Meeting Title: US x BF | Grooming Date: 2025-07-30 Meeting participants: Emily Giant, Uttam Kumaran, Amber Lin
WEBVTT
1 00:00:11.150 ⇒ 00:00:12.160 Emily Giant: Hey!
2 00:00:22.620 ⇒ 00:00:23.960 Uttam Kumaran: Hello!
3 00:00:25.970 ⇒ 00:00:27.080 Emily Giant: How’s it going.
4 00:00:27.600 ⇒ 00:00:31.970 Uttam Kumaran: Good. I’m just trying to keep working on this issue.
5 00:00:35.030 ⇒ 00:00:37.130 Emily Giant: Oh, the the Kpi model.
6 00:00:37.130 ⇒ 00:00:38.550 Uttam Kumaran: Yeah.
7 00:00:38.550 ⇒ 00:00:41.360 Emily Giant: What’s the like? Tldr on that.
8 00:00:42.190 ⇒ 00:00:50.620 Uttam Kumaran: The Ldr is, there’s something happening between Kpi unified and Kpi orders that I’m just like, continue trying to like isolate.
9 00:00:52.130 ⇒ 00:00:55.780 Uttam Kumaran: I just keep getting pulled a couple of different directions. So I’m just like.
10 00:00:55.780 ⇒ 00:00:58.530 Emily Giant: It happens, it happens in our instance, like
11 00:00:59.260 ⇒ 00:01:13.999 Emily Giant: I went to fix something with products except and wound up rebuilding all of our legacy tables. With products. I’m still doing it like it’s like you pull one thread and the entire sweater just like falls apart. It’s.
12 00:01:14.000 ⇒ 00:01:19.779 Uttam Kumaran: Yeah. And there’s like there was a Dbt job failing. And I’m like, Well, I can’t. I don’t. I can’t like rule that out.
13 00:01:19.780 ⇒ 00:01:20.205 Emily Giant: Yeah.
14 00:01:20.630 ⇒ 00:01:23.220 Uttam Kumaran: So like, okay, fix that first.st And then
15 00:01:24.370 ⇒ 00:01:30.589 Uttam Kumaran: the next thing. Yeah, that’s it’s fine. I’m doing a lot of development work this week. So it’s actually.
16 00:01:30.590 ⇒ 00:01:33.479 Emily Giant: I’m sorry. I know that is not your.
17 00:01:33.640 ⇒ 00:01:35.049 Uttam Kumaran: No, no, it’s fine man.
18 00:01:35.050 ⇒ 00:01:35.790 Emily Giant: No.
19 00:01:35.790 ⇒ 00:01:40.690 Uttam Kumaran: I wanna do. I wanna do more especially for you guys. There’s a lot of stuff to do. So it’s.
20 00:01:41.130 ⇒ 00:01:49.720 Emily Giant: It’s very satisfying to clean up our instance, because it’s such a mess that when you do anything that makes something work, it’s like, oh, wow, yeah, I really did something this week. This is great.
21 00:01:49.720 ⇒ 00:01:50.360 Uttam Kumaran: Yes.
22 00:01:50.360 ⇒ 00:01:52.229 Emily Giant: But it is also like
23 00:01:52.900 ⇒ 00:02:01.730 Emily Giant: it is so hard to make a small pr, because it when you pull one thread like 50 other ones come undone, and you can’t like
24 00:02:02.460 ⇒ 00:02:15.509 Emily Giant: fix anything without fixing all of it so many times, and it just turns into like a snowball effect. But if there’s any I can like. Jump in and help you with. Let me know, because I’m happy that, like no one’s
25 00:02:15.640 ⇒ 00:02:29.670 Emily Giant: getting harmed right now from the work that I haven’t published. So I have like another couple of days before people start yelling at me and realize it’s broken so I can like divert. Where is everyone.
26 00:02:30.630 ⇒ 00:02:39.719 Uttam Kumaran: I think Kyle had a an appointment, so I think he may be out, and I think Amber is jumping between some stuff today, so she may be late.
27 00:02:40.530 ⇒ 00:02:44.610 Emily Giant: I mean. I’m happy to look at grooming stuff. I don’t.
28 00:02:45.490 ⇒ 00:02:54.319 Uttam Kumaran: Yeah, like, probably big focus for me, was just like getting the stuff from our Tdd like into tickets.
29 00:02:54.320 ⇒ 00:02:54.940 Emily Giant: Yeah, yeah.
