Meeting Title: US x BF | Grooming Date: 2025-07-02 Meeting participants: Amber Lin, Emily Giant, Demilade Agboola, Uttam Kumaran, Caio Velasco
WEBVTT
1 00:00:32.960 ⇒ 00:00:34.370 Amber Lin: Hello! Everyone.
2 00:00:34.650 ⇒ 00:00:35.620 Emily Giant: Hello!
3 00:00:37.120 ⇒ 00:00:47.500 Amber Lin: Hmm! I’ll share. Screen this one. This grooming probably would take longer than last time, cause we’re actually going through
4 00:00:47.840 ⇒ 00:00:51.259 Amber Lin: all the different projects.
5 00:00:51.870 ⇒ 00:00:57.060 Amber Lin: And let’s see, okay, we can start with inventory.
6 00:00:58.101 ⇒ 00:01:08.130 Amber Lin: I’ve did my best with AI to add requirements and everything to these tickets. I want us together to
7 00:01:08.570 ⇒ 00:01:13.929 Amber Lin: look at if they’re still, if there’s still something we want to do.
8 00:01:14.070 ⇒ 00:01:20.889 Amber Lin: and if so, are they correctly named or correctly written?
9 00:01:22.520 ⇒ 00:01:31.420 Amber Lin: So I think this part, I’ll I’ll need your guys help on this. So I know for this cycle we’re gonna finish adding
10 00:01:31.820 ⇒ 00:01:37.470 Amber Lin: the non-fold goods. Finish the refolder renaming and refoldering.
11 00:01:40.520 ⇒ 00:01:47.139 Amber Lin: Can we take a moment to read through each one of these and
12 00:01:48.440 ⇒ 00:01:55.580 Amber Lin: make sure that they’re one something we still want to do, and 2 assign priorities and 3. Look at the point. Estimates
13 00:01:59.380 ⇒ 00:02:05.889 Emily Giant: Before we do those. Can you click on the add non floral and hard goods to inventory adjustments?
14 00:02:06.320 ⇒ 00:02:11.650 Emily Giant: I just want to see the criteria there. Refactor. Ctes runtime. Yep, that’s fine.
15 00:02:11.950 ⇒ 00:02:12.500 Amber Lin: Yeah.
16 00:02:13.290 ⇒ 00:02:18.540 Emily Giant: Okay. I was just making sure that done a lot. I knew that they already exist. They just need to be refractured.
17 00:02:19.640 ⇒ 00:02:23.649 Emily Giant: and that that’s also related to the ticket that I’m working on today.
18 00:02:24.430 ⇒ 00:02:27.529 Emily Giant: Like parent and piece, adjustment, type.
19 00:02:27.880 ⇒ 00:02:28.200 Amber Lin: Oh!
20 00:02:28.670 ⇒ 00:02:33.339 Emily Giant: Plural stuff. But I can add those comments to the ticket. I just didn’t know if it would.
21 00:02:33.340 ⇒ 00:02:34.040 Amber Lin: Sure.
22 00:02:34.040 ⇒ 00:02:35.880 Emily Giant: And change the pointing on that.
23 00:02:39.200 ⇒ 00:02:40.140 Amber Lin: I think.
24 00:02:40.440 ⇒ 00:02:53.090 Amber Lin: since you are working the other parts, I think for them a lot is part. It would still be 3 points, 3 points at 1 point. It’s like 2 h. So is it still? Is it still gonna be around 6 h, or is it gonna be less.
25 00:02:53.090 ⇒ 00:02:56.140 Emily Giant: Yeah, that’s fine. That’s totally fine.
26 00:02:56.140 ⇒ 00:02:56.760 Amber Lin: Okay.
27 00:02:57.980 ⇒ 00:03:00.720 Amber Lin: So this is something that came out. My.
28 00:03:00.720 ⇒ 00:03:03.139 Amber Lin: now, I’m ready for the one being already group
29 00:03:06.398 ⇒ 00:03:15.560 Amber Lin: this one came out of the meeting with Zack and Utam. So what we wanted was to before
30 00:03:15.830 ⇒ 00:03:39.680 Amber Lin: before we finish off inventory, or as we finish off inventory, we want to get the top dashboards and analysis impacted by the Mars that we’re rebuilding. And that means talking to the analyst owners and helping them understand how this is going to impact them, and also how we are going to rebuild the analysis that they’re doing based on the new marts.
31 00:03:40.100 ⇒ 00:03:52.690 Amber Lin: So I think this is the ultimate how it impacts the business is this is the implementation. So I thought it was very. I thought it was very important, but I wasn’t sure how many points
32 00:03:52.880 ⇒ 00:03:56.120 Amber Lin: that is. And I wanted to hear your guys thoughts.
33 00:03:57.820 ⇒ 00:03:58.570 Emily Giant: Hmm!
34 00:04:01.970 ⇒ 00:04:06.010 Emily Giant: It might be more than 3 points if we’re talking through like.
35 00:04:06.510 ⇒ 00:04:08.879 Emily Giant: Well, so inventory.
36 00:04:08.880 ⇒ 00:04:12.470 Amber Lin: Individual. I guess we need individual visual working sessions.
37 00:04:12.470 ⇒ 00:04:13.360 Emily Giant: Yeah.
38 00:04:16.290 ⇒ 00:04:19.029 Amber Lin: With Perry.
39 00:04:19.399 ⇒ 00:04:25.039 Emily Giant: Perry and Felipe are probably the only ones that really need to be at that session.
40 00:04:25.400 ⇒ 00:04:26.120 Amber Lin: Okay.
41 00:04:26.330 ⇒ 00:04:27.830 Amber Lin: Okay. Sounds good.
42 00:04:27.830 ⇒ 00:04:29.480 Emily Giant: In those sessions. Yeah.
43 00:04:29.480 ⇒ 00:04:52.679 Amber Lin: I think when we talked to Zack, he said, we also wanna be able to up uplift Pk to do to know more about dbt, so that they won’t always come to you, so you can have a chance to breathe. And also, I think, similar for Jesse to also, just to keep the 4 core people, informed Perry, Felipe, Jesse, and Pk.
44 00:04:53.345 ⇒ 00:04:54.010 Emily Giant: Yeah.
45 00:04:54.010 ⇒ 00:04:57.720 Amber Lin: Informed. I’ll say, pk, and Jesse,
46 00:04:59.590 ⇒ 00:05:04.340 Amber Lin: okay, so I’ll bring that up in the meeting in Thursday.
47 00:05:08.710 ⇒ 00:05:15.900 Amber Lin: Bring up a meeting this Thursday, so that actually.
48 00:05:16.110 ⇒ 00:05:19.737 Demilade Agboola: So we want to rework the dashboards, or are we
49 00:05:20.510 ⇒ 00:05:25.830 Demilade Agboola: just are we rebuilding, or are we just tweaking the dashboards with the new information.
