Meeting Title: Magic Spoon and CTA Planning Sync Date: 2026-01-21 Meeting participants: Ashwini Sharma, Awaish Kumar
WEBVTT
1 00:01:19.790 ⇒ 00:01:20.800 Awaish Kumar: Hello?
2 00:01:21.350 ⇒ 00:01:22.260 Ashwini Sharma: Ewie.
3 00:01:25.900 ⇒ 00:01:26.550 Ashwini Sharma: Wait a second.
4 00:01:26.550 ⇒ 00:01:27.970 Awaish Kumar: Yeah, so…
5 00:01:28.790 ⇒ 00:01:29.790 Ashwini Sharma: Vineyard.
6 00:01:30.350 ⇒ 00:01:34.409 Awaish Kumar: Like, I just wanted to understand how…
7 00:01:34.620 ⇒ 00:01:38.199 Awaish Kumar: Much like your time is
8 00:01:38.670 ⇒ 00:01:42.180 Awaish Kumar: being spent on Magic Spoon and CTA.
9 00:01:43.160 ⇒ 00:01:43.960 Ashwini Sharma: So…
10 00:01:44.410 ⇒ 00:01:50.259 Awaish Kumar: It’s something… Like, what I assigned initially was 10 for Magic Spawn.
11 00:01:50.470 ⇒ 00:01:53.260 Awaish Kumar: 24 city, and 10 for Eden.
12 00:01:53.540 ⇒ 00:01:57.320 Awaish Kumar: That’s what I was… Under the impression.
13 00:01:57.510 ⇒ 00:02:04.590 Ashwini Sharma: Yeah, so that 10 is not enough for Magic Spoon, right? Especially when… Dealing with this pipeline.
14 00:02:05.130 ⇒ 00:02:06.950 Ashwini Sharma: I don’t know, like, how… yeah…
15 00:02:08.160 ⇒ 00:02:12.190 Awaish Kumar: I’m also coming into the CTA now.
16 00:02:12.670 ⇒ 00:02:15.400 Awaish Kumar: So that goes… Yeah, so… Right.
17 00:02:18.340 ⇒ 00:02:23.319 Ashwini Sharma: I think I need to split 50% time with Magic Spoon and CTA.
18 00:02:23.640 ⇒ 00:02:26.969 Ashwini Sharma: I mean, 50% CTA, 50% magic spawn.
19 00:02:27.570 ⇒ 00:02:32.810 Awaish Kumar: Yeah, but then, like, that 50% is going to be 50-50 between us.
20 00:02:35.510 ⇒ 00:02:36.460 Awaish Kumar: But I’m…
21 00:02:36.460 ⇒ 00:02:38.420 Ashwini Sharma: No, you’re not there in Magic Phone, right?
22 00:02:38.940 ⇒ 00:02:40.280 Awaish Kumar: No, no, I’m CTA.
23 00:02:40.490 ⇒ 00:02:45.959 Awaish Kumar: So when I… I… like, if you would just, like, introduce me, right?
24 00:02:45.960 ⇒ 00:02:46.890 Ashwini Sharma: Yeah.
25 00:02:47.000 ⇒ 00:02:51.389 Ashwini Sharma: So, now that I am on CTA.
26 00:02:51.390 ⇒ 00:02:53.870 Awaish Kumar: You don’t have to spend 20 hours on this.
27 00:02:53.870 ⇒ 00:03:00.390 Ashwini Sharma: Okay, yeah, yeah, yeah. Now if you’re there in CTA, then I can spend, lesser time on CTA.
28 00:03:01.930 ⇒ 00:03:10.499 Awaish Kumar: Yeah, but that’s one of the things, right? That’s… that’s the planning that… like, that’s what we also thought of.
29 00:03:10.680 ⇒ 00:03:12.430 Awaish Kumar: might expune that.
30 00:03:12.540 ⇒ 00:03:21.620 Awaish Kumar: time should be less spent between you and Tammy. Like, you both should be able to cover it in between 20 to 30 hours max.
31 00:03:21.780 ⇒ 00:03:26.990 Awaish Kumar: It should not go beyond that, like, for both of you. But if it is going, right.
32 00:03:26.990 ⇒ 00:03:27.620 Ashwini Sharma: Yep.
33 00:03:27.620 ⇒ 00:03:30.020 Awaish Kumar: Then we need to figure out how…
34 00:03:30.310 ⇒ 00:03:33.910 Awaish Kumar: Like, if we should slow it, like, there are a few things we can say.
35 00:03:34.550 ⇒ 00:03:37.569 Awaish Kumar: Like, the client is always going to ask something.
36 00:03:38.530 ⇒ 00:03:45.240 Awaish Kumar: if I see the tickets in the roadmap, like, if you tell me that this is the plan for this week.
37 00:03:45.870 ⇒ 00:03:48.110 Awaish Kumar: And then I’m going to follow through that.
38 00:03:48.340 ⇒ 00:03:49.589 Awaish Kumar: The whole week.
39 00:03:49.810 ⇒ 00:03:51.450 Awaish Kumar: I’m going to push for that.
40 00:03:51.730 ⇒ 00:03:56.609 Awaish Kumar: But, if you are clear and come to me on Monday that
41 00:03:56.800 ⇒ 00:04:06.529 Awaish Kumar: In the 10 hours, this is what we are going to deliver, or in the 20 or 30 hours between me and Tamilare, this is our plan for the week.
42 00:04:07.160 ⇒ 00:04:11.259 Awaish Kumar: And then we can see if that is enough, if we need to…
43 00:04:11.520 ⇒ 00:04:15.130 Awaish Kumar: Add more time if we need to,
44 00:04:15.340 ⇒ 00:04:20.079 Awaish Kumar: Slow down, like, whatever… whatever the… what we… whatever we can do, right?
45 00:04:21.550 ⇒ 00:04:26.230 Awaish Kumar: Otherwise, it is really hard for me to make any kind of decision, or any…
46 00:04:26.380 ⇒ 00:04:28.370 Awaish Kumar: Any case for Utam, right?
47 00:04:28.670 ⇒ 00:04:32.640 Awaish Kumar: I know… I’m just getting pinged from everybody.
48 00:04:34.490 ⇒ 00:04:37.430 Awaish Kumar: on, like, on that we…
49 00:04:37.670 ⇒ 00:04:39.610 Awaish Kumar: We should be able to do that.
50 00:04:41.200 ⇒ 00:04:45.630 Awaish Kumar: But we are not, right? Like, for Edith, Robert is really exhausted.
51 00:04:45.900 ⇒ 00:04:50.449 Awaish Kumar: That, like, none of us actually worked on it last few weeks.
52 00:04:54.360 ⇒ 00:04:59.900 Awaish Kumar: That’s what we have to figure out. We have to find out if there are a few things we can optimize.
53 00:05:00.340 ⇒ 00:05:04.784 Awaish Kumar: In terms of… Tickets, or in terms of
54 00:05:05.660 ⇒ 00:05:08.690 Awaish Kumar: Like, the comms, or anything, like…
55 00:05:09.210 ⇒ 00:05:12.359 Awaish Kumar: If something can be optimized, we are going for it.
56 00:05:12.540 ⇒ 00:05:15.760 Awaish Kumar: If nothing can be optimized and everything is kind of…
57 00:05:16.030 ⇒ 00:05:22.059 Awaish Kumar: Ideal… under an ideal situation, we are just going to… Make some decisions on…
58 00:05:22.200 ⇒ 00:05:31.220 Awaish Kumar: how we should, sign over time, and then how much more support we need. We need to hire people, or some… whatever.
59 00:05:33.880 ⇒ 00:05:39.840 Ashwini Sharma: Yeah, I mean, like, when I look at the kind of work that is there in Magic Spoon, right.
60 00:05:41.680 ⇒ 00:05:43.719 Ashwini Sharma: Basically, this pipeline related.
61 00:05:43.910 ⇒ 00:05:46.699 Ashwini Sharma: It’s… it’s kind of, you know,
62 00:05:48.350 ⇒ 00:05:55.199 Ashwini Sharma: quite difficult to estimate, like, I’ll be done in this many hours, right? Considering the uncertainty around this pipeline.
63 00:05:57.160 ⇒ 00:06:04.529 Ashwini Sharma: And that’s why, yeah, like, last two days, I’ve spent a lot of time with Magix, just trying to figure out, like.
64 00:06:04.660 ⇒ 00:06:10.489 Ashwini Sharma: you know, Why it does not work, the pipeline, when the data volume is used.
