Meeting Title: Data platform planning sprint Date: 2025-06-02 Meeting participants: Awaish Kumar, Annie Yu, Luke Daque


WEBVTT

1 00:12:28.350 00:12:34.720 Awaish Kumar: Hello, so we only have 30 min for this meeting. So I would like

2 00:12:35.390 00:12:43.640 Awaish Kumar: that. We quickly finish it. And today I would like someone from team to host it.

3 00:12:46.080 00:12:50.010 Awaish Kumar: So maybe any, if you can just run this.

4 00:12:50.130 00:12:51.040 Awaish Kumar: Oh.

5 00:12:58.050 00:13:00.750 Annie Yu: Okay, let me share my screen.

6 00:13:12.070 00:13:13.319 Annie Yu: You see it.

7 00:13:15.960 00:13:16.650 Awaish Kumar: Yes.

8 00:13:19.980 00:13:26.760 Annie Yu: Okay, so should we start within review and go backwards. Is that how you usually do it?

9 00:13:27.360 00:13:28.770 Awaish Kumar: Yeah, that would be nice.

10 00:13:29.530 00:13:33.440 Annie Yu: Okay, so.

11 00:13:33.440 00:13:33.950 Awaish Kumar: Yes.

12 00:13:35.090 00:13:40.409 Annie Yu: This one for my, I think.

13 00:13:42.240 00:13:48.619 Annie Yu: Yeah, I haven’t heard back of anything but robert’s back, so I will have to

14 00:13:50.127 00:13:55.169 Annie Yu: ask him to fill out the contract, start and end for Eden docs

15 00:13:55.430 00:13:59.750 Annie Yu: and if Luke, do you have any updates on your end?

16 00:14:01.450 00:14:02.460 Luke Daque: Yeah, sure.

17 00:14:02.620 00:14:08.050 Luke Daque: So on my end. For the

18 00:14:09.550 00:14:17.339 Luke Daque: final, the one that’s in review finalizing the process for alerting via dp, 46, I updated the

19 00:14:18.060 00:14:24.090 Luke Daque: I completed that task in linear. I added my initial.

20 00:14:25.520 00:14:30.050 Luke Daque: What do you call that like? Maybe start.

21 00:14:30.050 00:14:30.600 Awaish Kumar: Good morning!

22 00:14:30.600 00:14:31.759 Luke Daque: So we can like.

23 00:14:32.380 00:14:34.830 Awaish Kumar: So can we have a notion document.

24 00:14:35.650 00:14:44.490 Luke Daque: Yeah, sure, I can create it. I can transfer this to an ocean document. But yeah, that that way. We can have like a starting point for that and maybe discuss what

25 00:14:45.149 00:14:49.940 Luke Daque: like as a team brainstorm on like, what? What would work in

26 00:14:50.110 00:14:52.240 Luke Daque: what might not work and stuff like that.

27 00:14:52.460 00:14:54.950 Luke Daque: So? Yeah, I’ll create a notion document for this one.

28 00:14:55.280 00:14:59.710 Luke Daque: Put it in there and see if it in folder.

29 00:15:01.085 00:15:11.780 Luke Daque: The other thing that I was working on was the the Meta plane Cicd. It should now already be working, at least for Eden. I was able to test it out.

30 00:15:14.060 00:15:20.140 Luke Daque: yeah. Looks like, it’s already working. But yeah, like, like, what Meta plane said, we need to be

31 00:15:21.190 00:15:27.859 Luke Daque: in the the plan to be able to use it. So they only extended our free trial until

32 00:15:28.350 00:15:33.299 Luke Daque: last week the end of last week. I’m not sure I haven’t tested it today, if it’s still working.

33 00:15:33.670 00:15:41.569 Luke Daque: But yeah, that was that was the end. So maybe we will have. I’ll have to set another schedule with them, so we can discuss about the

34 00:15:42.110 00:15:48.889 Luke Daque: the pricing model especially since we already are, we were able to test everything that we need to test. Basically.