50 00:05:25.830 ⇒ 00:05:31.820 Amber Lin: Yeah, that’s a i think that’s a question we need to figure out alright. I’ll write that down.
51 00:05:31.820 ⇒ 00:05:35.120 Emily Giant: We should rebuild them entirely.
52 00:05:36.490 ⇒ 00:05:37.350 Emily Giant: But
53 00:05:39.230 ⇒ 00:05:47.690 Emily Giant: for inventory, anyway, there’s so much out there with inventory specifically, that’s like mixed in with inventory Xf. And deprecated models
54 00:05:48.480 ⇒ 00:05:53.640 Emily Giant: that I just wanna make sure that, like those, are all archived or put in a folder
55 00:05:53.750 ⇒ 00:05:58.479 Emily Giant: for a couple months before getting deleted like we had talked about but there’s.
56 00:05:58.480 ⇒ 00:05:58.900 Demilade Agboola: Okay.
57 00:05:58.900 ⇒ 00:06:01.950 Emily Giant: Pretty much dead data living in there still.
58 00:06:04.710 ⇒ 00:06:05.750 Demilade Agboola: Okay. Sounds good.
59 00:06:06.010 ⇒ 00:06:10.799 Amber Lin: So I will. I’ll just actually separate out these tickets.
60 00:06:10.970 ⇒ 00:06:16.260 Demilade Agboola: So we want to. We want to like, actually deprecate the dashboards and build new dashboards.
61 00:06:18.120 ⇒ 00:06:21.890 Amber Lin: I see if.
62 00:06:22.240 ⇒ 00:06:23.480 Emily Giant: Maybe I would. Yeah.
63 00:06:24.140 ⇒ 00:06:27.630 Demilade Agboola: So we can stop using like old data sources.
64 00:06:31.770 ⇒ 00:06:34.610 Amber Lin: So I’m going to
65 00:06:41.670 ⇒ 00:06:45.859 Amber Lin: So I’m gonna put this here. I’ll say it needs grooming.
66 00:06:46.540 ⇒ 00:06:50.460 Amber Lin: I’m gonna move the previous one actually to.
67 00:06:50.860 ⇒ 00:06:53.809 Amber Lin: I think just getting the dashboards will probably
68 00:06:54.010 ⇒ 00:06:59.679 Amber Lin: take. Not that long. I’m gonna do that. This we should do that this cycle, this Thursday.
69 00:07:04.920 ⇒ 00:07:07.329 Amber Lin: I’m gonna move this.
70 00:07:09.680 ⇒ 00:07:20.050 Amber Lin: Hurry issue. Yeah, I think getting the plan is probably 2 or 3 points, 2 points.
71 00:07:21.380 ⇒ 00:07:24.439 Amber Lin: I’ll say, that’s also high priority.
72 00:07:26.615 ⇒ 00:07:35.869 Amber Lin: Okay, so inventory. That’s the 1st one. These are so, I think that’s the last.
73 00:07:37.450 ⇒ 00:07:42.480 Amber Lin: Oh, I think that’s the last modeling ticket we have.
74 00:07:45.550 ⇒ 00:07:52.399 Demilade Agboola: I mean for this flow. Yes, so this flow is, for like orders, and part of that will be inventory.
75 00:07:52.510 ⇒ 00:07:55.130 Amber Lin: But it’s just like we’re recreating.
76 00:07:56.580 ⇒ 00:08:03.519 Demilade Agboola: the different like bits and pieces I have made up like the orders and the content. So this would be for that
77 00:08:04.119 ⇒ 00:08:08.550 Demilade Agboola: potentially. Yes, we might continue like walking around, especially for like revenue.
78 00:08:09.090 ⇒ 00:08:13.260 Demilade Agboola: and figure out that there’s some other modeling like that we might need to do for that
79 00:08:13.650 ⇒ 00:08:16.660 Demilade Agboola: those will come up. But for now yes, this is what we have in view.
80 00:08:17.655 ⇒ 00:08:18.380 Amber Lin: Okay,
81 00:08:20.100 ⇒ 00:08:24.160 Amber Lin: So that’s auto.
82 00:08:25.630 ⇒ 00:08:32.039 Amber Lin: Is that still high priority? And is that still 2 points.
83 00:08:36.641 ⇒ 00:08:40.490 Demilade Agboola: I would say, need priority, medium.
84 00:08:40.909 ⇒ 00:08:42.879 Demilade Agboola: And I’ll probably say 3 points.
85 00:08:42.880 ⇒ 00:08:43.280 Amber Lin: Okay.
86 00:08:45.000 ⇒ 00:08:47.190 Amber Lin: So that’s good.
87 00:08:47.760 ⇒ 00:08:50.340 Amber Lin: Actually, let me move this to
88 00:08:53.790 ⇒ 00:08:55.230 Amber Lin: and next.
89 00:08:58.015 ⇒ 00:08:59.240 Amber Lin: Logic.
90 00:09:00.340 ⇒ 00:09:02.869 Amber Lin: What? What is this one?
91 00:09:04.410 ⇒ 00:09:08.459 Amber Lin: I just found it earlier, and I wasn’t sure what this was.
92 00:09:10.880 ⇒ 00:09:15.353 Emily Giant: Yes. So that’s part of the inventory work. There are
93 00:09:16.340 ⇒ 00:09:22.770 Emily Giant: a subset of orders that were delivered without actually having
94 00:09:23.050 ⇒ 00:09:29.449 Emily Giant: been assigned to a lot, and all of the reporting we do in inventory is for
95 00:09:29.560 ⇒ 00:09:36.779 Emily Giant: items that were successfully assigned to a lot and then sent, but there to be a a way
96 00:09:37.720 ⇒ 00:09:42.729 Emily Giant: to analyze orders that were sent without a lot assignment.
97 00:09:43.230 ⇒ 00:09:43.880 Amber Lin: Hmm.
98 00:09:45.070 ⇒ 00:09:48.040 Emily Giant: Because it accounts for a lot of inventory discrepancies.
99 00:09:49.350 ⇒ 00:09:51.079 Emily Giant: But right now, the way that
100 00:09:51.240 ⇒ 00:09:54.410 Emily Giant: things are joined it will obscure these orders.
101 00:09:54.410 ⇒ 00:09:55.120 Amber Lin: Hmm!
102 00:09:58.850 ⇒ 00:09:59.870 Amber Lin: So
103 00:10:01.060 ⇒ 00:10:02.320 Amber Lin: Oh, gosh!
104 00:10:02.700 ⇒ 00:10:08.850 Amber Lin: Is this also still 2 points? What is the priority for this.
105 00:10:13.070 ⇒ 00:10:13.810 Demilade Agboola: Bye.