65 00:06:10.740 ⇒ 00:06:13.080 Awaish Kumar: That could be the issue, right? That…
66 00:06:13.770 ⇒ 00:06:23.549 Awaish Kumar: like, you understand, like, you are very, like, you are a really very senior engineer, right? You know, whenever an engineer says that
67 00:06:23.780 ⇒ 00:06:32.379 Awaish Kumar: System is not working, that… that means, like, there is something in there, like, we are just not able to find out yet.
68 00:06:32.380 ⇒ 00:06:37.990 Ashwini Sharma: Yeah, that’s a… I agree to that. I’m not able to find… find it out yet. If I find out, I’ll fix it, that’s… that’s for sure.
69 00:06:37.990 ⇒ 00:06:38.550 Awaish Kumar: Sure.
70 00:06:39.140 ⇒ 00:06:41.329 Awaish Kumar: Yeah, that’s the… that’s the thing, like…
71 00:06:41.590 ⇒ 00:06:48.890 Awaish Kumar: system, does not introduce anything. We, have, like, we have to figure out the process
72 00:06:49.080 ⇒ 00:06:51.660 Awaish Kumar: Through which we can identify these things
73 00:06:51.930 ⇒ 00:06:56.580 Awaish Kumar: Quicker. Maybe this time it took time? Okay, that’s no problem.
74 00:06:56.890 ⇒ 00:07:02.150 Awaish Kumar: But… We, like, if this is a learning, you identify the pattern.
75 00:07:02.270 ⇒ 00:07:08.080 Awaish Kumar: What you have tried, what worked, what didn’t work. Maybe create something for the team, right?
76 00:07:08.460 ⇒ 00:07:11.489 Awaish Kumar: Maybe share that in a learning, so everybody knows you are…
77 00:07:11.720 ⇒ 00:07:23.609 Awaish Kumar: Like, at least we have some assets to share with our engineering team, that, okay, we have spent two days, we came up with these learnings, and these learnings are going to be gold for the future.
78 00:07:23.930 ⇒ 00:07:24.810 Awaish Kumar: Right?
79 00:07:26.160 ⇒ 00:07:30.699 Ashwini Sharma: Yeah, that can be done. I can create a document that can highlight, you know.
80 00:07:31.300 ⇒ 00:07:33.609 Ashwini Sharma: What worked, what didn’t work?
81 00:07:33.610 ⇒ 00:07:34.000 Awaish Kumar: Yeah.
82 00:07:34.000 ⇒ 00:07:37.700 Ashwini Sharma: And, what didn’t work, basically, because it has not yet worked.
83 00:07:38.430 ⇒ 00:07:45.030 Ashwini Sharma: And… Yeah, like, next time, if somebody has to create a pipeline for Magic Spoon.
84 00:07:45.210 ⇒ 00:07:50.360 Ashwini Sharma: Maybe, you know, they can incorporate the learnings from that.
85 00:07:50.530 ⇒ 00:07:57.760 Ashwini Sharma: And then utilize it. I mean, that totally can be done, right? I think the issue over here is how much time we should spend with Eden.
86 00:07:57.900 ⇒ 00:08:01.550 Ashwini Sharma: how much time we need to spend with the other clients, right?
87 00:08:01.740 ⇒ 00:08:07.350 Awaish Kumar: Yeah, there are a few things, right? For example, for example, if we were to start on something.
88 00:08:07.590 ⇒ 00:08:12.139 Awaish Kumar: on something, right? We need to pair it quickly, right?
89 00:08:12.650 ⇒ 00:08:16.850 Awaish Kumar: Like, if this thing get escalated, Bye.
90 00:08:17.030 ⇒ 00:08:18.910 Awaish Kumar: Utam, or by client.
91 00:08:20.630 ⇒ 00:08:24.090 Awaish Kumar: You know, like, it is then going to be a really…
92 00:08:25.070 ⇒ 00:08:30.149 Awaish Kumar: like, frustrating for everybody. We’re all then going to spend…
93 00:08:30.680 ⇒ 00:08:38.910 Awaish Kumar: all our hours burning on this thing. So, what I’m trying to say is that if you… you have spent
94 00:08:39.049 ⇒ 00:08:42.510 Awaish Kumar: One day, or more than a day, to fix some
95 00:08:42.620 ⇒ 00:08:48.520 Awaish Kumar: thing, like, single thing. Maybe just… maybe just pair, or…
96 00:08:49.330 ⇒ 00:08:54.890 Awaish Kumar: Just, like, meet with… meet for brainstorming, or whatever.
97 00:08:55.460 ⇒ 00:08:58.980 Awaish Kumar: And, yeah, and, like, maybe…
98 00:08:59.650 ⇒ 00:09:02.960 Awaish Kumar: We need to at least make it very, very clear.
99 00:09:03.570 ⇒ 00:09:16.719 Awaish Kumar: In our channels, that this is what we are going to… like, this is a blocker, this is what we are doing, we are already pairing, we are already, we already are aware of this, and we are doing that.
100 00:09:16.850 ⇒ 00:09:22.030 Awaish Kumar: And, like, we need to make it really clear for Otam and for the client, both.
101 00:09:24.690 ⇒ 00:09:27.210 Ashwini Sharma: Yeah, I talked to the client, today.
102 00:09:27.810 ⇒ 00:09:35.770 Ashwini Sharma: And, we decided on an approach right now, because, like, the change in the attributes came from their side.
103 00:09:35.950 ⇒ 00:09:47.069 Ashwini Sharma: So when I added more attributes, that’s where the failure started to happen, right? And right now, there was a rate limit exceeded, so I could not proceed further, and then I started working on CTS stuff.
104 00:09:47.980 ⇒ 00:09:57.810 Awaish Kumar: That’s one thing, but what I’m trying to say is that we should… like, they added some fee… some new fields, and they just started… the pipeline started paying.
105 00:09:57.860 ⇒ 00:10:09.220 Awaish Kumar: But what I’m saying, like, what you can say, okay, this is taking more time than expected, this is why, like, the new fields are added, but because of that, there are some
106 00:10:09.420 ⇒ 00:10:27.149 Awaish Kumar: like, in terms of APIs not sending us proper errors, there are not proper logging system in API, for whatever reasons, we are not able to identify the issue yet. We are taking measures on it, we are already meeting with the…
107 00:10:27.270 ⇒ 00:10:32.030 Awaish Kumar: Meeting in a team to brainstorm on tape on it, and we are already…
108 00:10:32.250 ⇒ 00:10:39.549 Awaish Kumar: Doing that, so, like, so they know that this is already our period, so they don’t have to come in and escalate.
109 00:10:41.020 ⇒ 00:10:45.419 Ashwini Sharma: Have they escalated? Like, I thought Madison is happy with the kind of thing that we are doing.
110 00:10:45.420 ⇒ 00:11:00.160 Awaish Kumar: They haven’t, and I… but I have seen. I have been here, like, for more than a year, I’ve seen these issues when we are… we assume everything is going great, and one day, one of the stakeholders just comes up with something, and then…
111 00:11:00.380 ⇒ 00:11:02.140 Awaish Kumar: Everything gets dropped.
112 00:11:02.340 ⇒ 00:11:10.799 Awaish Kumar: So I don’t want to be in that situation again. So, like, if you… like, what I’ve said is, there is nothing, like, we can’t do.
113 00:11:10.980 ⇒ 00:11:14.850 Awaish Kumar: It is just… just a way of being more proactive, right?
114 00:11:14.990 ⇒ 00:11:21.290 Awaish Kumar: there’s nothing I’m telling you which is, like, something really difficult. That’s just, like.
115 00:11:21.400 ⇒ 00:11:28.339 Awaish Kumar: You just say in different language that, okay, you are already giving them a priority, that’s all.
116 00:11:32.350 ⇒ 00:11:42.010 Ashwini Sharma: Okay, so let’s, let’s, you know, I think let’s, let’s formalize, right, the number of clients that we’ll be working on, because obviously, like, we cannot be in every place.
117 00:11:44.830 ⇒ 00:11:48.410 Awaish Kumar: Yeah, yeah, that’s… that’s a different… yeah, that’s…
118 00:11:48.410 ⇒ 00:11:52.619 Ashwini Sharma: Yeah, let’s not make it more than 3 per… developer, right?
119 00:11:53.360 ⇒ 00:11:56.199 Ashwini Sharma: I don’t know how others are doing it, like.
120 00:11:56.480 ⇒ 00:11:59.310 Awaish Kumar: But that is… that depends completely on…
121 00:11:59.740 ⇒ 00:12:05.010 Awaish Kumar: On the hours, normally, yeah, that’s an ideal situation, what you just said.
122 00:12:05.310 ⇒ 00:12:09.720 Awaish Kumar: no one developer for more than two clients. I…
123 00:12:09.940 ⇒ 00:12:21.660 Awaish Kumar: Any ideal situation, I agree with that, but there are times when we have to do that, like, because maybe for some clients you don’t have the 20 hours of work.