30 00:02:55.280 ⇒ 00:02:57.320 Uttam Kumaran: Whatever we can get into tickets.
31 00:02:59.070 ⇒ 00:03:19.100 Emily Giant: Yeah, that makes sense. And I think that there’s a lot in there. So when I hopped on with Perry yesterday, when we had to reschedule like there’s no such thing as like me canceling a meeting with Perry. Well, like chat with me the whole 3 min like if it’s blocked off to hang out like we will chat. So we did. And like a lot of the stuff that I went through. I just was like, you know.
32 00:03:19.480 ⇒ 00:03:34.560 Emily Giant: since you’re gonna be the main stakeholder that we’re working with. Can we just look over this before the actual meeting, so that, like any surprises and so much of what is in there from the team yesterday already exists. It just needs to be like
33 00:03:35.140 ⇒ 00:04:01.549 Emily Giant: ironed out in places, so that it’s like easier to digest and looker or in the mart so that’s the good news with the marketing team is like. As we were going through their wish list we were like that exists that exists that exists. It just needs to be like cleaned up post migration. So I don’t think it’s gonna be like as cumbersome as it looks from from the get. But let me pull up that document.
34 00:04:04.520 ⇒ 00:04:14.989 Emily Giant: I got another screen, and it’s like I don’t know if it’s my laptop, but it only wants to connect to like one external monitor at a time. And it’s making me really.
35 00:04:14.990 ⇒ 00:04:19.369 Uttam Kumaran: Oh, you have to get, I think sometimes you have to get like a like
36 00:04:19.519 ⇒ 00:04:22.490 Uttam Kumaran: I use this thing called display link, and.
37 00:04:22.490 ⇒ 00:04:24.340 Emily Giant: Play. Link. Let me write that down.
38 00:04:24.802 ⇒ 00:04:29.789 Uttam Kumaran: It allows you to connect to like more than one like you can do up to 4, I think.
39 00:04:30.408 ⇒ 00:04:33.130 Emily Giant: Okay, is it just like a software.
40 00:04:33.130 ⇒ 00:04:34.080 Uttam Kumaran: Yes.
41 00:04:34.080 ⇒ 00:04:34.480 Emily Giant: Okay.
42 00:04:35.330 ⇒ 00:04:38.340 Uttam Kumaran: But I also have, like a hardware thing is, I have 3.
43 00:04:39.300 ⇒ 00:04:44.199 Uttam Kumaran: So you, I would try the software first, st and then, yeah.
44 00:04:44.480 ⇒ 00:04:45.290 Emily Giant: Sorry
45 00:04:47.140 ⇒ 00:04:59.480 Emily Giant: I had to skip all of my morning meetings, because, like every now and then, my allergies will like make my eyes swell shut. So if I look wild, that’s why I just now have eyes, and I’m still sneezing.
46 00:05:00.210 ⇒ 00:05:01.460 Uttam Kumaran: Totally. Okay.
47 00:05:01.460 ⇒ 00:05:02.090 Emily Giant: Okay.
48 00:05:05.160 ⇒ 00:05:12.399 Emily Giant: all right, trying to think the best way to pull up this document.
49 00:05:16.640 ⇒ 00:05:18.579 Emily Giant: Don’t have it bookmarked somewhere.
50 00:05:50.710 ⇒ 00:05:55.560 Amber Lin: Hello! I’m so sorry I was in the Eden meeting that ran over.
51 00:05:55.560 ⇒ 00:05:56.120 Uttam Kumaran: All good.
52 00:05:56.860 ⇒ 00:06:07.429 Amber Lin: Yeah. Oh, Emily, 1st thing, do you? Can you help? Look at Perry’s calendar to see when it’s free? We just. It’s the last meeting we have on the revenue side.
53 00:06:08.660 ⇒ 00:06:12.610 Uttam Kumaran: Well did she have any questions, Emily, like.
54 00:06:13.550 ⇒ 00:06:18.840 Uttam Kumaran: Or no like you think it’s worth meeting with her to go over anything.