106 00:10:14.770 ⇒ 00:10:15.450 Emily Giant: Go ahead!
107 00:10:15.930 ⇒ 00:10:21.480 Demilade Agboola: I was gonna say for priority, given that it’s still part of inventory, I think we should set it to high.
108 00:10:23.490 ⇒ 00:10:30.099 Demilade Agboola: I think it’s probably maybe 2 or 3 point. It depends on how like, because we’re
109 00:10:30.310 ⇒ 00:10:41.510 Demilade Agboola: inventory is coming along really nicely. You do have the sub orders like inventory by sub orders. Part of what Emily and I were talking about today was kind of how to put the orders, inventory
110 00:10:41.700 ⇒ 00:10:46.810 Demilade Agboola: supporter level inventory with the inventory number like the lot id.
111 00:10:47.650 ⇒ 00:10:48.320 Demilade Agboola: Therefore.
112 00:10:48.918 ⇒ 00:10:51.290 Emily Giant: So it’ll kind of be like the.
113 00:10:51.540 ⇒ 00:10:55.220 Demilade Agboola: Final product of being able to finalize that strategy.
114 00:10:56.650 ⇒ 00:11:00.289 Amber Lin: Okay, sounds good. So we’ll put it as high
115 00:11:00.430 ⇒ 00:11:03.790 Amber Lin: gonna move that to ready for development.
116 00:11:06.520 ⇒ 00:11:11.270 Amber Lin: Among these, what is the most next most important one.
117 00:11:18.360 ⇒ 00:11:18.900 Demilade Agboola: Actually
118 00:11:22.160 ⇒ 00:11:23.389 Demilade Agboola: you want to say something.
119 00:11:24.081 ⇒ 00:11:31.590 Amber Lin: Actually, we can just look at each of the ones is adding freshness test like
120 00:11:33.284 ⇒ 00:11:39.779 Amber Lin: let me know the priority and the story points. And if this makes sense.
121 00:11:41.527 ⇒ 00:11:50.149 Demilade Agboola: It is a priority, but also part of why we want to get like Meta plane. And just like Demo, that is, that will allow us to be able to
122 00:11:50.300 ⇒ 00:11:52.919 Demilade Agboola: do some of these things automatically without having.
123 00:11:52.920 ⇒ 00:11:53.250 Amber Lin: That’s true.
124 00:11:53.760 ⇒ 00:11:59.959 Demilade Agboola: Set up like Dvt test and stuff. We can just kind of know the latest freshness, and if.
125 00:12:01.040 ⇒ 00:12:02.890 Demilade Agboola: It’s out of date, Metapil notified.
126 00:12:02.890 ⇒ 00:12:03.950 Amber Lin: I see.
127 00:12:04.310 ⇒ 00:12:10.280 Amber Lin: So actually, we want. We’ll wait for Meta plane to be done first.st
128 00:12:14.060 ⇒ 00:12:23.750 Amber Lin: It’s oh, okay. So I’ll say, this is.
129 00:12:25.050 ⇒ 00:12:28.340 Amber Lin: say it’s blocked by a meta plane.
130 00:12:30.530 ⇒ 00:12:31.460 Amber Lin: Okay.
131 00:12:33.080 ⇒ 00:12:34.368 Uttam Kumaran: Yeah, for this one.
132 00:12:34.690 ⇒ 00:12:35.450 Amber Lin: We should have.
133 00:12:35.450 ⇒ 00:12:41.089 Uttam Kumaran: Next sprint. Hey? Sorry I was listening in should have this for next sprint
134 00:12:41.633 ⇒ 00:12:53.660 Uttam Kumaran: I we’re just like signing an agreement with Meta plane. And then for Emily, for your context. We’re gonna for for a lot of our clients. We try to have, like some amount of
135 00:12:55.290 ⇒ 00:13:12.170 Uttam Kumaran: freshness and observability. So we’ll sort of demo what it looks like to have it on like one or 2 tables. And then we can. I can sort of explain what potential pricing looks like. We want to expand it to like way more tables it’s actually fairly reasonable for
136 00:13:12.460 ⇒ 00:13:20.930 Uttam Kumaran: the time. Cost that some of these challenges are are hitting us at. But yeah, I hope to have this next screen, I’m sure. Been pushing this along on our side.
137 00:13:21.380 ⇒ 00:13:22.320 Emily Giant: Alright, cool.
138 00:13:22.320 ⇒ 00:13:28.250 Amber Lin: Okay, is this still a low priority.
139 00:13:28.684 ⇒ 00:13:31.170 Uttam Kumaran: I would leave it as low.
140 00:13:31.170 ⇒ 00:13:31.610 Amber Lin: Okay.
141 00:13:31.610 ⇒ 00:13:34.010 Uttam Kumaran: None of our new models are being.
142 00:13:34.140 ⇒ 00:13:40.070 Amber Lin: Used yet. But I would just leave this here for now sounds good.
143 00:13:41.930 ⇒ 00:13:43.490 Amber Lin: Inventory.
144 00:13:44.550 ⇒ 00:13:54.690 Amber Lin: Right? Okay, gonna scoot that okay. Code, base cleanup.
145 00:13:54.900 ⇒ 00:13:57.330 Amber Lin: Remove assignees
146 00:13:59.170 ⇒ 00:14:07.230 Amber Lin: is this is 3 points, a good estimate, and does. Is there anything else I need to add
147 00:14:07.550 ⇒ 00:14:08.600 Amber Lin: to hear.
148 00:14:13.860 ⇒ 00:14:18.220 Demilade Agboola: I think it’s still low priority.
149 00:14:18.650 ⇒ 00:14:22.250 Demilade Agboola: But like part of this is just some of the
150 00:14:25.240 ⇒ 00:14:33.951 Demilade Agboola: right experience. Some of these things are happening as well in some of like the building of the intermediate models that I’m doing, because,
151 00:14:35.750 ⇒ 00:14:48.839 Demilade Agboola: that there’s some logic that’s high up in the model that I feel like it’s too high up there. We can move it down to the intermediate model, and that can allow it for for better propagation throughout. So I think, yeah, I think close fine. I think 3 points.
152 00:14:48.940 ⇒ 00:14:51.209 Demilade Agboola: It’s also a decent estimate as well.
153 00:14:51.730 ⇒ 00:14:58.240 Amber Lin: Okay, okay, I see. So I’m gonna add a note.
154 00:15:00.190 ⇒ 00:15:01.829 Amber Lin: So let’s
155 00:15:05.800 ⇒ 00:15:07.480 Amber Lin: sounds good.
156 00:15:14.963 ⇒ 00:15:24.139 Amber Lin: So this one calendar enhancements is this something that we’re currently doing related to the fiscal calendar fiscal calendar.