124 00:12:21.920 ⇒ 00:12:23.680 Awaish Kumar: And then water, like…
125 00:12:24.110 ⇒ 00:12:27.479 Ashwini Sharma: No, when there is not, then definitely, yeah, I mean.
126 00:12:28.150 ⇒ 00:12:29.800 Awaish Kumar: So that’s… that’s why…
127 00:12:30.910 ⇒ 00:12:44.779 Awaish Kumar: That’s why this talk is happening, because I want to make sure, if there is a work of 28 and 20 hours on both, then if you are working on that, then that should be it. For Eden, we need to hire somebody.
128 00:12:45.080 ⇒ 00:12:53.680 Awaish Kumar: So, they… before I have this discussion with Utam, I have to have discussion with my team.
129 00:12:53.790 ⇒ 00:13:01.290 Awaish Kumar: that what we need, what are the problems, why we are… and we are all optimized on everything, and then I can go
130 00:13:01.580 ⇒ 00:13:05.130 Awaish Kumar: Tote them and say, hey, I need more people here. That’s all.
131 00:13:07.370 ⇒ 00:13:12.939 Ashwini Sharma: Yeah, and a few days back didn’t, I think KC was assigned to Eden, right?
132 00:13:13.850 ⇒ 00:13:15.020 Awaish Kumar: Sorry, who? Casey.
133 00:13:15.020 ⇒ 00:13:15.960 Ashwini Sharma: KSC?
134 00:13:16.590 ⇒ 00:13:23.850 Awaish Kumar: Yeah, Casey, he’s not a DOE, he’s an AI engineer. It’s just… Helping there.
135 00:13:25.520 ⇒ 00:13:33.180 Awaish Kumar: with some light stuff, like, he… we can’t say him, really a D or A. He’s…
136 00:13:33.480 ⇒ 00:13:36.070 Awaish Kumar: You can say a beginner, kind of.
137 00:13:38.640 ⇒ 00:13:48.899 Awaish Kumar: like, he’s an AI engineer, and he’s… he’s interested in learning data work. So, that’s why he’s here to support Zoram, which is more, like, really…
138 00:13:49.110 ⇒ 00:13:53.059 Awaish Kumar: Make small adjustments, if we have to do.
139 00:13:53.390 ⇒ 00:13:55.480 Ashwini Sharma: So he won’t be doing any development work.
140 00:13:56.270 ⇒ 00:13:59.349 Awaish Kumar: He will be doing, but, like, a small, like,
141 00:13:59.550 ⇒ 00:14:03.749 Awaish Kumar: like, small things for Zoran. So, for example.
142 00:14:04.190 ⇒ 00:14:22.419 Awaish Kumar: He needs… if he needs to upgrade some DEXA pipeline, or a little bit of SQL, or add new field, but, like, net new model, or complex… if there is complexity in building a model, or something like that, then no, right? He’s not there yet.
143 00:14:29.800 ⇒ 00:14:30.859 Awaish Kumar: Right? Yeah.
144 00:14:30.950 ⇒ 00:14:36.009 Ashwini Sharma: In that case, yeah, I think we should get one more data engineer, definitely, because…
145 00:14:36.890 ⇒ 00:14:38.219 Awaish Kumar: He’s not a, like…
146 00:14:38.220 ⇒ 00:14:43.809 Ashwini Sharma: See, Eden has a lot of, you know, contextual background, right? And…
147 00:14:44.190 ⇒ 00:14:47.150 Awaish Kumar: That’s the problem, yeah, that’s the one thing.
148 00:14:47.150 ⇒ 00:14:55.689 Ashwini Sharma: Yeah, and I don’t have that much of context, like, like the, you know, like what you have, or, like, what Demilade has, right?
149 00:14:55.970 ⇒ 00:15:00.669 Ashwini Sharma: And the thing is, like, when you allocate 10 hours for Eden, right, per week.
150 00:15:01.400 ⇒ 00:15:05.209 Ashwini Sharma: And if there is a new work that needs to be done by me.
151 00:15:05.630 ⇒ 00:15:08.019 Ashwini Sharma: It definitely goes beyond 10 hours.
152 00:15:09.530 ⇒ 00:15:18.360 Awaish Kumar: I… Yeah, like, Yeah, it’s… it’s like…
153 00:15:19.520 ⇒ 00:15:22.690 Ashwini Sharma: And that impacts the other two clients, right?
154 00:15:22.690 ⇒ 00:15:23.100 Awaish Kumar: Yeah.
155 00:15:23.100 ⇒ 00:15:23.920 Ashwini Sharma: NCD.
156 00:15:24.580 ⇒ 00:15:27.429 Awaish Kumar: It has been few V, it has been few…
157 00:15:27.550 ⇒ 00:15:35.139 Awaish Kumar: weeks that we didn’t have anything for Aiden. It’s just recently, we… they have requested some tickets.
158 00:15:35.360 ⇒ 00:15:40.210 Awaish Kumar: And that’s why it’s all that, like, colonization is happening.
159 00:15:42.780 ⇒ 00:15:50.680 Awaish Kumar: And, for… in the… in the, like, in the 10 hours, I… I… Like, I…
160 00:15:50.790 ⇒ 00:15:53.480 Awaish Kumar: I think, like, what you can do is maybe just…
161 00:15:54.690 ⇒ 00:16:07.249 Awaish Kumar: like, you have to tell it, like, at least if… like, if that is it, then you have to tell it. Like, tell everybody, like, if you are taking one ticket, you can assign story parts, and that’s the best way
162 00:16:07.380 ⇒ 00:16:16.110 Awaish Kumar: to tell Robert that, hey, I am assigned 10 hours for this time, I work, like, if you can see those two tickets, and that took my…
163 00:16:17.000 ⇒ 00:16:21.700 Awaish Kumar: 10 story points. That means I already done… I’m already done with my 10 hours.
164 00:16:21.700 ⇒ 00:16:32.860 Ashwini Sharma: Yeah, so there is one issue with the story point thing, right? I mean, Robert thinks that, you know, any issue can be done in two story points. I think that’s his default setting somewhere.
165 00:16:33.210 ⇒ 00:16:41.870 Ashwini Sharma: And that’s not the case. I mean, just to get the context of what the problem is in Eden, it takes more than two storyboards.
166 00:16:47.380 ⇒ 00:16:48.190 Awaish Kumar: Right. Okay.
167 00:16:48.190 ⇒ 00:16:49.850 Ashwini Sharma: So, yeah, I mean.
168 00:16:49.850 ⇒ 00:17:00.969 Awaish Kumar: Not for everything, but I agree with, like, if there is a net new model, then yes, I agree with you. Yeah, we need time to understand the exact.
169 00:17:01.270 ⇒ 00:17:10.680 Ashwini Sharma: Not this net new model, the recent thing, right? The CIO, the reverse ETL into CIO segment, throwing data into CIO, and then…
170 00:17:10.829 ⇒ 00:17:19.750 Ashwini Sharma: me going into CIO, figuring out what the heck is going on over there, right? I mean, it might seem like a very small change, right?
171 00:17:20.050 ⇒ 00:17:25.819 Ashwini Sharma: But just to figure out what is happening, it took me almost, like, you know, 2-3 hours.
172 00:17:26.960 ⇒ 00:17:27.599 Ashwini Sharma: So…
173 00:17:27.609 ⇒ 00:17:33.149 Awaish Kumar: Like, for that, we have a process. You need to meet with the team. Like, you don’t have.
174 00:17:33.150 ⇒ 00:17:42.970 Ashwini Sharma: No, I did that. See, getting access to this thing, system, going to the system, figuring out what is going on over there, how data is going from this
175 00:17:43.330 ⇒ 00:17:44.930 Ashwini Sharma: Actually, yeah.
176 00:17:45.390 ⇒ 00:17:53.430 Awaish Kumar: If you ask Zoran, he can exactly show you what’s going on in CIO.
177 00:17:53.710 ⇒ 00:17:57.100 Awaish Kumar: Like, he is a CIO person.
178 00:17:57.260 ⇒ 00:18:00.529 Awaish Kumar: Right. He can show you these are the different…
179 00:18:00.790 ⇒ 00:18:07.880 Awaish Kumar: models through which, where this field is. In, like, we already named in, in the…
180 00:18:08.350 ⇒ 00:18:11.259 Awaish Kumar: chat that what model, DVD models we use.
181 00:18:11.540 ⇒ 00:18:13.790 Awaish Kumar: Number 3, how data is moving?
182 00:18:14.060 ⇒ 00:18:19.660 Awaish Kumar: That’s in segment. But I agree, like, it might not be 2 hours, it can be 3 hours.