35 00:15:48.890 00:15:55.129 Awaish Kumar: Okay, let me like, let us have a meeting with them. Like, let’s let’s

36 00:15:55.230 00:15:58.129 Awaish Kumar: schedule a meeting for this to discuss the pricing.

37 00:15:58.560 00:16:00.140 Awaish Kumar: Okay?

38 00:16:00.460 00:16:06.540 Awaish Kumar: And then, after we have everything we can then decide

39 00:16:08.050 00:16:11.589 Awaish Kumar: on, like, whether to move forward with with Meta plane or not.

40 00:16:12.240 00:16:13.710 Luke Daque: Okay. Sounds good.

41 00:16:14.160 00:16:21.069 Annie Yu: So does that mean right? Now? We don’t have the ability to use all the features.

42 00:16:24.210 00:16:33.190 Luke Daque: But if they they did revert it to the free plan, then, yeah, we might just be limited to the features that are available for the free plan.

43 00:16:34.040 00:16:37.510 Luke Daque: unless or wish. You know anything else.

44 00:16:38.540 00:16:39.889 Awaish Kumar: No, no, yeah, that’s true.

45 00:16:40.100 00:16:41.080 Luke Daque: Yeah.

46 00:16:42.220 00:16:48.250 Awaish Kumar: But but the only few features are disabled for free plan. So it’s not a big deal.

47 00:16:48.850 00:16:54.040 Awaish Kumar: But anyway, we would like to move forward with priced plan, because

48 00:16:54.590 00:17:01.579 Awaish Kumar: for the free plan, we can just use it more like, it’s just a trial period. After that we have to move to some price.

49 00:17:02.460 00:17:02.840 Luke Daque: And.

50 00:17:02.840 00:17:04.130 Awaish Kumar: I’m grateful.

51 00:17:04.839 00:17:07.910 Awaish Kumar: We were just doing Poc. And

52 00:17:09.020 00:17:11.809 Awaish Kumar: now now is the time to

53 00:17:12.630 00:17:16.480 Awaish Kumar: reflect upon what we have worked. So, Luke, if I

54 00:17:17.920 00:17:20.937 Awaish Kumar: like, let’s create a summary of

55 00:17:24.295 00:17:37.810 Awaish Kumar: like, what on meta plane? What kind of features we are like, what kind of quality monitoring we are able to do like you were mentioning that we cannot do testing like the we do in Dbt.

56 00:17:38.560 00:17:45.649 Awaish Kumar: for example, I want to check the revenue like Number One is a normally detection. That’s something different. That’s like

57 00:17:46.514 00:17:55.729 Awaish Kumar: they are constantly reading about data. And one day there is any outlier, they will detect it. That’s 1 thing, but we are more interested in

58 00:17:57.810 00:17:59.369 Awaish Kumar: if there is like

59 00:18:00.380 00:18:08.230 Awaish Kumar: there, like, if if there is an like, there are equal number of rows, there is no problem with the rows. But accidentally we

60 00:18:12.840 00:18:16.149 Awaish Kumar: like. Jane, made a change in the query

61 00:18:18.250 00:18:21.349 Awaish Kumar: which resulted in higher number of revenue.

62 00:18:21.942 00:18:24.900 Awaish Kumar: Maybe we added some multiplication or whatever.

63 00:18:25.210 00:18:34.870 Awaish Kumar: And our test says that per day revenue for Eden should not go over 1 million dollars because this

64 00:18:35.570 00:18:45.639 Awaish Kumar: so that’s a there’s a upper range because they don’t have any such revenue. Right? So if I want to keep such kind of testing, is it possible to do that or not?

65 00:18:46.700 00:18:49.779 Luke Daque: Okay, what can you say that? Again? What kind of testing.