55 00:06:19.440 ⇒ 00:06:23.860 Emily Giant: I, if there’s anyone who I know exactly like
56 00:06:24.020 ⇒ 00:06:28.229 Emily Giant: how they use looker and what they’re looking for, it’s their team. So
57 00:06:29.140 ⇒ 00:06:40.170 Emily Giant: well, I think we need to involve her as much as possible. And like the working sessions. Yeah, I think we should e even if it’s like she’s definitely the like main stakeholder. And
58 00:06:40.890 ⇒ 00:06:43.060 Emily Giant: even when it comes to like
59 00:06:43.510 ⇒ 00:06:51.400 Emily Giant: how finance and the other teams are interacting with the data now, she has more knowledge about that like than they do somehow. So.
60 00:06:51.400 ⇒ 00:06:52.020 Uttam Kumaran: Okay. Okay.
61 00:06:52.020 ⇒ 00:06:53.710 Emily Giant: Let me see.
62 00:06:58.520 ⇒ 00:07:07.097 Emily Giant: she’s like very aware of what they don’t know if that makes sense. And I think that could be helpful for Kyle.
63 00:07:09.420 ⇒ 00:07:11.324 Emily Giant: okay, so that’s today.
64 00:07:13.050 ⇒ 00:07:14.850 Emily Giant: Can you see my screen? Amber.
65 00:07:15.794 ⇒ 00:07:16.400 Amber Lin: Nope.
66 00:07:16.400 ⇒ 00:07:20.839 Emily Giant: Okay, shatter down.
67 00:07:21.720 ⇒ 00:07:23.379 Emily Giant: I think I shared it, like
68 00:07:23.980 ⇒ 00:07:27.559 Emily Giant: as I don’t know what happened here. But let me know when you can see it.
69 00:07:33.590 ⇒ 00:07:34.700 Emily Giant: Still, no.
70 00:07:35.310 ⇒ 00:07:36.539 Uttam Kumaran: Yes, we can see it.
71 00:07:38.040 ⇒ 00:07:46.100 Emily Giant: So looking at, there’s some time here.
72 00:07:46.430 ⇒ 00:07:50.160 Emily Giant: What is that like? 1130 tomorrow?
73 00:07:55.400 ⇒ 00:07:56.900 Emily Giant: 1130 Eastern?
74 00:07:57.500 ⇒ 00:07:58.240 Emily Giant: Yes.
75 00:07:58.370 ⇒ 00:08:00.189 Emily Giant: So 1030. Your time.
76 00:08:04.650 ⇒ 00:08:06.649 Uttam Kumaran: Yeah, I can do that.
77 00:08:07.640 ⇒ 00:08:09.020 Uttam Kumaran: Yeah. Why don’t we do that?
78 00:08:12.380 ⇒ 00:08:17.689 Uttam Kumaran: Yeah, it can just be. It can just be us 3 amber it could just be me, Emily, and.
79 00:08:19.710 ⇒ 00:08:20.065 Amber Lin: Okay.
80 00:08:22.010 ⇒ 00:08:26.328 Emily Giant: So either then or another time she has is like.
81 00:08:28.790 ⇒ 00:08:35.669 Emily Giant: actually, she has a lot of the afternoon open tomorrow from like 12 to.
82 00:08:35.679 ⇒ 00:08:39.309 Uttam Kumaran: Yeah, my whole afternoon is done. It’s cooked. So
83 00:08:39.309 ⇒ 00:08:42.549 Uttam Kumaran: what about today? Is it too short of notice?
84 00:08:42.549 ⇒ 00:08:43.789 Uttam Kumaran: I don’t wanna do today?
85 00:08:43.789 ⇒ 00:08:45.259 Amber Lin: Okay, that’s okay.
86 00:08:45.510 ⇒ 00:08:48.929 Uttam Kumaran: I don’t wanna do anything. I can’t book anything same day.
87 00:08:48.930 ⇒ 00:08:50.609 Amber Lin: Okay, that’s okay.
88 00:08:51.580 ⇒ 00:08:55.918 Emily Giant: And she has, like all of Friday, open, which makes me think she’s probably not in on Friday.
89 00:08:56.160 ⇒ 00:08:58.030 Uttam Kumaran: Maybe let’s at 1030.
90 00:08:58.520 ⇒ 00:09:00.389 Uttam Kumaran: Central tomorrow is fine.
91 00:09:01.970 ⇒ 00:09:13.610 Emily Giant: Okay, cool. And she has, like a meeting with Stephanie at 1145. But if we do like 1115, or excuse me, 1015, your time to
92 00:09:14.290 ⇒ 00:09:17.000 Emily Giant: 1045.
