00:13:25.740 00:13:32.910 Awaish Kumar: Yeah, I think that’s it. That’s the end of the stand-up. Is there anything else you want to discuss?

132 00:13:34.340 00:13:47.909 Brylle Girang: Yeah, so Awash, I was talking with Otam the other day, and I want to get your thoughts here. We think that stand-ups during Mondays are not really required and efficient, because we’re… that’s the start of the week.

133 00:13:48.170 00:13:57.240 Brylle Girang: We were thinking about converting the Monday stand-ups from a general service stand-ups to client-focused stand-ups instead.

134 00:13:57.380 00:14:08.359 Brylle Girang: So, every Monday, instead of data service, we’re going to be meeting with, regarding CTA, Element, etc. What do you think? I want to hear everyone’s thoughts there.

135 00:14:11.160 00:14:13.999 Awaish Kumar: Yeah, I think that’s a good idea, like,

136 00:14:14.420 00:14:19.510 Awaish Kumar: like, we don’t… like, I don’t do… I don’t think if we need to have, like.

137 00:14:20.450 00:14:24.240 Awaish Kumar: A single meeting for each client, but it is a good idea that

138 00:14:24.340 00:14:35.860 Awaish Kumar: instead of a standard, we can have those as planning things. So for each week, we’re going to… like, on one day, we can review with EPs that what’s week look like, what are the tickets, how the Gantt chart looks like.

139 00:14:35.960 00:14:37.239 Awaish Kumar: for each client.

140 00:14:37.640 00:14:38.510 Awaish Kumar: Yeah.

141 00:14:38.510 00:14:39.060 Brylle Girang: Okay.

142 00:14:39.640 00:14:45.949 Brylle Girang: I think we’re going to be piloting with one meeting per client, at least for next week, and then let’s see…

143 00:14:46.190 00:14:55.600 Brylle Girang: If it’s not going to work, and then we convert to, like, a structured or a collated meeting instead, but that’s going to be the goal for starting next week.

144 00:14:55.850 00:15:05.940 Brylle Girang: Stand-ups will be held from Tuesday to Friday, and then we’re going to focus on individual clients every Monday, and that’s where we’ll look at the Gantt charts.

145 00:15:06.720 00:15:07.510 Demilade Agboola: How long were that?

146 00:15:07.510 00:15:08.090 Brylle Girang: unit.

147 00:15:08.770 00:15:09.610 Brylle Girang: Sorry?

148 00:15:09.820 00:15:11.629 Demilade Agboola: How long would that be for each client?

149 00:15:12.480 00:15:18.140 Brylle Girang: I scheduled just 30 minutes, For each client, at least for the first run.

150 00:15:18.620 00:15:23.420 Demilade Agboola: Yeah, but if you’re on 3 clients, that’s 1 hour, 30 minutes on client meetings.

151 00:15:27.830 00:15:28.400 Brylle Girang: Hmm.

152 00:15:29.510 00:15:35.230 Brylle Girang: Like, is that too much for, like, for Monday? I want to better understand.

153 00:15:35.670 00:15:37.619 Awaish Kumar: Yeah, so that’s what I’d like to see…

154 00:15:37.780 00:15:41.840 Awaish Kumar: If somebody is involved in more than one plan, like, 3, 4…

155 00:15:41.950 00:15:45.999 Awaish Kumar: And then he used to spend, like, 2 hours just in meetings, that’s… that’s the point.

156 00:15:46.740 00:15:52.779 Brylle Girang: Okay. Well, do you think that it’s going to be better if we, like, schedule a one-hour call?

157 00:15:52.880 00:15:56.960 Brylle Girang: with each CSO or EP pair instead?

158 00:15:57.580 00:16:01.099 Brylle Girang: Or a 30-minute call with each CSO EP pair.

159 00:16:04.280 00:16:08.340 Brylle Girang: So, for example, one call with Demi and Mustafa, just for…

160 00:16:08.340 00:16:09.600 Awaish Kumar: Oh, okay.

161 00:16:10.340 00:16:15.379 Awaish Kumar: Yeah, my idea is that, like, CSO EP should pair, and

162 00:16:15.480 00:16:17.640 Awaish Kumar: come up with the Gantt chart.