66 00:18:49.780 00:18:54.460 Awaish Kumar: So like for the for the columns like we we know that, like some

67 00:18:55.160 00:18:59.870 Awaish Kumar: for the columns for example, good to see

68 00:19:00.470 00:19:07.620 Awaish Kumar: the countries column right? I know that Eden only works in not maybe region columns. If Eden is working only in the

69 00:19:07.770 00:19:11.749 Awaish Kumar: few provinces of region, if and if I get an entry

70 00:19:11.860 00:19:16.570 Awaish Kumar: if I get enrolled with the with the new region where

71 00:19:17.310 00:19:20.480 Awaish Kumar: Eden does not do any business right? So that’s

72 00:19:22.520 00:19:25.539 Awaish Kumar: that’s a like kind of a data quality issue, right.

73 00:19:25.810 00:19:26.520 Luke Daque: Right.

74 00:19:26.960 00:19:30.239 Awaish Kumar: So how like are we able to handle that in? Aw.

75 00:19:30.440 00:19:36.609 Luke Daque: I think, for for simple tests like that, I think we can just use Dbt.

76 00:19:36.940 00:19:43.550 Awaish Kumar: We don’t want to. That’s the plan, right? We, if we if we can just use Dbt, we don’t need meta plan. Then

77 00:19:43.700 00:19:44.749 Awaish Kumar: we want to.

78 00:19:44.750 00:19:45.240 Luke Daque: Yeah.

79 00:19:45.240 00:19:49.030 Awaish Kumar: Use Meta plane for all of our testing. That’s that’s the plan.

80 00:19:49.190 00:19:53.040 Luke Daque: Yeah, I don’t think they have such tests. They only have, like

81 00:19:53.480 00:19:56.069 Luke Daque: some sort of anomaly defection, or like.

82 00:19:56.600 00:20:00.310 Luke Daque: like, even for the uniqueness, tests and null tests.

83 00:20:00.310 00:20:05.760 Awaish Kumar: No, but they had the like. They said, like, you can write custom queries for testing.

84 00:20:06.490 00:20:10.689 Luke Daque: Yeah, but it’s still even the custom queries. They are also still

85 00:20:13.000 00:20:21.019 Luke Daque: some sort of like an anomaly detection. So let’s say, our cost. For example, our custom test is just a uniqueness test.

86 00:20:21.740 00:20:29.662 Luke Daque: So even if even if there is, even if the sequel statement is just looking for uniqueness, Meta plane will

87 00:20:30.660 00:20:35.969 Luke Daque: look at it as if it was an anomaly detection, so it will see how many times

88 00:20:36.170 00:20:41.701 Luke Daque: a a column has unique, and then sets a standard deviation for that, for, like

89 00:20:42.790 00:20:48.990 Luke Daque: like a running average. And if ever the count of Uniqueness goes, Michael Geneview.

90 00:20:49.680 00:20:54.430 Awaish Kumar: My question would be, is there a way to do it? For example, if I write a query like.

91 00:20:55.170 00:21:00.809 Awaish Kumar: if I write a custom query, like, select one from some table.

92 00:21:00.810 00:21:01.200 Luke Daque: Hmm.

93 00:21:01.200 00:21:05.280 Awaish Kumar: Where the region is in qualified region.

94 00:21:05.840 00:21:06.260 Luke Daque: Right.

95 00:21:06.540 00:21:10.049 Awaish Kumar: So whenever the region is in that it will give one.

96 00:21:10.150 00:21:12.009 Awaish Kumar: and it will be always be.

97 00:21:12.480 00:21:13.520 Luke Daque: One, yeah.

98 00:21:13.520 00:21:17.109 Awaish Kumar: Give one license. If if it’s not there, it will give

99 00:21:17.670 00:21:21.279 Awaish Kumar: it will, it will not return one, and it will be an anomaly right. It will then return.

100 00:21:21.280 00:21:27.579 Luke Daque: Yeah, yeah, we can do it like that. But yeah, so it’s going to be a different way of writing our

101 00:21:27.820 00:21:30.349 Luke Daque: test so that it will work.

102 00:21:30.350 00:21:30.760 Awaish Kumar: Okay.

103 00:21:30.760 00:21:32.650 Luke Daque: With Meta claim, yeah.