183 00:18:19.790 ⇒ 00:18:26.170 Awaish Kumar: But I don’t agree that… You spend the whole day just doing that.
184 00:18:26.510 ⇒ 00:18:33.400 Awaish Kumar: Right? So… I agree, like, when you’re new, things take time.
185 00:18:33.580 ⇒ 00:18:49.730 Awaish Kumar: It can be… it can ex… extend, like, maybe from 2, you can go to 3, maybe 4, but… because that’s your first ticket, you can tell that, like, it was my first ticket, I needed to get some contacts, I need 2 more hours. That’s… that’s okay, completely okay, right?
186 00:18:50.010 ⇒ 00:18:55.279 Awaish Kumar: But, like, you have to tell him, right, in the meeting, in your stand-up.
187 00:19:05.150 ⇒ 00:19:14.530 Awaish Kumar: Or… or you can update it, the story points, and then… and let him know that, like, it took you more… more… more time than usual, but yeah.
188 00:19:15.880 ⇒ 00:19:20.300 Awaish Kumar: But that should be,
189 00:19:21.900 ⇒ 00:19:28.040 Awaish Kumar: like, if I can do something in 2 hours, I can say, somebody who’s new, maybe take 4.
190 00:19:28.660 ⇒ 00:19:34.219 Awaish Kumar: But, like, get time with the team.
191 00:19:34.630 ⇒ 00:19:37.529 Awaish Kumar: That’s one of the things I would suggest.
192 00:19:38.000 ⇒ 00:19:44.790 Awaish Kumar: And, yeah, and everything can’t be done in 2 hours, I agree with that.
193 00:19:45.050 ⇒ 00:19:46.760 Awaish Kumar: But, yeah, we should…
194 00:19:47.730 ⇒ 00:19:58.340 Awaish Kumar: And second thing, you just have to be open… openly, you can just say, Robert, like, how much time it’s going to take, that’s all.
195 00:20:02.220 ⇒ 00:20:03.240 Awaish Kumar: Okay.
196 00:20:03.240 ⇒ 00:20:09.820 Ashwini Sharma: Yeah, no, no, okay, let’s take a look at one particular example, right? Something that has come up.
197 00:20:10.720 ⇒ 00:20:13.990 Awaish Kumar: I’m just telling you the measures we can take here.
198 00:20:14.410 ⇒ 00:20:15.360 Awaish Kumar: like…
199 00:20:16.290 ⇒ 00:20:33.140 Awaish Kumar: Obviously, if you have 10 hours, like, for example, if we say, you are spending 20 on Magic Spoon, 20 on CTA. Let’s say I’m taking on, some, some tickets on CTA, and we split between us, like, 10, 10.
200 00:20:33.380 ⇒ 00:20:34.220 Awaish Kumar: Okay.
201 00:20:34.530 ⇒ 00:20:38.959 Awaish Kumar: Now, if I assign you on Eden, let’s say,
202 00:20:39.730 ⇒ 00:20:49.219 Awaish Kumar: you have identified two tickets, which are going to take you time, you can work on that, and then you can tell Robert, like, this… this is what I’ve worked on. That’s…
203 00:20:52.150 ⇒ 00:20:53.960 Awaish Kumar: And that’s how it’s going to work.
204 00:20:56.660 ⇒ 00:21:00.310 Ashwini Sharma: Okay, now, let’s take a look at this one, right?
205 00:21:00.420 ⇒ 00:21:03.089 Ashwini Sharma: This is new work that has come up, okay?
206 00:21:03.520 ⇒ 00:21:05.740 Ashwini Sharma: no.
207 00:21:05.870 ⇒ 00:21:12.400 Awaish Kumar: If you listen to stand up, Like,
208 00:21:14.150 ⇒ 00:21:20.720 Awaish Kumar: Actually, maybe you know, like, there’s Zoran was saying that we don’t need this ticket, I don’t know…
209 00:21:20.990 ⇒ 00:21:29.450 Awaish Kumar: Maybe it’s, it’s not even needed, right? We already have this thing in the… And the CIO.
210 00:21:29.730 ⇒ 00:21:34.189 Awaish Kumar: Right? So he mentioned him on Monday’s stand-up, that thing.
211 00:21:36.810 ⇒ 00:21:42.850 Ashwini Sharma: Yeah, he said that. He said that in Monday’s stand-up, but again, today, this guy, Gregory, came up.
212 00:21:43.020 ⇒ 00:21:44.730 Ashwini Sharma: The customer has nudged them.
213 00:21:44.840 ⇒ 00:21:47.820 Ashwini Sharma: planned as NASDAM regarding this particular ticket.
214 00:21:49.540 ⇒ 00:21:53.439 Awaish Kumar: But, like, that’s… that’s… I don’t know, that’s, like…
215 00:21:53.550 ⇒ 00:21:56.959 Awaish Kumar: Who’s… who’s asking for that, Greg? Greg is not a…
216 00:21:57.370 ⇒ 00:22:01.830 Awaish Kumar: Like, who has created this ticket? Like, Greg is not a CSO.
217 00:22:02.160 ⇒ 00:22:03.649 Ashwini Sharma: Greg has created it.
218 00:22:03.650 ⇒ 00:22:11.990 Awaish Kumar: I’m not sure how it ended up here, and, like, who’s the EP on this? Who is, who is basically…
219 00:22:12.520 ⇒ 00:22:18.120 Awaish Kumar: Like, that flow is not working when you do that, yeah, so… I don’t know, like,
220 00:22:18.460 ⇒ 00:22:23.609 Awaish Kumar: if, like, if Greg says, customer is asking, then was Zozo around there?
221 00:22:23.970 ⇒ 00:22:29.440 Awaish Kumar: like, did… Did anybody clear, like… Why this is…
222 00:22:29.760 ⇒ 00:22:35.499 Awaish Kumar: like, between Zoran, between Greg and you, did you identify, like.
223 00:22:35.680 ⇒ 00:22:42.760 Awaish Kumar: Do we already have this data in CIO, or do we really need to work on it? Like, what’s the status?
224 00:22:45.080 ⇒ 00:22:50.119 Ashwini Sharma: Well, yeah, that’s what I don’t know, like, see, I’m not talking to the customer in this case, right?
225 00:22:50.120 ⇒ 00:22:54.920 Awaish Kumar: Hold on, but you have to talk to Zoran and Greg, like.
226 00:22:55.570 ⇒ 00:22:58.479 Awaish Kumar: Put them all in one call and ask, like.
227 00:22:58.640 ⇒ 00:23:07.529 Awaish Kumar: like, tell Zorang, like, whatever you are saying, show us that, and ask Greg, like, that’s what you need, or if you need something else, because…
228 00:23:08.840 ⇒ 00:23:14.829 Awaish Kumar: That’s how it’s going to clear up, otherwise you are just going to write message, somebody else will write some message, and that’s…
229 00:23:14.830 ⇒ 00:23:23.529 Ashwini Sharma: No, that’s fine, okay, no, like, okay, let’s say, you know, I’m just taking as a hypothetical example, right? For example, let’s say we have to implement this thing.
230 00:23:25.530 ⇒ 00:23:27.110 Ashwini Sharma: Yeah, that’s the…
231 00:23:27.110 ⇒ 00:23:33.280 Awaish Kumar: first step, that’s what I’m saying, even if it’s something you have to implement, You’ll have to meet with…
232 00:23:33.800 ⇒ 00:23:34.500 Awaish Kumar: No, no.
233 00:23:34.500 ⇒ 00:23:38.549 Ashwini Sharma: That I’ll meet. What I’m asking you is something different, right?
234 00:23:38.720 ⇒ 00:23:48.610 Ashwini Sharma: Now, let’s say if I have to implement this, right, based on whatever context you have, and based on whatever requirement is there, what do you think this would take?
235 00:24:00.310 ⇒ 00:24:04.089 Awaish Kumar: Okay, so… Like, number one thing.
236 00:24:04.360 ⇒ 00:24:12.220 Awaish Kumar: he needs a field in CIO. That field is going from a model, customer image profile. What I need…
237 00:24:12.470 ⇒ 00:24:21.690 Awaish Kumar: this data, like, if I… a user begins in tech, users log in, user… like, do I have this data in first… first…
238 00:24:21.880 ⇒ 00:24:23.519 Awaish Kumar: First, like, my thought.
239 00:24:23.890 ⇒ 00:24:28.130 Awaish Kumar: Do you have intake data in, in,
240 00:24:29.510 ⇒ 00:24:32.280 Awaish Kumar: In… coming from Basque? I don’t think so.
241 00:24:33.310 ⇒ 00:24:34.680 Awaish Kumar: Like, when I do that.