157 00:15:25.840 ⇒ 00:15:29.750 Emily Giant: That is something that I had to do that came in as like a
158 00:15:30.720 ⇒ 00:15:34.080 Emily Giant: p. 1, even though it says low, it’s almost done.
159 00:15:34.270 ⇒ 00:15:36.299 Amber Lin: Oh, so this is actually being done!
160 00:15:36.300 ⇒ 00:15:40.537 Emily Giant: Oh, wait, wait! Wait! This is different. I’m sorry. Different than the other one.
161 00:15:41.200 ⇒ 00:15:45.050 Emily Giant: add a fiscal calendar to support clean joins and time-based logic.
162 00:15:45.420 ⇒ 00:15:56.430 Emily Giant: I think that this might be related to the fact that there’s like 10 different fiscal calendars going on in our Dbt like, have a consolidated version but when we were doing the
163 00:15:56.984 ⇒ 00:16:00.540 Emily Giant: Dbt audit, there were so many different versions.
164 00:16:02.960 ⇒ 00:16:03.880 Amber Lin: Okay.
165 00:16:04.220 ⇒ 00:16:07.409 Emily Giant: Potentially more than 10. But
166 00:16:07.680 ⇒ 00:16:14.549 Emily Giant: yeah, they each have, like their own view. And like our, there’s no streamlined version. So it’s.
167 00:16:15.510 ⇒ 00:16:19.719 Amber Lin: So it will be better to say, standard dimes.
168 00:16:19.720 ⇒ 00:16:20.310 Emily Giant: Yeah.
169 00:16:20.630 ⇒ 00:16:30.100 Amber Lin: Size Cisco calendars and dbt, I don’t
170 00:16:30.200 ⇒ 00:16:33.930 Amber Lin: know if this is the right acceptance criteria, then
171 00:16:41.930 ⇒ 00:16:46.219 Amber Lin: are we gonna add one or just gonna delete all the except for one.
172 00:16:50.450 ⇒ 00:16:56.640 Demilade Agboola: I I think we should just create the a proper acceptance criteria. So like a standardized
173 00:16:57.280 ⇒ 00:17:00.470 Demilade Agboola: standardized fiscal calendar.
174 00:17:01.840 ⇒ 00:17:02.820 Demilade Agboola: Yeah.
175 00:17:06.770 ⇒ 00:17:09.190 Amber Lin: Is this still low in 2 points?
176 00:17:11.969 ⇒ 00:17:20.449 Demilade Agboola: Yes, it’s still low, and I might say 3 points instead, just because you’ll need to replace it across multiple places once you’re done.
177 00:17:22.069 ⇒ 00:17:27.649 Amber Lin: In place, Isis
178 00:17:31.969 ⇒ 00:17:33.149 Amber Lin: alright.
179 00:17:37.849 ⇒ 00:17:42.989 Amber Lin: and so inventory. Supply chain version.
180 00:17:53.919 ⇒ 00:17:57.349 Amber Lin: is this the right acceptance criteria.
181 00:18:08.910 ⇒ 00:18:14.954 Emily Giant: Yeah, I’m trying to figure out if
182 00:18:16.240 ⇒ 00:18:22.029 Emily Giant: this is something that should be done in Looker versus dbt, but I’ve done a lot. I
183 00:18:23.130 ⇒ 00:18:24.890 Emily Giant: drive on that one.
184 00:18:25.290 ⇒ 00:18:33.140 Demilade Agboola: I I generally prefer, like logic being done in Dvt as much as possible. Cause once you stop with any looker, it can be
185 00:18:33.510 ⇒ 00:18:39.510 Demilade Agboola: harder for people to see especially when changes are being made in that layer.
186 00:18:41.480 ⇒ 00:18:47.620 Demilade Agboola: just to be clear supply chain version is that the same as the revenue version? Or is it different? Logic.
187 00:18:51.560 ⇒ 00:18:57.860 Emily Giant: It’s it’s not different logic. It’s just
188 00:18:59.080 ⇒ 00:19:02.390 Emily Giant: different questions that are being asked. So
189 00:19:03.200 ⇒ 00:19:07.639 Emily Giant: like, for example, I don’t think revenue is gonna care about in transit
190 00:19:08.100 ⇒ 00:19:13.230 Emily Giant: back ordered spoilage, that type of metric.
191 00:19:14.410 ⇒ 00:19:19.220 Emily Giant: But that’s not to say it shouldn’t exist in the same mart table.
192 00:19:26.690 ⇒ 00:19:36.219 Amber Lin: How would this one be done then, or do we need to do this as a separate one? Or should it be built into the current models.
193 00:19:36.380 ⇒ 00:19:38.369 Amber Lin: How should this be done?
194 00:19:40.400 ⇒ 00:19:47.804 Demilade Agboola: No, this will be separate models. Just so that it’s not confusing for people who are utilizing the models.
195 00:19:49.090 ⇒ 00:19:54.800 Demilade Agboola: it would just be in different folders, but, like the folder, will differentiate. What’s
196 00:19:55.940 ⇒ 00:19:58.460 Demilade Agboola: well, to get your inventory up is
197 00:19:58.730 ⇒ 00:20:05.630 Demilade Agboola: supporting. So whether it’s supporting like the supply chain, or just regular inventory.
198 00:20:09.070 ⇒ 00:20:14.039 Amber Lin: So we’re gonna make a different folder that supports the supply chain version.
199 00:20:14.250 ⇒ 00:20:19.240 Amber Lin: We’re gonna make a new model that answers these questions
200 00:20:22.030 ⇒ 00:20:26.369 Amber Lin: is that still low priority, and that’s still 3 points.
201 00:20:32.242 ⇒ 00:20:34.150 Demilade Agboola: Just so we’re on the same page.
202 00:20:34.570 ⇒ 00:20:41.710 Demilade Agboola: Oh, are we building? We’re building 3 inventory models, then, or 3 inventory versions, are we building 2.
203 00:20:42.790 ⇒ 00:20:44.109 Demilade Agboola: So that’s to Emily.
204 00:20:46.010 ⇒ 00:20:51.010 Demilade Agboola: Because the current one we’re not doing is not is not revenue focused. It’s it feels mostly. Yeah.
205 00:20:58.500 ⇒ 00:21:02.729 Demilade Agboola: the current one we’re building. What what would you say? The focus is right now.
206 00:21:04.230 ⇒ 00:21:05.110 Emily Giant: Revenue.
207 00:21:06.470 ⇒ 00:21:10.780 Emily Giant: I don’t know. It’s it’s both like it’s the underpinning of
208 00:21:12.360 ⇒ 00:21:14.837 Emily Giant: both of them. But I guess
209 00:21:17.510 ⇒ 00:21:22.891 Uttam Kumaran: Like do we need? Do we need inventory to go into revenue.