104 00:21:32.650 00:21:40.000 Awaish Kumar: Okay, so, but my point is like, are we? We are able to handle it but one way or other. That’s the point.

105 00:21:40.000 00:21:43.230 Luke Daque: Yeah, I think, so, yeah, yeah.

106 00:21:43.230 00:21:47.150 Awaish Kumar: Okay? So we like, let’s write some notes on this

107 00:21:47.340 00:21:54.530 Awaish Kumar: on Meta plans feature just like some bullet points and then we will discuss pricing. We’ll put it in there

108 00:21:54.630 00:21:58.699 Awaish Kumar: and then. We have a 1 pager summary of features plus pricing.

109 00:21:58.850 00:22:01.530 Awaish Kumar: and then we can easily make a decision.

110 00:22:02.150 00:22:03.060 Luke Daque: Gotcha.

111 00:22:04.376 00:22:08.623 Annie Yu: Do we need a picture for that? Or or look should just remember.

112 00:22:09.260 00:22:10.750 Awaish Kumar: Let’s create.

113 00:22:12.120 00:22:13.070 Annie Yu: Okay.

114 00:22:13.950 00:22:19.320 Awaish Kumar: Like create a notion, Doc. Maybe notion, Doc, with with a summary

115 00:22:21.370 00:22:25.140 Awaish Kumar: of features of Meta playing it. It should be just bullet points

116 00:22:28.560 00:22:32.560 Awaish Kumar: we will have only have 2 tab, 2 kind of

117 00:22:33.110 00:22:37.360 Awaish Kumar: headings. One is features, metaplane features, and then Meta plane pricing.

118 00:22:41.180 00:22:42.380 Annie Yu: Pricing.

119 00:22:42.700 00:22:45.859 Annie Yu: Okay, is that for look.

120 00:22:48.440 00:22:54.990 Awaish Kumar: It’s not like. It’s not like, I don’t want you to explain like ours. It’s just maybe spend some

121 00:22:55.150 00:22:58.319 Awaish Kumar: under an hour to get this.

122 00:22:59.640 00:23:05.639 Awaish Kumar: You have already tested a lot of meta plans, things we just write down whatever features there are.

123 00:23:11.830 00:23:13.379 Awaish Kumar: Okay. We are done here.

124 00:23:16.330 00:23:16.980 Annie Yu: Okay.

125 00:23:17.310 00:23:20.130 Awaish Kumar: Okay. Now, you can tick off any.

126 00:23:21.220 00:23:25.019 Annie Yu: Yeah, for this one on my plate.

127 00:23:25.300 00:23:27.360 Annie Yu: I actually haven’t

128 00:23:27.680 00:23:36.869 Annie Yu: haven’t done anything here. Didn’t have time last week, but I think I’m gonna prioritize this today. So if

129 00:23:37.725 00:23:42.245 Annie Yu: if Luke, you have a 30 min today,

130 00:23:42.980 00:23:45.910 Annie Yu: will you be able to help me with this.

131 00:23:47.970 00:23:54.880 Luke Daque: Yeah, sure, I’m I’m free today. I believe I don’t have lots of stuff to do. So. Yeah.

132 00:23:55.100 00:23:56.259 Luke Daque: we can have that.

133 00:23:56.720 00:24:06.239 Annie Yu: Okay, that’s great. I’ll I’ll send an invite just right after this call. I’m gonna prioritize this like over the other teams today.

134 00:24:06.990 00:24:10.020 Luke Daque: Sure sounds good, cool.

135 00:24:11.719 00:24:15.309 Annie Yu: And then a lot of I’m not sure.

136 00:24:15.710 00:24:17.770 Annie Yu: Is he on the call? He’s not.

137 00:24:18.870 00:24:19.739 Awaish Kumar: He doesn’t.

138 00:24:19.740 00:24:20.689 Awaish Kumar: Okay, let me.

139 00:24:22.160 00:24:26.999 Awaish Kumar: Okay, we can just move on. And for the 1st topic.

140 00:24:33.580 00:24:37.009 Annie Yu: Wish. Do you have any updates that you want to highlight.