242 00:24:34.680 ⇒ 00:24:36.130 Ashwini Sharma: It’s not there.
243 00:24:36.130 ⇒ 00:24:39.289 Awaish Kumar: There’s no data on that. I can’t do that, then, like…
244 00:24:43.880 ⇒ 00:24:47.510 Awaish Kumar: Right? My thought process is, like.
245 00:24:47.660 ⇒ 00:24:50.080 Awaish Kumar: Where is my raw data? Where is my…
246 00:24:51.470 ⇒ 00:24:59.400 Awaish Kumar: What is the process, like, the tools that… that needs to be used? Like, user pick and syntax, okay, the intake data.
247 00:24:59.790 ⇒ 00:25:03.720 Awaish Kumar: Do I have it somewhere? I don’t know, like, I can’t recall it.
248 00:25:08.480 ⇒ 00:25:15.650 Awaish Kumar: I don’t know, like, even if there is some data on ATEX in… and victory.
249 00:25:22.220 ⇒ 00:25:23.690 Awaish Kumar: Yeah, so…
250 00:25:23.860 ⇒ 00:25:30.819 Awaish Kumar: if there is… there is some ways to do that, then I will identify that, and that can happen with Zoran, because
251 00:25:30.970 ⇒ 00:25:35.729 Awaish Kumar: Basque is a platform from which we are getting some data in our warehouse.
252 00:25:36.600 ⇒ 00:25:38.379 Awaish Kumar: But maybe there is not…
253 00:25:38.640 ⇒ 00:25:42.820 Awaish Kumar: There’s no data on in-text. Maybe we have to then ask,
254 00:25:43.030 ⇒ 00:25:51.000 Awaish Kumar: Zoran, like, where this intake data is coming from, or ask similar data, because I can’t recall having it somewhere.
255 00:25:51.710 ⇒ 00:26:03.010 Awaish Kumar: Then I’m gonna just ask them, like, in the channel here, hi everyone, I’m looking for this data. I couldn’t find it anywhere. Let’s… does anybody have any information on that?
256 00:26:03.180 ⇒ 00:26:07.029 Awaish Kumar: Okay, like… And then, based on that.
257 00:26:10.010 ⇒ 00:26:18.649 Awaish Kumar: it will, like, if I have to then make… if, for example, assume data is there, then this is a really simple model, like, the SQL change.
258 00:26:18.870 ⇒ 00:26:19.690 Awaish Kumar: Right?
259 00:26:20.250 ⇒ 00:26:30.909 Awaish Kumar: And then, if you know things, right? Yeah, I understand that knowing it for first time will take you some time than me. I can do it in maybe…
260 00:26:34.090 ⇒ 00:26:35.680 Awaish Kumar: And, like…
261 00:26:36.300 ⇒ 00:26:48.750 Awaish Kumar: At max 2 hours, because one… it will take 1 hour for me to implement, but I will take one more hour for maybe, you can say, validation, and seeing if it actually ends up in CIO.
262 00:26:49.570 ⇒ 00:26:53.340 Awaish Kumar: Right? But to figure out, to ask Demiladi, to…
263 00:26:53.780 ⇒ 00:26:57.430 Awaish Kumar: Look at… maybe do some searches in BigQuery.
264 00:26:57.710 ⇒ 00:27:01.529 Awaish Kumar: Maybe you have to, spend 2 more hours.
265 00:27:02.330 ⇒ 00:27:03.240 Awaish Kumar: Tonight.
266 00:27:04.700 ⇒ 00:27:07.810 Awaish Kumar: But that’s, like, that’s what it should take.
267 00:27:11.680 ⇒ 00:27:16.369 Awaish Kumar: like, because, yeah, because that’s… that’s, like, first time you’re going to CIO,
268 00:27:16.760 ⇒ 00:27:22.340 Awaish Kumar: First time, you will be looking at the… The model.
269 00:27:22.450 ⇒ 00:27:24.889 Awaish Kumar: That’s… yeah.
270 00:27:26.030 ⇒ 00:27:39.680 Awaish Kumar: And then you have to do some… you have to do some skimming, right? Like, you can’t go in and, like, maybe log into segment and look at all the pipelines which are there. If you do that, obviously, you won’t finish.
271 00:27:39.860 ⇒ 00:27:41.200 Awaish Kumar: Hit it on time.
272 00:27:41.370 ⇒ 00:27:51.299 Awaish Kumar: So, yeah, maybe going straight to, okay, where is the CIO? Where is… if somebody can point to that, that would be really nice, like, just meet with
273 00:27:52.100 ⇒ 00:27:56.359 Awaish Kumar: Demi, okay, yeah, or me, or, like, where is this data going from?
274 00:27:57.750 ⇒ 00:28:02.470 Awaish Kumar: like, in sync with how’s that syncing? I can show you the exact…
275 00:28:03.060 ⇒ 00:28:06.510 Awaish Kumar: Pipeline, and that’s… it’s all, right?
276 00:28:06.770 ⇒ 00:28:10.710 Awaish Kumar: And maybe that took 30 minutes for you to learn it, so…
277 00:28:11.060 ⇒ 00:28:15.949 Awaish Kumar: Which might have taken maybe an hour, if you have done it yourself.
278 00:28:21.620 ⇒ 00:28:30.369 Awaish Kumar: Yeah, and yeah, but I… I understand, like, when there is a neat new model, which… or in need, it can take some time, because
279 00:28:30.710 ⇒ 00:28:36.940 Awaish Kumar: Those are really, Sometimes those are really big and complex, and…
280 00:28:37.690 ⇒ 00:28:46.889 Awaish Kumar: if you can see the tickets for new models, you can see how much information is there. Just reading that will take you one hour.
281 00:28:52.100 ⇒ 00:28:55.899 Ashwini Sharma: Yeah, that’s alright. Eden has a lot of context behind it, and…
282 00:29:01.340 ⇒ 00:29:04.390 Awaish Kumar: Yeah, so that’s… There’s that.
283 00:29:04.500 ⇒ 00:29:05.310 Awaish Kumar: Okay.
284 00:29:05.890 ⇒ 00:29:13.310 Awaish Kumar: So for this, yeah, if you want to ask anything for this ticket, then… .
285 00:29:14.360 ⇒ 00:29:17.880 Ashwini Sharma: Yeah, I’ll check with Zoran and Demilhardi on this one.
286 00:29:18.240 ⇒ 00:29:20.820 Awaish Kumar: There’s no intent data, I assume.
287 00:29:21.180 ⇒ 00:29:28.669 Awaish Kumar: At least in, basque. So, either Zoran’s edge layer thing.
288 00:29:29.740 ⇒ 00:29:37.010 Awaish Kumar: is maybe bringing some information on where the user begins syntact. So, ask him, like, because he has some…
289 00:29:37.250 ⇒ 00:29:40.420 Awaish Kumar: Like, he’s capturing all the events for each user.
290 00:29:40.580 ⇒ 00:29:42.619 Awaish Kumar: So we might have, somewhere.
291 00:29:42.990 ⇒ 00:29:45.780 Awaish Kumar: Some way to identify which are intake pages.
292 00:29:46.010 ⇒ 00:29:50.590 Awaish Kumar: And you can see, We started, and we will finish the intake.
293 00:29:50.750 ⇒ 00:29:54.160 Awaish Kumar: And through that edge layer data, we might be able to get this
294 00:29:54.620 ⇒ 00:30:01.349 Awaish Kumar: Field in, and then you have to join it and put it in, maybe, customer enriched profile table.
295 00:30:11.020 ⇒ 00:30:12.259 Awaish Kumar: Anything else?
296 00:30:13.030 ⇒ 00:30:15.350 Ashwini Sharma: No, this is fine, I think, I think,
297 00:30:17.450 ⇒ 00:30:19.689 Ashwini Sharma: I’ll talk to Zoran more on this.
298 00:30:20.310 ⇒ 00:30:25.620 Ashwini Sharma: And figure out, like, how it needs to be done, or if it needs to be done.
299 00:30:28.170 ⇒ 00:30:29.420 Awaish Kumar: But he said, like.
300 00:30:31.800 ⇒ 00:30:42.949 Ashwini Sharma: No, you’re saying this one, and probably this was already communicated to the customer, that’s what Greg said, right? And then still they gave a nudge on to him, you know, asking the status on this ticket.
301 00:30:46.090 ⇒ 00:30:52.749 Awaish Kumar: Okay, so, like, I think there’s just confusion.
302 00:30:53.240 ⇒ 00:31:00.840 Awaish Kumar: So everybody is confused. From the messages, I can read it. Nobody’s aligned on what they are talking about.