210 00:21:23.340 ⇒ 00:21:26.169 Emily Giant: Yeah, they make all of their.
211 00:21:26.170 ⇒ 00:21:33.000 Uttam Kumaran: Probably not the other way around, right? Because it’s the sale itself. So the sale is going to be post
212 00:21:33.670 ⇒ 00:21:42.657 Uttam Kumaran: supply. So I feel like inventory should probably be. Go first.st
213 00:21:45.090 ⇒ 00:21:45.890 Uttam Kumaran: Secrets.
214 00:21:45.890 ⇒ 00:21:47.080 Emily Giant: Correct. Yeah.
215 00:21:49.350 ⇒ 00:21:52.809 Amber Lin: So what does it mean for the different versions we’re building? Is it just
216 00:21:53.635 ⇒ 00:21:56.650 Amber Lin: this current version? And then a supply chain version.
217 00:21:57.920 ⇒ 00:22:04.610 Emily Giant: In in this instance I would say that we’re building the the supply chain version. Now.
218 00:22:04.830 ⇒ 00:22:05.640 Amber Lin: Oh, really.
219 00:22:05.870 ⇒ 00:22:10.910 Emily Giant: Yeah, and that the revenue version would be
220 00:22:11.020 ⇒ 00:22:14.210 Emily Giant: tied into the next sprint where we’re working on those revenue models.
221 00:22:14.210 ⇒ 00:22:20.490 Amber Lin: Oh, okay, currently, we are building a.
222 00:22:25.630 ⇒ 00:22:30.089 Amber Lin: So this is actually, we should say, revenue version.
223 00:22:34.090 ⇒ 00:22:35.240 Emily Giant: I’m confused now.
224 00:22:35.240 ⇒ 00:22:36.530 Amber Lin: I am also very confused.
225 00:22:36.530 ⇒ 00:22:41.690 Emily Giant: So if we’re talking about the the supply chain version.
226 00:22:42.880 ⇒ 00:22:43.199 Amber Lin: Time, with.
227 00:22:43.200 ⇒ 00:22:48.900 Emily Giant: That’s what Demo Lade has been like doing now, and that
228 00:22:49.810 ⇒ 00:22:55.860 Emily Giant: the revenue version will need to be tied to the shopify sales data. This is not like what we’re doing now is not
229 00:22:56.040 ⇒ 00:23:04.409 Emily Giant: so need a more like comprehensive cross reference of revenue and inventory levels.
230 00:23:05.080 ⇒ 00:23:08.330 Emily Giant: Cause they’re just making totally like different decisions based on.
231 00:23:08.330 ⇒ 00:23:08.880 Amber Lin: Okay.
232 00:23:09.880 ⇒ 00:23:10.526 Amber Lin: I see.
233 00:23:10.850 ⇒ 00:23:11.440 Emily Giant: Yeah.
234 00:23:11.440 ⇒ 00:23:18.050 Amber Lin: I see, I understand. So the current model does it answer these questions about inventory available in transit and back, ordered.
235 00:23:19.620 ⇒ 00:23:20.740 Emily Giant: Yes, it does.
236 00:23:20.740 ⇒ 00:23:21.340 Demilade Agboola: Yes.
237 00:23:21.340 ⇒ 00:23:26.216 Amber Lin: Awesome. So I think what what we actually need is to
238 00:23:26.850 ⇒ 00:23:35.839 Amber Lin: have one that can help us connect the current inventory mart to the future of Revenue Mart that we’re building. So it’s more like a transitory thing.
239 00:23:41.320 ⇒ 00:23:46.090 Amber Lin: I’m sorry. That was a question. Is that is that different interpretation.
240 00:23:46.680 ⇒ 00:23:47.440 Demilade Agboola: Yeah. So
241 00:23:47.440 ⇒ 00:23:55.790 Demilade Agboola: right now, yeah, what we’re doing is, the inventory says, largely focused on, like, how many goods were sold on? How like.
242 00:23:55.890 ⇒ 00:24:07.030 Demilade Agboola: how many where we delivered that kind of thing we’re talking about like the quantity of things. But we’ll need to build a version that focuses on like the
243 00:24:07.180 ⇒ 00:24:09.969 Demilade Agboola: dollar amount associated with the different.
244 00:24:10.970 ⇒ 00:24:11.959 Demilade Agboola: Quantity that has.
245 00:24:11.960 ⇒ 00:24:12.800 Amber Lin: Hmm.
246 00:24:12.800 ⇒ 00:24:19.920 Demilade Agboola: Or it’s like, it’s more, it’s more revenue focused than like the goods that we’re currently looking at.
247 00:24:29.330 ⇒ 00:24:37.660 Amber Lin: so I think this is this is good I’m gonna delete
248 00:24:37.810 ⇒ 00:24:42.670 Amber Lin: these, i’ll say, niece grooming, so would that still be.
249 00:24:43.780 ⇒ 00:24:46.700 Amber Lin: 3 points and low priority.
250 00:24:55.990 ⇒ 00:25:02.140 Demilade Agboola: I wouldn’t say low priority. I’ll probably say right now it’s probably medium. It’s not the highest priority, but it’s not low.
251 00:25:04.630 ⇒ 00:25:05.340 Amber Lin: Points.
252 00:25:06.650 ⇒ 00:25:08.459 Demilade Agboola: Probably not probably 5.
253 00:25:09.020 ⇒ 00:25:12.330 Amber Lin: Okay, great.
254 00:25:12.550 ⇒ 00:25:16.170 Amber Lin: I will do more grooming on that
255 00:25:17.150 ⇒ 00:25:22.619 Amber Lin: great good. I’m glad we cleared that up then that was pretty important.
256 00:25:22.730 ⇒ 00:25:28.599 Amber Lin: Yes, okay, so I have 1, 2.
257 00:25:28.700 ⇒ 00:25:30.690 Amber Lin: Let’s look at. Look at this one.
258 00:25:31.200 ⇒ 00:25:39.310 Amber Lin: I wasn’t sure what this one is. I just know that it was in our backlog, and then I tried my best. This was the original notes it had.
259 00:25:43.930 ⇒ 00:25:44.710 Emily Giant: Yeah.
260 00:25:48.220 ⇒ 00:25:48.980 Emily Giant: Continue.
261 00:25:51.920 ⇒ 00:25:57.769 Demilade Agboola: Yeah, this was this was, you have snapshots for like orders.
262 00:26:00.040 ⇒ 00:26:08.030 Demilade Agboola: And because sometimes Afs goes into negative. And we’re trying to figure out like that period in which certain things happen so.
263 00:26:08.810 ⇒ 00:26:12.209 Demilade Agboola: We wanted to have a snapshot for that, if I remember correctly.