141 00:24:37.510 00:24:41.960 Awaish Kumar: Yeah, like, on this ticket, like Dvt, internal platform cost efficiency.

142 00:24:42.735 00:24:47.790 Awaish Kumar: I have created 2 another tickets for this. So basically.

143 00:24:48.030 00:24:51.390 Awaish Kumar: we want to have a platform where

144 00:24:51.907 00:24:55.960 Awaish Kumar: we run our all like DVD jobs for all of our clients

145 00:24:56.778 00:25:00.940 Awaish Kumar: cost efficiently. Right now we are running it in Github actions.

146 00:25:01.190 00:25:04.040 Awaish Kumar: We want to have a poc on

147 00:25:05.041 00:25:10.270 Awaish Kumar: where we can move from away from Github actions.

148 00:25:10.390 00:25:18.250 Awaish Kumar: So one way is to trigger them through the Daxter. So I’ve created 2 tickets like Dp, 51.

149 00:25:18.620 00:25:21.970 Awaish Kumar: And I think it’s the one is 52 like if you could.

150 00:25:22.320 00:25:25.970 Awaish Kumar: If you little bit scroll up in progress tickets.

151 00:25:26.910 00:25:28.809 Awaish Kumar: I’ve created these 2 tickets.

152 00:25:28.970 00:25:40.149 Awaish Kumar: I want to have a test to integrate Dexter with urban stems. Dbt project and see how we can manage

153 00:25:40.330 00:25:44.340 Awaish Kumar: to run Dbt jobs from

154 00:25:45.260 00:25:52.950 Awaish Kumar: through Dexter. If there is any update on Dbt project like any commit in any new, we have merged domain.

155 00:25:53.680 00:25:58.970 Awaish Kumar: We, the Dexter triggers the job to run it instead of bit of action.

156 00:26:01.320 00:26:08.763 Awaish Kumar: So this is the one of the ticket which is basically result of

157 00:26:10.590 00:26:20.000 Awaish Kumar: researching on this, and if if we get, if we successfully run it through extra, we will do it. Otherwise we will might try something else.

158 00:26:20.350 00:26:22.535 Awaish Kumar: So I have these 2 tickets

159 00:26:23.630 00:26:27.859 Awaish Kumar: to assign to somebody, but I don’t. We don’t have anyone else. Then

160 00:26:28.630 00:26:31.190 Awaish Kumar: me and Luke to handle it.

161 00:26:34.990 00:26:41.010 Awaish Kumar: Let me discuss with Kyle, and they are interested in in working on this.

162 00:26:42.450 00:26:48.350 Awaish Kumar: Otherwise I look and like we will assign this between us.

163 00:26:53.430 00:26:58.199 Awaish Kumar: So we have 2 tasks. One is to run DVD. Via Dexter. Another one is to run

164 00:26:58.330 00:27:01.149 Awaish Kumar: for atomic tasks. So we have some

165 00:27:01.990 00:27:05.229 Awaish Kumar: integrate like we, we run some

166 00:27:06.730 00:27:13.459 Awaish Kumar: integration like ingestions through our tool called polytomic. So if we want to move data from slack to

167 00:27:13.800 00:27:20.320 Awaish Kumar: to, for example, Google bigquery, we can do it through polyatomic. But we we want a a pipeline.

168 00:27:21.280 00:27:40.010 Awaish Kumar: a centralized pipeline which basically controls the complete flow. Right now, polyatomic is running independently. Dbt is running independently. We don’t have like, if if polytomic fails, we still run dbt, so there’s no control over it. So we want to have a

169 00:27:40.370 00:27:43.800 Awaish Kumar: centralized place from where we control our flows.

170 00:27:43.930 00:27:48.999 Awaish Kumar: So this is the these are the tasks pushing us toward that direction.

171 00:27:53.360 00:28:02.210 Awaish Kumar: So let’s wait before we assign this to someone. And then, yeah, you can go ahead with.

172 00:28:03.640 00:28:04.350 Annie Yu: Okay.