93 00:09:17.520 ⇒ 00:09:20.260 Emily Giant: Is that possible? Or does it need to be at the 30.
94 00:09:20.670 ⇒ 00:09:24.769 Amber Lin: Would she be free early if she’s in the meeting.
95 00:09:28.390 ⇒ 00:09:30.640 Emily Giant: Free early, like earlier than.
96 00:09:30.640 ⇒ 00:09:36.400 Uttam Kumaran: I’m basically free until 12 Eastern, so I can do anytime before 12 Eastern.
97 00:09:36.690 ⇒ 00:09:37.365 Emily Giant: Okay.
98 00:09:38.040 ⇒ 00:09:42.469 Amber Lin: Instead of the working session in the morning. We we do.
99 00:09:42.890 ⇒ 00:09:47.339 Emily Giant: Yeah, that’s perfect. Wait. She’s got a 9, 45, but we could do a 9 o’clock.
100 00:09:47.690 ⇒ 00:09:50.470 Amber Lin: Yeah, what? What we can do that.
101 00:09:50.870 ⇒ 00:09:56.059 Emily Giant: Okay, and I think she’s she’s on mountain time right now. She’s in Wyoming.
102 00:09:56.180 ⇒ 00:09:59.209 Emily Giant: So is that the same time as you, Tom or.
103 00:10:00.017 ⇒ 00:10:03.010 Uttam Kumaran: I’m 1 h ahead of mountain time.
104 00:10:03.010 ⇒ 00:10:11.050 Emily Giant: Okay, yeah, we’ll schedule it. I mean, she’s meant to be available at 10 o’clock. So like
105 00:10:11.570 ⇒ 00:10:13.269 Emily Giant: 9 to 9, 30.
106 00:10:14.055 ⇒ 00:10:14.530 Uttam Kumaran: Yeah.
107 00:10:15.070 ⇒ 00:10:16.920 Emily Giant: Or 8 to 8 30, for you.
108 00:10:18.420 ⇒ 00:10:19.599 Emily Giant: Are you sure.
109 00:10:19.600 ⇒ 00:10:21.060 Uttam Kumaran: Yeah, yeah, I’ll be out.
110 00:10:22.530 ⇒ 00:10:24.570 Uttam Kumaran: I would rather do it earlier.
111 00:10:25.400 ⇒ 00:10:26.120 Uttam Kumaran: So.
112 00:10:27.240 ⇒ 00:10:32.976 Emily Giant: Yeah, me, too. My mornings are always insane, and I try to keep my afternoon clear to like, actually do work.
113 00:10:35.090 ⇒ 00:10:38.689 Emily Giant: But okay, does that work for everyone, then 9 to 9, 30.
114 00:10:38.900 ⇒ 00:10:42.129 Amber Lin: It’ll just be you Utam and Perry so.
115 00:10:42.420 ⇒ 00:10:43.170 Emily Giant: Perfect.
116 00:10:43.170 ⇒ 00:10:44.298 Amber Lin: I won’t be there.
117 00:10:49.033 ⇒ 00:10:56.460 Amber Lin: Oh, actually, maybe Udem, you do your invite so we can have the zoom recording because I would need the transcript.
118 00:10:58.066 ⇒ 00:10:58.879 Uttam Kumaran: Sure, okay.
119 00:10:58.880 ⇒ 00:11:02.740 Amber Lin: Okay, sounds good. I’ll I’ll send
120 00:11:03.030 ⇒ 00:11:05.849 Amber Lin: Harry’s. I think you’ll have Harry’s email.
121 00:11:06.210 ⇒ 00:11:06.940 Amber Lin: Okay.
122 00:11:29.850 ⇒ 00:11:30.950 Amber Lin: okay.
123 00:11:42.070 ⇒ 00:11:46.689 Amber Lin: So on the revenue side.
124 00:11:52.840 ⇒ 00:11:55.100 Uttam Kumaran: Is there? Yeah, do you have? Is there a question or.
125 00:11:55.100 ⇒ 00:12:09.359 Amber Lin: Oh, sorry. Sorry. Starting to create tickets or modify tickets on the revenue side. I think next sprint our focus would be the initial modeling on the revenue side.
126 00:12:09.952 ⇒ 00:12:19.460 Amber Lin: I don’t yet have specific tickets for them. I had a big one to break break down, because I wasn’t sure if we’re gonna keep the audit.
127 00:12:19.460 ⇒ 00:12:21.500 Uttam Kumaran: Is there? Is there a project for this already?