303 00:31:01.100 ⇒ 00:31:07.730 Awaish Kumar: Zoran is saying… Jodi’s already identifying that. Then Greg says, I need it in CIO.
304 00:31:08.510 ⇒ 00:31:11.270 Awaish Kumar: Okay, like, you need it in CIO, but…
305 00:31:11.910 ⇒ 00:31:23.079 Awaish Kumar: where is that data? Like, if Zoran is asking, like… like, Jude is identifying through something, is that data in BigQuery somewhere? If there is, where is that?
306 00:31:23.460 ⇒ 00:31:25.390 Awaish Kumar: Just use that, like…
307 00:31:25.680 ⇒ 00:31:32.980 Awaish Kumar: this ticket, all these comments, like, Greg says they want to use this data, and CIO is starting now.
308 00:31:33.120 ⇒ 00:31:50.589 Awaish Kumar: Like, Jude was maybe identifying it using MagicLink, and then he’s trying to maybe do it in BigQuery. He now just needs in CIO. Okay, if he’s already doing it in BigQuery, then just let us know what query he’s using to identify, right?
309 00:31:50.770 ⇒ 00:31:55.230 Awaish Kumar: Using that query, you can also identify, and then you can put that data into
310 00:31:55.940 ⇒ 00:32:01.620 Awaish Kumar: in CIO, right? Using a flag or whatever. So that’s all, right?
311 00:32:01.880 ⇒ 00:32:05.970 Awaish Kumar: Everybody’s just talking different things, that’s all the confusion here.
312 00:32:11.130 ⇒ 00:32:16.060 Awaish Kumar: So, like, like, Greg Zoran needs to be in the same room, basically.
313 00:32:17.610 ⇒ 00:32:20.740 Ashwini Sharma: Yeah, I’ll get them same… the same room, and then discuss it out.
314 00:32:21.360 ⇒ 00:32:21.960 Awaish Kumar: Yeah.
315 00:32:41.280 ⇒ 00:32:45.879 Awaish Kumar: Okay, there were… there was one more ticket here, I think, assigned to you.
316 00:32:47.250 ⇒ 00:32:52.170 Ashwini Sharma: Yeah, yeah, the other ticket was mainly around this one.
317 00:32:53.350 ⇒ 00:32:55.749 Ashwini Sharma: Prefer client review.
318 00:32:55.920 ⇒ 00:33:06.560 Ashwini Sharma: This was… Yeah, so this is, basically, it was going over to, customer I.O.
319 00:33:06.670 ⇒ 00:33:07.949 Ashwini Sharma: to segment.
320 00:33:08.300 ⇒ 00:33:10.150 Awaish Kumar: How is Greg is playing here, like…
321 00:33:14.080 ⇒ 00:33:16.440 Awaish Kumar: I think Greg is kind of replacing…
322 00:33:17.120 ⇒ 00:33:18.040 Ashwini Sharma: Henry.
323 00:33:18.040 ⇒ 00:33:22.960 Awaish Kumar: Henry, and… He’s the one who should… Also…
324 00:33:23.850 ⇒ 00:33:28.499 Awaish Kumar: Take the, like, the engagement with the client, so we…
325 00:33:28.980 ⇒ 00:33:35.490 Awaish Kumar: He’s maybe also new to the… he’s also new, not maybe, but he’s also new to the client, so…
326 00:33:35.710 ⇒ 00:33:38.139 Awaish Kumar: That’s why, maybe, this is the…
327 00:33:39.050 ⇒ 00:33:45.320 Awaish Kumar: That’s the confusion, because, like, Eshoni, you are new, And he’s new, as well.
328 00:33:46.830 ⇒ 00:33:47.950 Awaish Kumar: On this slide.
329 00:34:02.080 ⇒ 00:34:05.930 Ashwini Sharma: I use this one.
330 00:34:10.150 ⇒ 00:34:12.420 Ashwini Sharma: Right… over here.
331 00:34:23.420 ⇒ 00:34:25.519 Awaish Kumar: No, no, so what’s happening? I don’t know.
332 00:34:25.870 ⇒ 00:34:28.739 Ashwini Sharma: Yeah, I’m just showing you over here.
333 00:34:29.190 ⇒ 00:34:34.530 Ashwini Sharma: So basically, this guy is expecting the data in a certain format, right?
334 00:34:34.920 ⇒ 00:34:37.420 Ashwini Sharma: And if we see the mapping over here.
335 00:34:38.650 ⇒ 00:34:46.430 Ashwini Sharma: Now, what it does is it takes the DOB in the table, BigQuery, and then assigns it to birthdate, right?
336 00:34:46.469 ⇒ 00:34:48.529 Awaish Kumar: You know, something is happening over here.
337 00:34:48.630 ⇒ 00:34:55.000 Ashwini Sharma: DOB is going into Customer I.O. as DOB only.
338 00:34:56.020 ⇒ 00:34:57.150 Awaish Kumar: Scroll down.
339 00:34:58.120 ⇒ 00:34:59.170 Ashwini Sharma: Customer.io.
340 00:34:59.170 ⇒ 00:35:00.410 Awaish Kumar: Yeah, go on.
341 00:35:00.410 ⇒ 00:35:01.160 Ashwini Sharma: again.
342 00:35:02.690 ⇒ 00:35:03.840 Ashwini Sharma: Yeah, that’s…
343 00:35:03.840 ⇒ 00:35:07.350 Awaish Kumar: Just scroll down. Just scroll down again.
344 00:35:07.790 ⇒ 00:35:08.560 Ashwini Sharma: Mordon?
345 00:35:09.440 ⇒ 00:35:10.440 Ashwini Sharma: Fuck yeah.
346 00:35:10.470 ⇒ 00:35:14.110 Awaish Kumar: Look at this data. This is simple. Now look at DUB.
347 00:35:15.090 ⇒ 00:35:21.670 Awaish Kumar: Where is DOB? Yeah. See? It has changed. This is how it is… Looking.
348 00:35:22.490 ⇒ 00:35:27.509 Awaish Kumar: If you go… scroll up a little bit… And select a different record.
349 00:35:27.750 ⇒ 00:35:29.350 Awaish Kumar: Scroll up a little bit.
350 00:35:29.850 ⇒ 00:35:31.190 Awaish Kumar: And from here.
351 00:35:31.400 ⇒ 00:35:35.159 Awaish Kumar: Yeah, you can change some other ID, right? Now…
352 00:35:36.620 ⇒ 00:35:40.710 Awaish Kumar: So this is… this is how the data is going to be in CIO.
353 00:35:41.260 ⇒ 00:35:44.420 Awaish Kumar: So this is the different farming. What farmer does he need?
354 00:35:44.680 ⇒ 00:35:45.660 Awaish Kumar: No, this…
355 00:35:45.660 ⇒ 00:35:52.510 Ashwini Sharma: this is what? This is… this is sending a test record, right? So, basically, like, you’re sending this record to CIO, right?
356 00:35:54.330 ⇒ 00:36:07.810 Awaish Kumar: We didn’t set, right? Right now, what we did, we just selected a record, and we are just seeing how it will look like if we send it in CIO. If you scroll down a little bit more, you will see a button to send it, actually.
357 00:36:07.810 ⇒ 00:36:12.409 Ashwini Sharma: Yeah, right. So, so you see, the DOB is in this format, okay?
358 00:36:12.650 ⇒ 00:36:13.650 Awaish Kumar: That’s what I’m saying.
359 00:36:13.850 ⇒ 00:36:15.960 Ashwini Sharma: Yeah. No.
360 00:36:17.110 ⇒ 00:36:18.530 Ashwini Sharma: Over here…
361 00:36:18.880 ⇒ 00:36:24.210 Awaish Kumar: But is it ending up in the same format in CustomIO, or is it still changed?
362 00:36:24.210 ⇒ 00:36:28.769 Ashwini Sharma: Customer I.O, this has, am I logged in?
363 00:36:30.080 ⇒ 00:36:32.550 Ashwini Sharma: Let’s take a look at this one.
364 00:36:33.720 ⇒ 00:36:41.689 Ashwini Sharma: So the DOB field in Customer I.O. has a proper listing, see? All the… if… either it is null, or it is there.
365 00:36:42.050 ⇒ 00:36:42.700 Awaish Kumar: Okay.
366 00:36:43.110 ⇒ 00:36:46.400 Ashwini Sharma: Right? But this is the one that… that is.
367 00:36:46.780 ⇒ 00:36:47.730 Awaish Kumar: Should be used.
368 00:36:47.730 ⇒ 00:36:54.279 Ashwini Sharma: Yeah, this should be used, but the guy, Jude, he does not want to use this, and he wants to use.
369 00:36:54.280 ⇒ 00:36:55.440 Awaish Kumar: Anything else.