264 00:26:12.430 ⇒ 00:26:24.339 Emily Giant: Yup and for optimal shipping analysis, our outbound transportation team needs to figure out like at what point skews are going out of stock, so that
265 00:26:24.950 ⇒ 00:26:35.219 Emily Giant: when an order is shipped non-optimally, it’s what the cause is, whether it’s like allocation of inventory or a system problem.
266 00:26:36.260 ⇒ 00:26:39.770 Amber Lin: Yeah, faulty shipping.
267 00:26:40.180 ⇒ 00:26:41.339 Amber Lin: Is that true?
268 00:26:42.220 ⇒ 00:26:51.519 Amber Lin: Find the root cause of okay priority levels and point estimates.
269 00:26:53.000 ⇒ 00:26:53.830 Emily Giant: Hmm!
270 00:26:59.010 ⇒ 00:27:03.650 Emily Giant: I don’t have a lot of background on these Duma Laude, so I trust you.
271 00:27:09.080 ⇒ 00:27:12.500 Demilade Agboola: I’ll probably say, let’s do say medium.
272 00:27:12.780 ⇒ 00:27:20.730 Demilade Agboola: It’s not necessarily the most important thing right now on our plate, so we’ll say medium priority, and then.
273 00:27:21.950 ⇒ 00:27:25.580 Demilade Agboola: in terms of time, let’s do 5.
274 00:27:32.550 ⇒ 00:27:42.460 Amber Lin: Sounds good scoot, that one over and then last few is on documentation. So
275 00:27:43.650 ⇒ 00:27:51.129 Amber Lin: documenting the lineage and also adding inline comments, so that people that come can understand it.
276 00:27:51.690 ⇒ 00:28:02.199 Amber Lin: So, okay, is this one still low priority? Does it take 2 points.
277 00:28:04.520 ⇒ 00:28:07.229 Demilade Agboola: I mean, it’s still a low priority, but I think you’ll take one on 2 points.
278 00:28:07.230 ⇒ 00:28:10.739 Amber Lin: Okay, so that would take 3 or 5.
279 00:28:12.084 ⇒ 00:28:14.840 Demilade Agboola: So I’m not sure. Let’s see, let’s see
280 00:28:15.030 ⇒ 00:28:23.737 Demilade Agboola: 5, because we’re going to be documenting everything that like we’ve been working on. And so it’s like the definition of things. It’s going to be
281 00:28:25.030 ⇒ 00:28:27.540 Demilade Agboola: Should I do logic join this.
282 00:28:28.360 ⇒ 00:28:35.830 Amber Lin: Merge these 2 tickets as well, or is, are they separate.
283 00:28:38.930 ⇒ 00:28:45.779 Demilade Agboola: I mean, they’re kind of this. This is done while building, though, like, you know, the online comments.
284 00:28:46.457 ⇒ 00:28:50.199 Amber Lin: I don’t. Necessarily, I don’t actually think this is like its own individual task
285 00:28:50.487 ⇒ 00:29:03.999 Amber Lin: I think this is like a more of a last check to make sure everything has it and add anything that’s missing. I kinda knew that you were doing that while we’re building, but just in case we miss anything. This is like a last check.
286 00:29:05.610 ⇒ 00:29:09.150 Demilade Agboola: Yeah. So for a check. Yeah, we could just do this as like a 3 point task.
287 00:29:09.550 ⇒ 00:29:10.343 Emily Giant: But I’m.
288 00:29:14.056 ⇒ 00:29:14.809 Amber Lin: This one.
289 00:29:14.810 ⇒ 00:29:17.060 Demilade Agboola: Scoring you through points. Yeah, scoring you through points.
290 00:29:17.300 ⇒ 00:29:18.080 Amber Lin: Okay.
291 00:29:18.080 ⇒ 00:29:19.260 Demilade Agboola: Assign.
292 00:29:23.700 ⇒ 00:29:26.490 Amber Lin: Priority, still low or.
293 00:29:26.830 ⇒ 00:29:28.109 Demilade Agboola: Yeah, we’ll tittle off.
294 00:29:28.110 ⇒ 00:29:28.690 Amber Lin: Okay.
295 00:29:29.460 ⇒ 00:29:30.750 Amber Lin: Sounds good.
296 00:29:32.120 ⇒ 00:29:36.620 Amber Lin: Similarly, for this one, you said it was gonna be 5 points.
297 00:29:38.610 ⇒ 00:29:39.320 Demilade Agboola: Yeah.
298 00:29:40.240 ⇒ 00:29:45.260 Amber Lin: Okay, is there anything here that we need to add.
299 00:29:55.760 ⇒ 00:29:59.129 Demilade Agboola: Maybe evt documentation as well.
300 00:29:59.460 ⇒ 00:30:00.000 Amber Lin: Hmm!
301 00:30:03.570 ⇒ 00:30:05.760 Amber Lin: Great low priority.
302 00:30:06.040 ⇒ 00:30:10.670 Amber Lin: I’ll move that fantastic
303 00:30:11.691 ⇒ 00:30:18.379 Amber Lin: this one is also related to the stakeholders. So we we will have. I want to have
304 00:30:18.730 ⇒ 00:30:24.379 Amber Lin: weekly meetings with the stakeholders, especially for inventory as we
305 00:30:24.580 ⇒ 00:30:45.690 Amber Lin: come to the end of developing for inventory, and we’ll onboard them on how the logic is built, and also how they can use the stuff we built. So where to find things, how to use it, what things actually mean. So that probably would take a few working sessions or just presentations, and then working sessions to walk them through.
306 00:30:49.100 ⇒ 00:30:49.740 Emily Giant: Good.
307 00:30:49.900 ⇒ 00:30:53.062 Amber Lin: Yeah, I think it’s high priority.
308 00:30:53.710 ⇒ 00:31:06.339 Amber Lin: I wanted to know what you guys think. And also how long, especially how long this would take you guys what we think. We’ll get people on boarded and confident to use the stuff that we built.
309 00:31:10.304 ⇒ 00:31:14.430 Emily Giant: I don’t think it’s gonna take them that long because they’ve been so involved.
310 00:31:14.760 ⇒ 00:31:19.740 Emily Giant: So the build that we did before mother’s day.
311 00:31:20.680 ⇒ 00:31:24.959 Emily Giant: So well, if we’re talking other users like, what
312 00:31:25.300 ⇒ 00:31:32.359 Emily Giant: are we talking just analysts? Or is it like anyone in the organization that’s using looker and using reports.
313 00:31:33.092 ⇒ 00:31:47.240 Amber Lin: I guess everyone affected by the inventory march. We can start by the priority people, which definitely will be Perry and Felipe, and then the next wrong would be Pk. And Jesse, and and then, whoever
314 00:31:47.570 ⇒ 00:31:52.919 Amber Lin: their tasks relates to inventory that might be needed. But we’ll go in a priority order.