128 00:12:21.500 ⇒ 00:12:24.120 Amber Lin: Yes, is in Dbt. Revenue.
129 00:12:24.780 ⇒ 00:12:27.449 Uttam Kumaran: Okay. So all of these are in Dvt revenue.
130 00:12:29.560 ⇒ 00:12:30.310 Uttam Kumaran: Okay.
131 00:12:36.530 ⇒ 00:12:41.159 Uttam Kumaran: okay, yeah, like, I would probably remove a couple of these things like.
132 00:12:41.320 ⇒ 00:12:41.940 Amber Lin: Okay.
133 00:12:41.940 ⇒ 00:12:46.990 Uttam Kumaran: 1 50. Well, I guess, how do you? Wanna yeah, how do we want to do this today? Like, do you.
134 00:12:47.295 ⇒ 00:12:57.079 Amber Lin: Feel free to remove anything that you see just like just cancel, delete them, and then we’ll we can start, or I can also get rid of all these, and then start.
135 00:12:57.080 ⇒ 00:12:59.759 Uttam Kumaran: Yeah, like 1 57, we can remove
136 00:13:01.580 ⇒ 00:13:04.710 Uttam Kumaran: like, let’s just let’s just go in like a list, please. Okay.
137 00:13:05.260 ⇒ 00:13:07.879 Uttam Kumaran: so can we start at either top or the bottom.
138 00:13:08.270 ⇒ 00:13:09.619 Amber Lin: No, let’s start. Here.
139 00:13:13.970 ⇒ 00:13:17.520 Uttam Kumaran: Yeah. So I don’t know is this, this is like inventory, like.
140 00:13:19.520 ⇒ 00:13:22.780 Amber Lin: It’s 20 days ago. Is this still valid, Emily?
141 00:13:25.370 ⇒ 00:13:26.910 Emily Giant: Is this still what I’m sorry.
142 00:13:26.910 ⇒ 00:13:28.639 Amber Lin: Is this still a valid ticket.
143 00:13:29.070 ⇒ 00:13:34.940 Emily Giant: No logic to include, exclude models for downstream of inventory adjustments. No, this can be closed out.
144 00:13:34.940 ⇒ 00:13:35.720 Amber Lin: Okay.
145 00:13:41.990 ⇒ 00:13:49.750 Amber Lin: it’s like, finishing. These 2 are like finishing up this rebuild.
146 00:13:54.300 ⇒ 00:13:55.790 Amber Lin: 1, 5, 9.
147 00:13:57.830 ⇒ 00:14:01.059 Emily Giant: It’s still valid for inventory, but it’s not urgent.
148 00:14:01.060 ⇒ 00:14:03.000 Amber Lin: Oh, sorry we’re in revenue.
149 00:14:03.000 ⇒ 00:14:05.859 Emily Giant: Oh, and revenue deprecate my great old logic.
150 00:14:08.100 ⇒ 00:14:09.779 Amber Lin: Will happen eventually.
151 00:14:09.780 ⇒ 00:14:15.410 Uttam Kumaran: Yeah, I guess, like, these are all like 2 generic. So I would just get rid of like 1, 59.
152 00:14:18.550 ⇒ 00:14:27.970 Uttam Kumaran: I would get rid of 53 and
153 00:14:28.870 ⇒ 00:14:32.940 Uttam Kumaran: yeah. So let’s like, let’s just remove these. You can just delete these. Yeah,
154 00:14:35.520 ⇒ 00:14:43.160 Uttam Kumaran: And then, okay, so let’s just like, Go, let’s do one pass. And just, I’ll I’ll tell you which ones delete that are like too generic. So
155 00:14:43.380 ⇒ 00:14:48.079 Uttam Kumaran: 1, 72, 45 says categorization.
156 00:14:53.130 ⇒ 00:14:58.240 Uttam Kumaran: Okay, so like 133-12-9120. So what is 1, 20.
157 00:15:01.960 ⇒ 00:15:07.420 Amber Lin: I think similar, as once we have the more incremental models.
158 00:15:08.060 ⇒ 00:15:09.530 Uttam Kumaran: Is there anything in that ticket.
159 00:15:09.830 ⇒ 00:15:12.719 Amber Lin: No? Oh, AI ticket!
160 00:15:13.530 ⇒ 00:15:14.850 Amber Lin: Nothing. Really.