370 00:36:56.330 ⇒ 00:36:57.360 Awaish Kumar: Okay.
371 00:36:57.360 ⇒ 00:36:59.430 Ashwini Sharma: Yeah, he wants to use… oh, sorry.
372 00:36:59.860 ⇒ 00:37:01.289 Ashwini Sharma: Birth date here.
373 00:37:02.230 ⇒ 00:37:04.780 Awaish Kumar: Okay, but if you go back to…
374 00:37:05.340 ⇒ 00:37:08.279 Ashwini Sharma: This is what he wants to use, right?
375 00:37:08.410 ⇒ 00:37:14.589 Awaish Kumar: Now, the birthdate is in multiple different formats. It is in this format, it is in this format.
376 00:37:14.600 ⇒ 00:37:17.290 Ashwini Sharma: And it is in the regular, this thing format.
377 00:37:17.850 ⇒ 00:37:21.189 Awaish Kumar: Where is this coming from? Like, can we go back to segment?
378 00:37:23.960 ⇒ 00:37:24.530 Ashwini Sharma: Yep.
379 00:37:25.410 ⇒ 00:37:26.160 Ashwini Sharma: I do so.
380 00:37:26.520 ⇒ 00:37:27.300 Awaish Kumar: Indeed.
381 00:37:27.680 ⇒ 00:37:29.029 Ashwini Sharma: Bird date is over here.
382 00:37:31.460 ⇒ 00:37:34.070 Awaish Kumar: TOB, going through birthdate, but that’s not…
383 00:37:34.360 ⇒ 00:37:36.690 Awaish Kumar: How? That’s not happening right now.
384 00:37:41.430 ⇒ 00:37:44.960 Awaish Kumar: our DOV is not the same as birth rating.
385 00:37:45.580 ⇒ 00:37:46.729 Awaish Kumar: Good CRU.
386 00:37:47.160 ⇒ 00:37:50.540 Ashwini Sharma: Yeah, it’s not happening. So DOB is going to DOB only.
387 00:37:50.680 ⇒ 00:37:52.799 Ashwini Sharma: It’s not going to birthdate.
388 00:37:53.890 ⇒ 00:37:56.080 Awaish Kumar: That’s why I’m flicking, why…
389 00:37:56.550 ⇒ 00:38:03.560 Awaish Kumar: But is it… okay. Is it going from here, or there are different other models?
390 00:38:03.670 ⇒ 00:38:05.930 Awaish Kumar: Which are also selling data to CIO.
391 00:38:09.600 ⇒ 00:38:11.700 Awaish Kumar: Yeah, if you go back to… sorry.
392 00:38:13.290 ⇒ 00:38:15.880 Ashwini Sharma: They are not updating people.
393 00:38:16.180 ⇒ 00:38:17.310 Awaish Kumar: Okay, okay.
394 00:38:19.300 ⇒ 00:38:20.849 Awaish Kumar: Are we okay?
395 00:38:21.110 ⇒ 00:38:22.120 Ashwini Sharma: alerted at all.
396 00:38:22.660 ⇒ 00:38:25.260 Ashwini Sharma: I think that was the only one that was updating people.
397 00:38:36.940 ⇒ 00:38:37.550 Awaish Kumar: Okay.
398 00:38:37.550 ⇒ 00:38:40.400 Ashwini Sharma: Okay, I think I have to go over here, one more back.
399 00:38:47.670 ⇒ 00:38:56.140 Ashwini Sharma: So these are not exactly… I mean, it says create or update person, they are not updating that way, right? It’s totally different fields.
400 00:38:56.890 ⇒ 00:39:00.670 Awaish Kumar: Okay, let’s… let’s open the Zesk one, what… what you say is.
401 00:39:12.840 ⇒ 00:39:15.039 Awaish Kumar: Okay, scrolling down…
402 00:39:19.140 ⇒ 00:39:23.179 Awaish Kumar: Okay… Okay, Senior 8.
403 00:39:25.120 ⇒ 00:39:28.180 Ashwini Sharma: It’s not operating DOB or birthdate or anything.
404 00:39:29.110 ⇒ 00:39:30.260 Awaish Kumar: Oh, yeah.
405 00:39:36.440 ⇒ 00:39:37.909 Ashwini Sharma: Did you follow up?
406 00:39:38.500 ⇒ 00:39:39.030 Ashwini Sharma: Yeah?
407 00:39:39.450 ⇒ 00:39:41.120 Awaish Kumar: It’s not updating the…
408 00:39:41.240 ⇒ 00:39:48.639 Awaish Kumar: the DOB field, but it is how it’s… how it is going to work, like, it is going to add a new role in CIO.
409 00:39:49.380 ⇒ 00:39:52.309 Awaish Kumar: Or is it going to update the…
410 00:39:52.720 ⇒ 00:39:57.109 Awaish Kumar: fields for that customer ID, like, how is that working? Do you know?
411 00:39:59.730 ⇒ 00:40:05.019 Ashwini Sharma: No, it updates only what fields it’s supposed to update, right?
412 00:40:05.130 ⇒ 00:40:06.610 Awaish Kumar: So, basically, it…
413 00:40:06.630 ⇒ 00:40:12.019 Ashwini Sharma: Let’s look at this one, we’re just testing…
414 00:40:17.260 ⇒ 00:40:18.779 Ashwini Sharma: It should be in the models.
415 00:40:20.150 ⇒ 00:40:21.629 Ashwini Sharma: But this is the model.
416 00:40:23.080 ⇒ 00:40:25.970 Awaish Kumar: Yes, like, we already sold this one.
417 00:40:27.020 ⇒ 00:40:32.249 Ashwini Sharma: Yeah, yeah, I’m trying to go inside that model and then show you what exactly it is doing.
418 00:40:32.900 ⇒ 00:40:33.900 Ashwini Sharma: This one.
419 00:40:36.120 ⇒ 00:40:42.249 Ashwini Sharma: Query Builder, yeah, so it picks up… Certain records, right?
420 00:40:42.710 ⇒ 00:40:48.479 Ashwini Sharma: Customer ID, and the minimum of days since it is closed. These are the two values that it is getting from the warehouse.
421 00:40:48.700 ⇒ 00:40:54.080 Awaish Kumar: Yeah, I… I… saw that. I’m… I was just asking, like,
422 00:40:55.290 ⇒ 00:41:01.690 Awaish Kumar: how it will work in CIO. It will just, for that customer ID, it will just going to update this one.
423 00:41:01.870 ⇒ 00:41:04.170 Ashwini Sharma: Yeah, only for that customer ID, right?
424 00:41:17.760 ⇒ 00:41:22.409 Ashwini Sharma: So, yeah, take this customer ID, and then update this property for the customer ID.
425 00:41:24.100 ⇒ 00:41:24.800 Awaish Kumar: Okay.
426 00:41:29.070 ⇒ 00:41:33.859 Awaish Kumar: So yeah, like, let’s… like, let’s do this check.
427 00:41:34.250 ⇒ 00:41:35.330 Awaish Kumar: Fuhrer.
428 00:41:35.600 ⇒ 00:41:37.960 Awaish Kumar: all the CIO connections, if…
429 00:41:38.390 ⇒ 00:41:45.610 Awaish Kumar: there is any birthdate kind of thing. Like, we need to identify where this birthdate is coming from.
430 00:41:46.210 ⇒ 00:41:50.040 Awaish Kumar: I, like, from… from BigQuery, or…
431 00:41:50.990 ⇒ 00:41:54.750 Awaish Kumar: from somewhere else, or how is… how that is working? I don’t know.
432 00:41:56.640 ⇒ 00:42:05.220 Awaish Kumar: Like, if there is something… Some other, like… Okay.
433 00:42:07.030 ⇒ 00:42:14.429 Ashwini Sharma: data, for example. I don’t know if there is some data coming from GF4 or directly to CIO, or whatever.
434 00:42:14.880 ⇒ 00:42:21.390 Awaish Kumar: So, I don’t know that. So, we just need to… for these CIO connections, maybe just have one…
435 00:42:21.710 ⇒ 00:42:25.649 Awaish Kumar: One pass over them to just see the mapping.
436 00:42:26.000 ⇒ 00:42:28.880 Awaish Kumar: Is… is any of the connection is sending?
437 00:42:29.560 ⇒ 00:42:30.870 Awaish Kumar: His birthdate.
438 00:42:35.560 ⇒ 00:42:37.800 Ashwini Sharma: Do you feel that something is overriding budget?
439 00:42:39.280 ⇒ 00:42:44.290 Awaish Kumar: I’m… yeah, that’s what I’m feeling, that that is being fed from somewhere.