315 00:31:53.370 ⇒ 00:31:54.170 Emily Giant: Okay.
316 00:31:55.910 ⇒ 00:32:00.129 Emily Giant: Hmm, cause there are definitely like, non analyst.
317 00:32:00.790 ⇒ 00:32:07.008 Emily Giant: Like more tertiary stakeholders that do use these dashboards. And
318 00:32:08.150 ⇒ 00:32:12.160 Emily Giant: I’m trying to understand. If like at this point, we would be involving them.
319 00:32:13.960 ⇒ 00:32:16.550 Emily Giant: Or if that would be Perry and Felipe
320 00:32:17.040 ⇒ 00:32:19.589 Emily Giant: communicating it to them at that point.
321 00:32:19.590 ⇒ 00:32:21.510 Amber Lin: I think that would be the best way.
322 00:32:21.510 ⇒ 00:32:22.940 Emily Giant: Okay, that’s fine.
323 00:32:23.050 ⇒ 00:32:23.850 Emily Giant: Okay?
324 00:32:24.350 ⇒ 00:32:25.200 Amber Lin: Sounds good.
325 00:32:25.960 ⇒ 00:32:36.270 Amber Lin: Move that perfect we’re done with inventory. I’ll go groom those 2, and
326 00:32:37.780 ⇒ 00:32:44.399 Amber Lin: I want to look at. I just want to show you guys what it looks like in revenue right now. But I want us to groom
327 00:32:45.960 ⇒ 00:32:51.432 Amber Lin: a a bit of this, then finish off redshift and looker.
328 00:32:52.230 ⇒ 00:33:01.420 Amber Lin: So this one essentially the next next phase, we’re gonna do the audit. So I think because we don’t have much time left today.
329 00:33:01.921 ⇒ 00:33:09.649 Amber Lin: We can just make sure that everything in the audit is looking good. So we have tickets that we can move into.
330 00:33:10.597 ⇒ 00:33:12.240 Amber Lin: The next cycle.
331 00:33:15.540 ⇒ 00:33:21.140 Amber Lin: So what we have. This cycle is to set up the model, the March scaffolding
332 00:33:22.075 ⇒ 00:33:31.190 Amber Lin: to do the audit for orders, and then guess we can go through.
333 00:33:31.500 ⇒ 00:33:41.869 Amber Lin: Go through these ones. My 1st question is, is this breakdown valid for auditing? So we have orders, subscriptions, discounts, refunds, transactions.
334 00:33:44.260 ⇒ 00:33:51.620 Demilade Agboola: I would say, like, based off the work we’re doing. It’s not as it’s. It’s kind of out of scope in the sense that, like
335 00:33:51.960 ⇒ 00:33:57.989 Demilade Agboola: we’ve had to do a bunch of that I think, minus maybe discounts.
336 00:33:58.920 ⇒ 00:33:59.550 Emily Giant: Yeah, and.
337 00:34:00.240 ⇒ 00:34:08.210 Emily Giant: Think good credits, and I guess that can be lumped into discounts like gift cards, credits.
338 00:34:09.520 ⇒ 00:34:13.119 Emily Giant: and like loyalty points deprecated.
339 00:34:13.659 ⇒ 00:34:17.780 Emily Giant: But those can, I think, go into those categories of audit.
340 00:34:20.560 ⇒ 00:34:21.610 Amber Lin: So
341 00:34:22.060 ⇒ 00:34:29.900 Amber Lin: sorry, should I still break it down in term in like these tickets, or is there a different breakdown that we want to use.
342 00:34:37.130 ⇒ 00:34:38.150 Demilade Agboola: I think we can.
343 00:34:41.329 ⇒ 00:34:45.301 Caio Velasco: Can I say, Oh, yeah, go go ahead. Go ahead.
344 00:34:46.210 ⇒ 00:34:48.766 Demilade Agboola: I was gonna say, yeah, we could probably like
345 00:34:50.389 ⇒ 00:34:54.279 Demilade Agboola: So things like transactions, things like subscriptions.
346 00:34:54.280 ⇒ 00:34:54.860 Amber Lin: Hmm.
347 00:34:57.209 ⇒ 00:35:04.007 Demilade Agboola: they’re still going to. We’re still gonna have to look at them in their own way, cause I know we haven’t really looked at transactions. To be honest.
348 00:35:04.919 ⇒ 00:35:08.009 Demilade Agboola: we have looked at orders.
349 00:35:08.159 ⇒ 00:35:14.259 Demilade Agboola: but like, yes, so subscriptions refunds, discounts. Yeah, I think right now as they are, they kind of
350 00:35:16.449 ⇒ 00:35:20.329 Demilade Agboola: in the in their own important like categories, and
351 00:35:20.689 ⇒ 00:35:22.869 Demilade Agboola: I think that that will be fine, for now.
352 00:35:24.660 ⇒ 00:35:28.179 Amber Lin: So transactions and orders. You said, we already looked at.
353 00:35:29.824 ⇒ 00:35:32.669 Demilade Agboola: Transactions, not as much orders definitely.
354 00:35:32.950 ⇒ 00:35:40.560 Amber Lin: Oh, okay, okay. Should this? I? Sorry. I didn’t know that. Should that still be in cycle? Then.
355 00:35:45.420 ⇒ 00:35:46.139 Demilade Agboola: Because I know there are.
356 00:35:46.140 ⇒ 00:35:55.580 Amber Lin: You looked at it, and right now it’s assigned to Kyle. So it’s everything documented so that we can hand off to Kyle, or should I?
357 00:35:56.066 ⇒ 00:35:59.880 Amber Lin: Should we move it to the next cycle? How should we.
358 00:36:01.603 ⇒ 00:36:05.953 Demilade Agboola: So in terms of documentation, yeah, it’s not documented.
359 00:36:07.890 ⇒ 00:36:17.760 Demilade Agboola: well, I mean, there is a little bit of documentation, but it’s not the most like thorough document cause. I was trying to be able to move quickly, to be able to get things out.
360 00:36:18.160 ⇒ 00:36:18.680 Amber Lin: Yeah.
361 00:36:24.440 ⇒ 00:36:29.039 Demilade Agboola: and that’s kind of what has power. Some of the restructuring that is currently going on.
362 00:36:30.835 ⇒ 00:36:32.105 Demilade Agboola: But yeah.
363 00:36:33.560 ⇒ 00:36:38.689 Amber Lin: So what is the best way to say? Hand off or divide tasks.
364 00:36:39.640 ⇒ 00:36:42.168 Caio Velasco: Oh, can can I ask a question in that?