161 00:15:16.620 ⇒ 00:15:18.970 Amber Lin: I base this off of what we have for inventory.
162 00:15:18.970 ⇒ 00:15:22.939 Uttam Kumaran: Oh, okay, then I would. Yeah, I would remove the this one.
163 00:15:22.940 ⇒ 00:15:23.510 Amber Lin: Okay.
164 00:15:30.980 ⇒ 00:15:33.150 Uttam Kumaran: And what is 1, 33.
165 00:15:35.250 ⇒ 00:15:37.210 Uttam Kumaran: Okay, this is a good one.
166 00:15:37.740 ⇒ 00:15:44.579 Uttam Kumaran: We can leave this one and is there anything else? Are these all of them.
167 00:15:48.010 ⇒ 00:15:53.130 Amber Lin: Yeah, these are all of them. I didn’t have any building tickets, because I know we don’t have
168 00:15:53.860 ⇒ 00:15:55.700 Amber Lin: didn’t have a plan yet.
169 00:15:57.660 ⇒ 00:15:58.360 Uttam Kumaran: Okay.
170 00:16:01.260 ⇒ 00:16:07.339 Uttam Kumaran: So yeah, I mean, basically, the goal of like, what I’ll probably do is I’m just gonna start to work on
171 00:16:07.820 ⇒ 00:16:10.199 Uttam Kumaran: creating tickets for
172 00:16:10.650 ⇒ 00:16:20.490 Uttam Kumaran: new models. I mean, we don’t. I don’t think we we don’t necessarily have to do it. But is, is everyone kind of clear on like for the Tdd, basically, we’re gonna have tickets that are related to
173 00:16:21.060 ⇒ 00:16:28.119 Uttam Kumaran: like either re-architecting like like cleanup of existing models. There’s gonna be.
174 00:16:28.120 ⇒ 00:16:28.670 Amber Lin: You.
175 00:16:28.810 ⇒ 00:16:36.669 Uttam Kumaran: There’s gonna be things that are related to creating new models. And basically, we’re gonna end up with several march models that are net new.
176 00:16:36.780 ⇒ 00:16:38.910 Uttam Kumaran: So I mean, like, I don’t.
177 00:16:39.010 ⇒ 00:16:46.069 Uttam Kumaran: I don’t feel like we have to do that like on this call. I can just go do those. But like I just wanna make sure all the 3 of us are clear on like
178 00:16:46.180 ⇒ 00:16:48.059 Uttam Kumaran: what the outputs are. Gonna be.
179 00:16:50.020 ⇒ 00:17:02.689 Emily Giant: Yeah, that makes sense. Like, I think that there’s a lot that we need to figure out. That should probably be tickets like what we’re talking about with Zack right now, how we’re integrating loop, how we’re integrating North meme all of these like
180 00:17:04.155 ⇒ 00:17:05.010 Emily Giant: new.
181 00:17:05.010 ⇒ 00:17:11.870 Uttam Kumaran: So maybe we can. Yeah, maybe at least we can. Today, we can start with the ingestion piece. So let’s put a ticket for loop
182 00:17:11.980 ⇒ 00:17:15.139 Uttam Kumaran: data ingestion. And for north beam data ingestion.
183 00:17:20.390 ⇒ 00:17:21.220 Uttam Kumaran: Yeah.
184 00:17:22.650 ⇒ 00:17:33.989 Emily Giant: I think those are the 2 main ones. And then there’s gonna be like down the line, gorgeous data ingestion. But that’s like customer service mart. So for revenue, those 2 would be the only like net new integrations. I think.
185 00:17:34.340 ⇒ 00:17:44.079 Uttam Kumaran: Yeah. And then I think if we can just create a couple of like tickets. So what we, I want a ticket for a couple of models. So orders sub orders.
186 00:17:45.010 ⇒ 00:17:50.420 Uttam Kumaran: line items and transactions cool?
187 00:17:56.230 ⇒ 00:17:58.313 Uttam Kumaran: I’m we’re also gonna want
188 00:18:02.730 ⇒ 00:18:04.469 Uttam Kumaran: Refunds.
189 00:18:11.080 ⇒ 00:18:14.330 Uttam Kumaran: And then within the transactions ticket.
190 00:18:14.480 ⇒ 00:18:19.969 Uttam Kumaran: Can you just put a note that we need to support discounts and markdowns here
191 00:18:22.460 ⇒ 00:18:26.600 Uttam Kumaran: as and then, if you go to the orders.