440 00:42:46.140 ⇒ 00:42:48.420 Ashwini Sharma: This looks like disabled, right?
441 00:42:51.170 ⇒ 00:42:52.850 Awaish Kumar: Yeah, they’re disabled.
442 00:43:09.340 ⇒ 00:43:14.900 Ashwini Sharma: There are event stream, and then there are these, bundle.
443 00:43:18.520 ⇒ 00:43:20.110 Ashwini Sharma: University together.
444 00:43:22.480 ⇒ 00:43:25.050 Awaish Kumar: Yeah, only the River City TL we need to locate.
445 00:43:25.400 ⇒ 00:43:26.789 Ashwini Sharma: Not the event streams.
446 00:43:27.310 ⇒ 00:43:32.490 Awaish Kumar: Event streams… oh, okay, event streams are directly reading from Bask.
447 00:43:32.650 ⇒ 00:43:34.789 Awaish Kumar: I’m going to CIO, right?
448 00:43:34.790 ⇒ 00:43:35.990 Ashwini Sharma: Yeah.
449 00:43:36.690 ⇒ 00:43:40.730 Awaish Kumar: That… that… okay, that is also send… we’ll be sending some data away.
450 00:43:41.810 ⇒ 00:43:44.359 Awaish Kumar: Oh, you need… you should look for… yeah.
451 00:43:44.480 ⇒ 00:43:47.050 Awaish Kumar: Maybe look at Signed Up, for example.
452 00:43:47.460 ⇒ 00:43:49.719 Awaish Kumar: That will have some sign-up information.
453 00:43:51.760 ⇒ 00:43:55.119 Awaish Kumar: Like, it may have some birthright kind of thing, I don’t know.
454 00:43:57.100 ⇒ 00:43:59.009 Awaish Kumar: Coming directly from Basque.
455 00:44:03.400 ⇒ 00:44:06.789 Awaish Kumar: Okay, there’s no… yeah, there’s this person, last one.
456 00:44:07.200 ⇒ 00:44:09.310 Awaish Kumar: Create or update person there.
457 00:44:11.350 ⇒ 00:44:13.470 Awaish Kumar: Let me look at this mapping, yeah.
458 00:44:16.720 ⇒ 00:44:17.500 Awaish Kumar: What?
459 00:44:32.570 ⇒ 00:44:33.280 Awaish Kumar: Okay.
460 00:44:35.940 ⇒ 00:44:38.350 Awaish Kumar: Yeah, there’s personal attributes, right?
461 00:44:38.470 ⇒ 00:44:41.950 Awaish Kumar: You see traits going into personal attributes.
462 00:44:42.300 ⇒ 00:44:47.990 Awaish Kumar: This, 1, 2, 3, 4, 5, 6, row number 6.
463 00:44:52.090 ⇒ 00:44:52.960 Ashwini Sharma: This one?
464 00:44:54.830 ⇒ 00:44:58.989 Awaish Kumar: So, this is sending person attribute. I don’t know what is in trades now.
465 00:45:03.850 ⇒ 00:45:05.970 Ashwini Sharma: I also don’t know what’s over there.
466 00:45:07.790 ⇒ 00:45:10.249 Ashwini Sharma: But this is a webhook, I think. This is a webhook.
467 00:45:10.250 ⇒ 00:45:14.850 Awaish Kumar: I was just… This is reading data from a webhook.
468 00:45:15.000 ⇒ 00:45:19.950 Awaish Kumar: And then… Traits could be an error or something.
469 00:45:20.090 ⇒ 00:45:31.100 Awaish Kumar: Or, right, struct or something, which has multiple fields, and it is sending everything to personal attributes. It might have… this trades field might have birth rate.
470 00:45:31.390 ⇒ 00:45:32.499 Awaish Kumar: For a person.
471 00:45:33.000 ⇒ 00:45:35.569 Awaish Kumar: We need to identify what is in there.
472 00:45:37.270 ⇒ 00:45:38.800 Ashwini Sharma: Hey, you guys see…
473 00:45:38.800 ⇒ 00:45:48.980 Awaish Kumar: trades.email, right? So that trade has an email in it there, which is it is sending to CIO. Like, similarly, it may have birthdate.
474 00:45:51.880 ⇒ 00:45:54.509 Awaish Kumar: Hank, maybe… Click on this.
475 00:45:54.510 ⇒ 00:45:56.830 Ashwini Sharma: Added…
476 00:45:56.830 ⇒ 00:45:58.290 Awaish Kumar: Yeah, maybe look at the example.
477 00:45:58.290 ⇒ 00:45:59.029 Ashwini Sharma: Old Road.
478 00:45:59.030 ⇒ 00:46:01.030 Awaish Kumar: Is there any example below?
479 00:46:01.450 ⇒ 00:46:03.310 Awaish Kumar: Guest record or something?
480 00:46:04.760 ⇒ 00:46:07.739 Awaish Kumar: No test even selected, okay.
481 00:46:09.860 ⇒ 00:46:15.080 Awaish Kumar: Can we select on the… can we click on this scroll down arrow?
482 00:46:17.110 ⇒ 00:46:19.289 Awaish Kumar: On the same row number 6.
483 00:46:21.910 ⇒ 00:46:22.680 Ashwini Sharma: This one?
484 00:46:23.140 ⇒ 00:46:25.369 Awaish Kumar: Yeah, there is a little… there is this arrow.
485 00:46:26.610 ⇒ 00:46:33.300 Awaish Kumar: Yeah, can you kill… can you type, like… Traits? Like, find out traits.
486 00:46:33.660 ⇒ 00:46:39.990 Awaish Kumar: in the… Is it searchable? I don’t know.
487 00:46:43.570 ⇒ 00:46:49.800 Awaish Kumar: It’s not searchable. Okay, there’s… Let’s just scroll down quickly to see if there is a way…
488 00:46:50.600 ⇒ 00:46:52.339 Awaish Kumar: There’s nothing.
489 00:46:54.750 ⇒ 00:46:59.759 Ashwini Sharma: Same thing. I think maybe we should go to Basque and look at this webhook structure, right?
490 00:47:01.060 ⇒ 00:47:06.519 Awaish Kumar: I don’t have to… yeah, you can’t find it in Baa, you have to look at BigQuery, basically.
491 00:47:07.550 ⇒ 00:47:09.969 Awaish Kumar: Basically, have all the webhook data, right?
492 00:47:10.290 ⇒ 00:47:14.750 Awaish Kumar: Bigquery have the… Data coming from all these webhooks.
493 00:47:16.880 ⇒ 00:47:18.180 Awaish Kumar: Basque signed up.
494 00:47:18.700 ⇒ 00:47:19.710 Ashwini Sharma: Signed up…
495 00:47:35.200 ⇒ 00:47:37.749 Awaish Kumar: But the problem…
496 00:47:51.100 ⇒ 00:47:55.669 Awaish Kumar: I don’t know, now I’m not sure where it’s going in, either in signed up, or…
497 00:47:55.780 ⇒ 00:48:01.120 Awaish Kumar: Maybe it is going in, identifies table for person.
498 00:48:02.240 ⇒ 00:48:03.510 Ashwini Sharma: So begin tomorrow.
499 00:48:03.510 ⇒ 00:48:07.739 Awaish Kumar: It could end up… Yeah, in BigQuery, it might…
500 00:48:07.900 ⇒ 00:48:12.490 Awaish Kumar: End up in a different format than it is being shown in segment.
501 00:48:13.480 ⇒ 00:48:16.590 Ashwini Sharma: Yeah, that’s why I was thinking, like, why not go into Basque?
502 00:48:17.870 ⇒ 00:48:23.730 Ashwini Sharma: And then see… See the webhook structure?
503 00:48:26.890 ⇒ 00:48:29.190 Awaish Kumar: Okay, I don’t know if they have…
504 00:48:34.080 ⇒ 00:48:39.300 Awaish Kumar: Okay, I actually have to… Prepare file for next meeting.
505 00:48:39.300 ⇒ 00:48:43.320 Ashwini Sharma: Okay, alright, no issues. I’ll try to see if there is something that…
506 00:48:44.970 ⇒ 00:48:52.199 Awaish Kumar: Yeah, let’s see if there is anything… updating that. I’ve also made with Zoran, he can introduce.
507 00:48:52.470 ⇒ 00:48:56.670 Awaish Kumar: give you, you know, maybe a few… maybe thoughts on the CIU and stuff.
508 00:48:57.060 ⇒ 00:48:57.560 Awaish Kumar: Okay.
509 00:48:57.560 ⇒ 00:48:59.260 Ashwini Sharma: Yeah, okay, alright, man.
510 00:48:59.600 ⇒ 00:49:00.350 Ashwini Sharma: Thanks.