173 00:28:08.694 00:28:13.559 Annie Yu: so that’s pretty much these are the same thing as these ones. Right?

174 00:28:13.820 00:28:14.650 Awaish Kumar: Yes, yes.

175 00:28:14.650 00:28:18.043 Annie Yu: These ones, and then

176 00:28:24.320 00:28:26.079 Awaish Kumar: Yeah, we have this 48.

177 00:28:27.710 00:28:28.410 Annie Yu: 4.th

178 00:28:29.530 00:28:30.330 Annie Yu: Here.

179 00:28:33.480 00:28:35.330 Annie Yu: look! Do you want to take it?

180 00:28:37.190 00:28:41.509 Luke Daque: The poor parts to go set up. Yeah, I did set up

181 00:28:42.170 00:28:56.380 Luke Daque: 4 parts to go in Meta plane, although it’s not yet complete. I was able to set up snow, the Snowflake environment, and Dvt. But I haven’t started anything yet. I’m planning to do that as soon as I have like time to best

182 00:28:57.395 00:29:06.039 Luke Daque: especially the source diff, and also the yes, since it’s already using

183 00:29:06.680 00:29:13.330 Luke Daque: Snowflake. So we should be able to do the diffs better compared to the big query that we were using for them.

184 00:29:16.970 00:29:21.929 Awaish Kumar: Okay. So where we are here like, can it be done by today? End of day or.

185 00:29:22.196 00:29:27.259 Luke Daque: Yeah, I think so. I’ll I I suppose I have time today to to work on that one. Yeah.

186 00:29:27.550 00:29:28.210 Awaish Kumar: Okay?

187 00:29:30.140 00:29:44.240 Awaish Kumar: And any, please have some like progress on urban stem stuff. And apart from that, I have

188 00:29:44.390 00:29:46.890 Awaish Kumar: one more ticket with which kind of a

189 00:29:47.220 00:29:51.870 Awaish Kumar: kind of this like this investigation ticket. So let’s create one more ticket.

190 00:29:55.880 00:30:00.500 Awaish Kumar: We just want to like, we want to create performance dashboards.

191 00:30:01.760 00:30:10.110 Awaish Kumar: So for internal for all our clients or projects, so.

192 00:30:10.720 00:30:12.350 Annie Yu: What kind of dashboard.

193 00:30:13.240 00:30:15.679 Awaish Kumar: Performance dashboard cost.

194 00:30:16.050 00:30:22.670 Awaish Kumar: Okay? You can. What you see, you can see a performance dashboard, basically, for all our projects.

195 00:30:23.970 00:30:26.850 Awaish Kumar: for all the brain folds, projects.

196 00:30:28.570 00:30:31.510 Annie Yu: Okay, dashboards for.

197 00:30:32.170 00:30:34.629 Awaish Kumar: Performance, performance, dashboards.

198 00:30:34.630 00:30:36.020 Annie Yu: Orange. Okay.

199 00:30:37.870 00:30:46.110 Awaish Kumar: So basically, we, we will be measuring the performance of our projects, either client or internal.

200 00:30:48.940 00:30:51.030 Awaish Kumar: Also internal projects.

201 00:30:52.976 00:30:55.410 Annie Yu: Okay. So this is including.

202 00:30:55.850 00:30:56.710 Awaish Kumar: Yeah. Eric.

203 00:30:58.420 00:31:02.880 Annie Yu: All client project, and internal.

204 00:31:06.810 00:31:17.970 Awaish Kumar: Yes. So basically, what what we mean by performance is we want to measure. For example, if we have a client which pays us 8,000

205 00:31:18.400 00:31:20.100 Awaish Kumar: dollars per month.

206 00:31:20.460 00:31:24.110 Awaish Kumar: Then we’ll want to have a dashboard where we can measure our cost.

207 00:31:24.240 00:31:31.150 Awaish Kumar: So, for example, on a client, 3 people are working how much time they spend on

208 00:31:32.530 00:31:36.040 Awaish Kumar: on working on this client for this month.