192 00:18:28.940 ⇒ 00:18:31.239 Uttam Kumaran: can you put that we need to support.
193 00:18:33.530 ⇒ 00:18:41.010 Uttam Kumaran: Several different date fields, including delivery date order date.
194 00:18:41.840 ⇒ 00:18:44.019 Uttam Kumaran: Yeah, that’s fine for that.
195 00:18:48.420 ⇒ 00:18:54.230 Uttam Kumaran: Additionally, I wanna create a customers table. But can you? We can create one call customers.
196 00:19:00.710 ⇒ 00:19:03.040 Uttam Kumaran: And we’re gonna want a subscriptions table.
197 00:19:07.160 ⇒ 00:19:09.319 Uttam Kumaran: And then the note for subscriptions.
198 00:19:15.100 ⇒ 00:19:18.110 Uttam Kumaran: We’re gonna need to have several fields, for.
199 00:19:18.830 ⇒ 00:19:26.140 Uttam Kumaran: like the status of each subscription like, when was it pause? When was it started? When was did it end?
200 00:19:28.420 ⇒ 00:19:38.443 Uttam Kumaran: And then a new model I wanna we wanna have is basically like, let’s call it
201 00:19:50.520 ⇒ 00:19:54.369 Uttam Kumaran: I don’t know exactly what we’re gonna call it right now. But
202 00:19:56.590 ⇒ 00:20:00.302 Uttam Kumaran: can you also put like, I think one bottle we can do is just like
203 00:20:01.280 ⇒ 00:20:04.750 Uttam Kumaran: you can just say BOM. Slash eom
204 00:20:06.050 ⇒ 00:20:08.730 Uttam Kumaran: BOME. OM. Yeah.
205 00:20:10.570 ⇒ 00:20:12.670 Uttam Kumaran: Subscription snapshots.
206 00:20:13.600 ⇒ 00:20:18.219 Uttam Kumaran: So these are going to be snapshots of all active subscriptions at a given point.
207 00:20:23.320 ⇒ 00:20:28.675 Uttam Kumaran: And then the second, then that new model we’re gonna wanna do is also gonna be called
208 00:20:32.800 ⇒ 00:20:38.390 Uttam Kumaran: subscriptions revenue summary.
209 00:20:40.080 ⇒ 00:20:48.350 Uttam Kumaran: And then no, this is gonna be an aggregate table of the revenue associated with subscriptions.
210 00:20:51.291 ⇒ 00:20:53.340 Uttam Kumaran: At a given point in time.
211 00:21:01.090 ⇒ 00:21:02.030 Uttam Kumaran: Okay.
212 00:21:07.660 ⇒ 00:21:08.809 Uttam Kumaran: let me think.
213 00:21:56.845 ⇒ 00:22:02.610 Uttam Kumaran: Can I do a a monthly revenue summary table?
214 00:22:16.880 ⇒ 00:22:23.630 Uttam Kumaran: And then can we also add a customer.
215 00:22:35.070 ⇒ 00:22:38.910 Uttam Kumaran: We’re actually can. We just call like marketing revenue summary.
216 00:22:39.430 ⇒ 00:22:41.720 Uttam Kumaran: And the note for this one is
217 00:22:42.364 ⇒ 00:22:49.199 Uttam Kumaran: we’re going to be having where this is, where we’re gonna show revenue and conversions by source.
218 00:22:50.260 ⇒ 00:22:52.629 Uttam Kumaran: This will require north theme data.
219 00:23:02.380 ⇒ 00:23:04.839 Uttam Kumaran: And then can you also create?
220 00:23:07.780 ⇒ 00:23:17.160 Uttam Kumaran: This is gonna be 3 tickets. We’re gonna create monthly, weekly and daily revenue summary table.
221 00:23:17.620 ⇒ 00:23:23.770 Uttam Kumaran: These are just gonna have all those Kpis on those time grains.
222 00:23:37.790 ⇒ 00:23:40.850 Uttam Kumaran: okay, I feel like this is probably a good amount.
223 00:23:41.930 ⇒ 00:23:45.349 Amber Lin: Okay. Now, I can go fill in the details.
224 00:23:46.764 ⇒ 00:23:49.610 Amber Lin: With the transcripts and the document.
225 00:23:52.650 ⇒ 00:23:55.259 Amber Lin: Yeah, that’s good enough for me to work with.