163 00:16:17.970 00:16:21.219 Awaish Kumar: Before the meeting, and in the meeting, we just review it.

164 00:16:21.450 00:16:27.900 Awaish Kumar: how the week look like. So, the meeting is to go over each client and just see

165 00:16:28.480 00:16:31.959 Awaish Kumar: Gantt chart and linear, and the plan for the NIC.

166 00:16:32.090 00:16:34.090 Awaish Kumar: Like, it should be just 5-minute update.

167 00:16:34.190 00:16:38.840 Awaish Kumar: And the work, all the, like, the hard work happens before that meeting.

168 00:16:40.410 00:16:42.020 Awaish Kumar: Okay. Yep.

169 00:16:43.230 00:16:51.319 Brylle Girang: Okay, gotcha. Let me, speak with Utam about this, because our previous plan was to, like, really meet

170 00:16:51.670 00:16:59.880 Brylle Girang: 30 minutes each week for each client, but I hear you. I’m just going to, like, build a better plan around this. Thanks, everyone.

171 00:17:00.750 00:17:01.730 Awaish Kumar: Thank you.

172 00:17:02.040 00:17:09.049 Awaish Kumar: Yeah, yeah, feel free to get back to work. Ashwini, can you just stay for… 5 minutes?

173 00:17:11.630 00:17:12.240 Ashwini Sharma: Russia.

174 00:17:12.859 00:17:14.379 Awaish Kumar: Okay, thank you, everyone.

175 00:17:22.769 00:17:29.159 Awaish Kumar: Yeah, what I want to discuss about CTA is, like, if you have seen my PR,

176 00:17:29.389 00:17:33.759 Awaish Kumar: Yeah. Like, that’s… like, I added the curious, the way we discussed that we…

177 00:17:34.210 00:17:37.290 Ashwini Sharma: Oh, yeah, yeah. I saw your PR, Sam.

178 00:17:37.290 00:17:53.160 Awaish Kumar: So, what I’m saying is, I added all the 17 queries, so, like, the queries I added might not, like, have all the, like, exactly matching data, right? It will have some ups and downs. We are just going to queue, like, this will be a QA document, which we are going to just share.

179 00:17:53.300 00:17:56.609 Awaish Kumar: This is the query, this is the result, and…

180 00:17:56.790 00:18:05.900 Awaish Kumar: Then we can see where are the differences, big differences, and start to add them as linear tickets, and we can work with Kyle to fix those.

181 00:18:06.170 00:18:12.649 Ashwini Sharma: Sure, well, yeah, I’ll create similar queries like you have done, right, and add it to this,

182 00:18:13.160 00:18:18.609 Ashwini Sharma: to a new PR, not on top of your PR, but on the same parallel line, yeah.

183 00:18:18.610 00:18:20.099 Awaish Kumar: Out of that, yeah.

184 00:18:20.350 00:18:25.770 Ashwini Sharma: Yeah, I’m working on it right now, as Magic Spoon is running right now.

185 00:18:26.080 00:18:28.730 Ashwini Sharma: Yeah.

186 00:18:28.730 00:18:34.849 Awaish Kumar: What else? For CTA, I think we have two things to discuss. One is audit report, where we are just going to

187 00:18:35.220 00:18:40.619 Awaish Kumar: show the document, and show the queries, and, like, there’s a lot of queries, I don’t know how they wanna…

188 00:18:41.200 00:18:46.510 Awaish Kumar: I don’t… like, the… I think that the best way was to use views, right?

189 00:18:47.100 00:18:48.009 Ashwini Sharma: Yeah, yeah.

190 00:18:48.620 00:18:50.639 Awaish Kumar: I don’t know. These could be…

191 00:18:50.640 00:19:04.979 Ashwini Sharma: Somehow, I… somehow, I don’t know why they would need these queries, right? Ideally, the way it should be done is, like, we should have created mods from where these reports can be derived, and they should have done a drag and drop on a dashboard.

192 00:19:05.330 00:19:13.839 Ashwini Sharma: From where, I mean, they could be analyzing that data on an Omni dashboard, or whatever dashboard tool they’re going to use it, right?