209 00:31:36.140 00:31:43.089 Awaish Kumar: plus the the cost we incurred by using some tools for this client.

210 00:31:43.210 00:31:50.689 Awaish Kumar: we should we spend some time for our like from our leadership team? And

211 00:31:50.930 00:31:55.480 Awaish Kumar: so we combine all that and figure out a cost right?

212 00:31:55.740 00:32:01.090 Awaish Kumar: What is our cost? What is our revenue, and what is our profit for this?

213 00:32:02.364 00:32:08.510 Awaish Kumar: Client, and also for internal project? We just measure the cost and compare it with the

214 00:32:10.600 00:32:18.820 Awaish Kumar: like how much we are able to do like effort, like how much we have spent

215 00:32:19.090 00:32:24.550 Awaish Kumar: and how much we achieved, like, how many things we were able to.

216 00:32:24.710 00:32:31.160 Awaish Kumar: Oh, streamline, or optimize or make cost efficient things like that.

217 00:32:32.290 00:32:39.770 Awaish Kumar: Because internal projects we don’t have revenue. We will just measure that cost plus like outcome.

218 00:32:45.620 00:32:52.059 Awaish Kumar: So I would love to like this will be a kind of spike if you can just write it on top.

219 00:32:52.310 00:32:58.470 Awaish Kumar: It’s not like, yeah, it’s not an indirectly implementation projects.

220 00:32:58.730 00:33:06.469 Awaish Kumar: So we will have implementation for that. We might have few extra tickets where every one of us has to do something

221 00:33:06.640 00:33:10.339 Awaish Kumar: to push it forward right now. It’s just a

222 00:33:11.140 00:33:20.049 Awaish Kumar: research research project, and I would love you to take it. Because, like.

223 00:33:20.960 00:33:24.339 Awaish Kumar: like, here, we are talking about dashboards. So I would

224 00:33:24.760 00:33:30.349 Awaish Kumar: like you this to be assigned to you. So you will be running a research on on it

225 00:33:30.990 00:33:35.750 Awaish Kumar: like how we can do it right? So what kind of a data you need?

226 00:33:36.110 00:33:41.029 Awaish Kumar: And then we’d figure out, okay, this data is will be coming from these sources.

227 00:33:41.210 00:33:49.962 Awaish Kumar: And you need maybe linear tickets. You need maybe access to like client revenue

228 00:33:51.540 00:33:56.139 Awaish Kumar: and maybe access to clockify. Or maybe

229 00:33:56.560 00:34:02.415 Awaish Kumar: if we have points in the lenience ticket. So we can just figure out from there and

230 00:34:03.700 00:34:10.800 Awaish Kumar: and like things like that plan, maybe access to some internal. Now,

231 00:34:15.520 00:34:22.205 Awaish Kumar: like, what like you? What else? From linear from, I don’t know from

232 00:34:25.679 00:34:29.880 Awaish Kumar: cost. Yeah. Cost. Yeah, for internal tools. Yeah.

233 00:34:30.780 00:34:37.239 Awaish Kumar: not internal, but the generally the tools like we use, like, for example for some client. If we are running Meta plane

234 00:34:38.050 00:34:44.639 Awaish Kumar: right? And we are paying for that, it’s our cost right for that client. So like, maybe we are paying 200.

235 00:34:47.820 00:34:55.259 Awaish Kumar: for for Meta, plan for some clients. So this that’s some cost so like like the cost, like human cost, plus

236 00:34:55.960 00:34:59.610 Awaish Kumar: cause from any tools, or like all all the all of that thing.

237 00:35:00.490 00:35:05.319 Awaish Kumar: And yeah, just run a Poc, how you can.

238 00:35:05.440 00:35:10.090 Awaish Kumar: what kind of data you will need. How will you produce a dashboard? You will be putting it in.

239 00:35:10.810 00:35:12.589 Awaish Kumar: and maybe

240 00:35:12.890 00:35:23.270 Awaish Kumar: like what kind of tool we will be using for building the dashboard for our internal work. So all of that questions needs to be answered before we move towards implementation.