226 00:23:56.090 ⇒ 00:23:57.620 Emily Giant: Yeah. Things will come up.
227 00:23:58.480 ⇒ 00:24:04.699 Uttam Kumaran: Yeah. So I I think a couple of points. So like all of these tickets are gonna have to have, like the
228 00:24:05.140 ⇒ 00:24:10.150 Uttam Kumaran: clear questions that the model will be answering.
229 00:24:11.510 ⇒ 00:24:20.370 Uttam Kumaran: It’s gonna have to have, like, some basically over like, what what are the core columns necessary.
230 00:24:23.290 ⇒ 00:24:26.529 Uttam Kumaran: And then what are the downstream and upstream dependencies?
231 00:24:27.490 ⇒ 00:24:31.960 Uttam Kumaran: So I wanna make sure all these are groomed before these get moved into any cycle.
232 00:24:33.831 ⇒ 00:24:36.588 Amber Lin: Sorry key question is asking
233 00:24:37.140 ⇒ 00:24:41.840 Uttam Kumaran: Like, what questions that we got from the stakeholders is this model?
234 00:24:43.980 ⇒ 00:24:45.160 Uttam Kumaran: Can I answer.
235 00:24:47.740 ⇒ 00:24:49.790 Amber Lin: And then the next one was.
236 00:24:52.620 ⇒ 00:24:54.080 Amber Lin: Columns, tables.
237 00:24:54.080 ⇒ 00:24:59.899 Uttam Kumaran: Yeah, like, what call what? What dimensions and metrics need to be made available, on what time grain.
238 00:25:07.233 ⇒ 00:25:10.469 Uttam Kumaran: And then, yeah, what are the downstream and upstream models?
239 00:25:10.950 ⇒ 00:25:26.060 Uttam Kumaran: And then another very helpful. Another thing is like, what legacy models does this replace or overlap with.
240 00:25:34.030 ⇒ 00:25:34.820 Amber Lin: okay.
241 00:25:35.529 ⇒ 00:25:43.490 Uttam Kumaran: So then I probably another like placeholder ticket is gonna be for like making sure that
242 00:25:44.718 ⇒ 00:25:50.550 Uttam Kumaran: we have a migration plan for moving dashboards over to the new more.
243 00:25:52.300 ⇒ 00:26:02.270 Uttam Kumaran: and a deprecation plan for existing revenue related tables.
244 00:26:09.680 ⇒ 00:26:10.360 Uttam Kumaran: cool.
245 00:26:13.120 ⇒ 00:26:23.049 Uttam Kumaran: Okay, that’s probably it, for now I have to jump. But I’m gonna I’m gonna use what we have and couple of things. I can create some more tickets. But
246 00:26:23.390 ⇒ 00:26:27.100 Uttam Kumaran: yeah, like, ideally, the core tickets are just gonna be building these marts.
247 00:26:28.700 ⇒ 00:26:29.960 Uttam Kumaran: Building these tables.
248 00:26:30.650 ⇒ 00:26:36.569 Emily Giant: Feels like the same jumping off point, though, like, I don’t want to do too much and then have to like delete them. This feels like.
249 00:26:36.570 ⇒ 00:26:37.330 Uttam Kumaran: Yeah.
250 00:26:37.330 ⇒ 00:26:43.160 Emily Giant: Yeah, good, foundationally, and more descriptive than what we had before.
251 00:26:44.870 ⇒ 00:26:45.600 Uttam Kumaran: Perfect.
252 00:26:45.600 ⇒ 00:26:46.010 Emily Giant: Yeah.
253 00:26:46.010 ⇒ 00:26:46.800 Amber Lin: Okay.
254 00:26:47.690 ⇒ 00:26:58.499 Amber Lin: Awesome. Yeah. Let me let me know when you’ve created new tickets, and I will jump on and flush them down. For the meantime I’ll go read the design document.
255 00:26:58.680 ⇒ 00:26:59.980 Uttam Kumaran: Okay, okay, perfect.
256 00:26:59.980 ⇒ 00:27:00.719 Amber Lin: All right.
257 00:27:01.890 ⇒ 00:27:03.240 Emily Giant: Thank you.
258 00:27:03.380 ⇒ 00:27:04.330 Uttam Kumaran: Fine.
259 00:27:04.330 ⇒ 00:27:05.120 Amber Lin: Bye.