193 00:19:13.840 00:19:18.519 Awaish Kumar: Maybe, I don’t know how Streamlit is supporting it, honestly, I’ve never used that.

194 00:19:19.140 00:19:20.560 Ashwini Sharma: But that is how…

195 00:19:20.800 00:19:21.380 Awaish Kumar: We’re done.

196 00:19:21.380 00:19:21.920 Ashwini Sharma: aid?

197 00:19:23.150 00:19:31.849 Awaish Kumar: Like, the pace table we have created, for example, that has all the data, but when you have to analyze it, you just need different, like.

198 00:19:32.180 00:19:34.799 Awaish Kumar: For example, if you look at the…

199 00:19:35.230 00:19:48.870 Awaish Kumar: the table in the document, it’s just, like, you have to just work a little bit, like, this one… this also comes from… can come from that table I’ve created, but it’s just, like, you have to select product category, then…

200 00:19:49.320 00:19:51.330 Awaish Kumar: Product category…

201 00:19:51.760 00:20:00.439 Awaish Kumar: there is a… okay, you can’t see. So, the product category, for example, is a list, right? There are a lot of codes assigned to a single attendee.

202 00:20:00.610 00:20:01.170 Awaish Kumar: So…

203 00:20:01.170 00:20:01.720 Ashwini Sharma: Yep.

204 00:20:01.720 00:20:05.629 Awaish Kumar: And the only way is that you split it up, and that you join with Allah.

205 00:20:06.360 00:20:11.309 Awaish Kumar: The code mapping table, and given product names.

206 00:20:12.480 00:20:21.690 Awaish Kumar: Then count by the unique… Register ID for each product category, and… That’s how…

207 00:20:22.780 00:20:25.770 Awaish Kumar: It’s working right now, so I don’t know how…

208 00:20:27.020 00:20:31.570 Awaish Kumar: how else we are going to show the data? Like, from the model, there’s a lot of work, like, the way…

209 00:20:31.670 00:20:34.870 Awaish Kumar: These tables are being shown. Yeah.

210 00:20:35.200 00:20:38.269 Awaish Kumar: If you just give a base model.

211 00:20:38.390 00:20:42.839 Awaish Kumar: There’s a lot of work, then, to carry… to come up with all these tables.

212 00:20:45.320 00:20:45.990 Ashwini Sharma: Yep.

213 00:20:48.270 00:20:50.139 Ashwini Sharma: November, okay.

214 00:20:50.140 00:20:54.409 Awaish Kumar: She wanted that… she mentioned that we need to standardize it, because

215 00:20:54.550 00:20:58.840 Awaish Kumar: If Kyle writes one carry someday, Catherine writes,

216 00:20:59.190 00:21:05.619 Awaish Kumar: And they query for same thing, and they get different results because they forget some filters sometime.

217 00:21:05.970 00:21:12.200 Awaish Kumar: So mapping… so this is where we are standardizing those, calculations.

218 00:21:14.450 00:21:15.450 Ashwini Sharma: Okay.

219 00:21:16.850 00:21:19.330 Ashwini Sharma: Yeah, that, that makes sense.

220 00:21:23.230 00:21:28.540 Awaish Kumar: Yeah, if… I don’t know why, when I’m sharing my screen, pages, it gets paused.

221 00:21:32.710 00:21:33.510 Awaish Kumar: Okay.

222 00:21:33.920 00:21:39.909 Awaish Kumar: So basically, that’s it, so… Apart from that, I don’t know how to handle that,

223 00:21:40.880 00:21:47.620 Awaish Kumar: Because the base model just is a very simple model, and they have to do, then, a lot of,

224 00:21:48.620 00:21:54.159 Awaish Kumar: Hmm… There is, if you have looked at the PR, basically, I can open that.

225 00:21:57.310 00:21:59.860 Awaish Kumar: So, is… where is that?

226 00:22:10.170 00:22:10.850 Awaish Kumar: Oh.

227 00:22:11.670 00:22:15.069 Ashwini Sharma: No, it won’t go from here. It’ll have to go from Okta.