241 00:35:41.750 00:35:42.320 Annie Yu: Bye,

242 00:35:46.130 00:35:52.850 Awaish Kumar: Come up with a Come up with a plan, and then we can move

243 00:35:54.280 00:35:58.200 Awaish Kumar: to have some proof like minimum Mvp.

244 00:35:58.860 00:36:01.749 Awaish Kumar: And from there we can then figure out what role.

245 00:36:03.070 00:36:07.189 Annie Yu: Okay, okay? Yeah. And then

246 00:36:08.440 00:36:12.399 Annie Yu: then we’ll we’ll assign tasks right?

247 00:36:13.340 00:36:19.670 Awaish Kumar: Yeah, like, obviously, like, if if it’s a

248 00:36:19.990 00:36:24.420 Awaish Kumar: if, it’s something like to do with well, I think

249 00:36:24.830 00:36:30.080 Awaish Kumar: scripts do some work with the ingestion. Then, like

250 00:36:31.011 00:36:38.178 Awaish Kumar: we will be taking it and if it’s some like, all the dashboarding work will be assigned to you. Anyway.

251 00:36:41.050 00:36:41.810 Annie Yu: Okay.

252 00:36:42.720 00:37:05.639 Annie Yu: yeah. And and for the dashboarding part, I think definitely fine with me building it. I’m just calling out, not sure if Kyle will be interested. Because I know that he’s got some experience in dashboarding. I also think he mentioned something about this, so just in case you he will be interested.

253 00:37:05.920 00:37:06.420 Annie Yu: That’ll be.

254 00:37:06.420 00:37:12.910 Awaish Kumar: Yeah, yeah, like, let’s just run this Poc and create. Then we create some tickets. Then we’ll see how to assign it.

255 00:37:13.150 00:37:14.250 Annie Yu: Yeah.

256 00:37:14.860 00:37:21.059 Awaish Kumar: So yeah, this week, I I would love that. You you guys finish what what is assigned to you

257 00:37:21.330 00:37:22.539 Awaish Kumar: within the week.

258 00:37:22.760 00:37:27.039 Awaish Kumar: I wouldn’t like to like, because this I don’t think there’s much.

259 00:37:28.430 00:37:34.390 Awaish Kumar: There’s like a lot of workload here you have like the tickets you have is kind of

260 00:37:34.640 00:37:36.129 Awaish Kumar: few hours of work.

261 00:37:36.350 00:37:43.430 Awaish Kumar: Chrome, so it would be nice if we can finish it in this week from.

262 00:37:44.680 00:37:50.210 Awaish Kumar: I don’t take it to the next week, so we have some progress here as well.

263 00:37:50.550 00:37:58.630 Awaish Kumar: And yeah, I think for Luke and me, we we have these tickets to work on

264 00:37:58.860 00:38:05.730 Awaish Kumar: regarding Dbt integration. And yeah, for for any. I think you only work

265 00:38:06.220 00:38:10.049 Awaish Kumar: maybe 5 to 8 h. We. You can just suspend on these 2 tickets.

266 00:38:10.650 00:38:13.110 Awaish Kumar: and maybe we’ll also pair with Luke

267 00:38:13.830 00:38:19.709 Awaish Kumar: for Kyle and them. Ladi, I I will discuss with them how they want to

268 00:38:20.290 00:38:23.119 Awaish Kumar: like what they want to work on in this week.

269 00:38:24.070 00:38:24.680 Annie Yu: Okay.

270 00:38:25.070 00:38:26.170 Awaish Kumar: Okay. Thank you.

271 00:38:26.560 00:38:28.490 Annie Yu: Okay, it’s good.

272 00:38:29.190 00:38:31.679 Luke Daque: Guys have a nice rest of your day.

273 00:38:32.130 00:38:34.640 Annie Yu: Yeah, thank you guys.

274 00:38:34.640 00:38:35.210 Awaish Kumar: Bye.