228 00:22:17.380 00:22:18.830 Awaish Kumar: It is an octa.

229 00:22:23.070 00:22:26.230 Ashwini Sharma: Oh, it works for you? For me, it doesn’t work.

230 00:22:28.000 00:22:29.010 Awaish Kumar: Okay, what?

231 00:22:29.790 00:22:32.199 Ashwini Sharma: And it forces me to go through Okta.

232 00:22:33.080 00:22:41.800 Awaish Kumar: Oh, Let’s go here… semantically… Quirions…

233 00:22:43.810 00:22:46.100 Awaish Kumar: Yeah, if you just look at this…

234 00:22:47.380 00:22:52.290 Awaish Kumar: attendance by region, so we’re saying, It just takes values from…

235 00:22:54.520 00:22:56.740 Awaish Kumar: from base, right? This is very simple.

236 00:22:57.150 00:22:57.940 Ashwini Sharma: Yep.

237 00:22:58.190 00:23:00.500 Awaish Kumar: All the calculations are afterward.

238 00:23:01.580 00:23:13.740 Awaish Kumar: However, the total looks like… And then the section, if it says countries USA, then Thomas Street, otherwise international.

239 00:23:14.340 00:23:18.159 Awaish Kumar: That we can add… that we can even add here, but there’s a…

240 00:23:21.740 00:23:25.059 Awaish Kumar: There’s just different calculations, count, returns…

241 00:23:25.730 00:23:33.299 Awaish Kumar: by domestic international category, and then this percentage of total entities. I don’t think all these

242 00:23:34.140 00:23:38.509 Awaish Kumar: all these, can be included in this model, like, I don’t know if…

243 00:23:39.250 00:23:45.689 Awaish Kumar: Percentage of, like, because that is, like, single attendee base table.

244 00:23:45.800 00:23:47.160 Awaish Kumar: We’ll just help.

245 00:23:47.330 00:23:54.119 Awaish Kumar: data on attendee level. So, when we do aggregation, we just have to, like.

246 00:23:55.870 00:24:03.239 Awaish Kumar: Build up, carry on top of it, so that you can do aggregations by category, by region, by…

247 00:24:03.670 00:24:08.990 Awaish Kumar: And then… Country called region, so, like…

248 00:24:09.230 00:24:11.350 Awaish Kumar: There’s a lot of things here, region…

249 00:24:14.960 00:24:18.650 Awaish Kumar: Attendance count, number of countries, how many are there.

250 00:24:18.930 00:24:21.220 Awaish Kumar: And basically, you just sign…

251 00:24:24.650 00:24:32.210 Ashwini Sharma: this thing is deleted or what? In March, we had, a folder called Reports?

252 00:24:35.090 00:24:39.299 Awaish Kumar: Oh, sorry, I was looking at… sorry, sorry, I was looking at a different repo altogether.

253 00:24:40.680 00:24:46.030 Ashwini Sharma: Models, mods… Reports.

254 00:24:48.850 00:24:53.269 Ashwini Sharma: Oh, where did I create that semantic? Did I create it in a different rep, or what?

255 00:24:54.780 00:24:57.419 Ashwini Sharma: Yeah, I created it in a different ripple, shit.

256 00:25:07.880 00:25:08.620 Awaish Kumar: Okay.

257 00:25:08.980 00:25:15.189 Ashwini Sharma: Okay, Avish, I’ll work a little bit. Let me create some queries and put it in the repo as a PR.

258 00:25:15.760 00:25:17.240 Ashwini Sharma: And then.

259 00:25:18.840 00:25:22.600 Awaish Kumar: Yeah, okay, let’s discuss after that. Thank you.

260 00:25:23.080 00:25:25.960 Ashwini Sharma: It’s in Martz, right? Mart’s, semantic layer.

261 00:25:25.960 00:25:26.699 Awaish Kumar: Yes, yes.

262 00:25:26.720 00:25:27.409 Ashwini Sharma: Ridic…

263 00:25:28.620 00:25:36.349 Ashwini Sharma: semantic layer, and then I’ll… yeah, I’ll copy it from your CPR. I created it in a different report. Okay, all right, man, thank you.