365 00:36:43.140 ⇒ 00:36:52.780 Caio Velasco: So the the scaffold, as I understand, would be myself going into the to the main model
366 00:36:52.930 ⇒ 00:37:10.529 Caio Velasco: and then understanding what is the revenue equation. So if the revenue equation has like 10 items, you would have 10 of the items there, that’s what I’m understanding. Does that make sense? Because, for example, if orders or transactions, something has been done, still, I have to understand them. If they are part of it.
367 00:37:10.660 ⇒ 00:37:18.970 Caio Velasco: If subscriptions or discounts, or anything else, is part of the equation which I would just know exposed meaning after I do the work.
368 00:37:19.190 ⇒ 00:37:25.980 Caio Velasco: so this can be also changing, and I’m assuming that those things are already known by Emily and
369 00:37:26.546 ⇒ 00:37:38.119 Caio Velasco: but then I think we can start with some of them which is already understood, and then I can study them. But probably there will be others, or less. It doesn’t make sense. Am I understanding what is happening.
370 00:37:40.665 ⇒ 00:38:04.064 Amber Lin: I can chime in a little bit about how this ticket was originally created. And then you guys can comment on if we still want this ticket, or if we have a different way, we want to do things. So I made this ticket so that we define the overall structure of the revenue mark that we will be building. So to have the different staging models, and to have the different
371 00:38:04.880 ⇒ 00:38:14.169 Amber Lin: the joints that that would be happening, or the different marts or segments that we might have. Just the overall skeleton of
372 00:38:14.320 ⇒ 00:38:19.459 Amber Lin: what we’re building towards. So this is more of having, like
373 00:38:20.110 ⇒ 00:38:25.887 Amber Lin: Dbt best practices. Generally, how revenue is
374 00:38:26.810 ⇒ 00:38:31.110 Amber Lin: the different categories under revenue, and how that would look like. So
375 00:38:31.440 ⇒ 00:38:40.299 Amber Lin: we know what the elements we need to rebuild are. But I want to hear you guys opinions on this. If this is the right way, we should go.
376 00:38:44.420 ⇒ 00:38:46.597 Demilade Agboola: Yeah, I think that sounds good.
377 00:38:47.750 ⇒ 00:38:53.209 Demilade Agboola: I mean, some things are intertwined like because of, you know, inventory and some things that come from
378 00:38:55.640 ⇒ 00:38:58.059 Demilade Agboola: like some of these tables, as well.
379 00:38:58.540 ⇒ 00:39:01.469 Demilade Agboola: It’s not like. It’s not completely.
380 00:39:02.320 ⇒ 00:39:10.000 Demilade Agboola: It won’t be completely new in that regard. Because for inventory like you start to go into like orders, and figure out from that.
381 00:39:10.140 ⇒ 00:39:19.650 Demilade Agboola: or from quantity sold for inventory comes from transactions, so there will still be some overlap.
382 00:39:20.510 ⇒ 00:39:25.779 Demilade Agboola: However, yes, I think this this would cover everything that needs to be done for revenue.
383 00:39:36.100 ⇒ 00:39:41.220 Amber Lin: Okay, Kyle, does that make sense? Does that make sense to you, or do you
384 00:39:41.820 ⇒ 00:39:46.850 Amber Lin: Do you have any questions, or are you clear on what needs to be done for this ticket.
385 00:39:46.850 ⇒ 00:40:11.069 Caio Velasco: Yeah, no, I think so. I think so. Basically like going to the revenue mark or table, the most important one. And then, you know revenue is price, times quantity, and that’s it. And then where is price? Where is quantity? And then it starts to get, you know, crazy, because there is a lot of things inside. So these things will be discovered anyway. But of course it’s like, it’s good to know beforehand that those things exist already, like orders. Transaction refund, discount.
386 00:40:11.180 ⇒ 00:40:17.029 Caio Velasco: but I think this would cover it all and definitely, not 2 points. This could be a month of work. I don’t know.
387 00:40:17.260 ⇒ 00:40:24.989 Caio Velasco: It just really depends on how easy they are to find and to understand. But it seems to be covering everything.
388 00:40:26.174 ⇒ 00:40:43.769 Amber Lin: Well, my initial, my initial view was that this wouldn’t take very long, because this is more of defining the structure. It doesn’t need too much of a step by step. Audit. I was thinking more of this as a top down approach to look at
389 00:40:44.303 ⇒ 00:40:55.140 Amber Lin: the overall end goal of how we want to structure things. And then we can split up the audit tasks by categories based on the scaffolding that we define
390 00:40:55.631 ⇒ 00:41:02.310 Amber Lin: or do the rebuilds from for each for each section as we define it. Because I don’t want.
391 00:41:02.860 ⇒ 00:41:13.450 Amber Lin: I don’t want us to have a say auditing task that goes on for a month like, I want it to be very granular that we can say, okay, we did task one. We’re gonna do task 2. So
392 00:41:15.480 ⇒ 00:41:16.380 Amber Lin: like
393 00:41:16.560 ⇒ 00:41:22.929 Amber Lin: I I guess that was my question of. Is that a reasonable approach to just do a top down
394 00:41:23.070 ⇒ 00:41:25.070 Amber Lin: bird’s eye view? First.st
395 00:41:28.270 ⇒ 00:41:37.010 Caio Velasco: Yes, but I still can’t see how it wouldn’t take long, because everything you have to understand you have to look for the whole lineage somehow.
396 00:41:37.722 ⇒ 00:41:49.969 Caio Velasco: And this could be easy or not depends on where things are. Theoretically, if we are helping them, is because things are complex and maybe disorganized, or whatever the reason is.
397 00:41:50.417 ⇒ 00:42:09.150 Caio Velasco: And the scaffolding can be in this in the way you’re putting it, as if we already know where they are, but I don’t think we do. So maybe that’s the the situation we can start and like, put some hours like something close as you proposing, and then see what we can do. And then we iterate.
398 00:42:10.300 ⇒ 00:42:13.059 Amber Lin: I guess that’s for Don Latte and Emily.
399 00:42:13.270 ⇒ 00:42:33.589 Amber Lin: do you guys think this is? This is the best way for us to spend Kyle’s time, or should we? Should I scrap this? And we make another another way that we do, auditing that like we can break it down to smaller chunks of tickets like each, like less than less than 5 points.
400 00:42:33.590 ⇒ 00:42:37.259 Emily Giant: Yeah, I think there’s gonna be a lot of discovery along the way in this one.
401 00:42:37.660 ⇒ 00:42:42.449 Emily Giant: To Kyle’s point, and it might be best to just scrap this one and break it down into like
402 00:42:44.230 ⇒ 00:42:46.470 Emily Giant: smaller units as opposed.
403 00:42:46.470 ⇒ 00:42:46.890 Amber Lin: Okay.
404 00:42:46.890 ⇒ 00:42:54.300 Emily Giant: Trying to figure out what we want, and then discovering all this junk along the way, and having to rewrite this a bunch of times.
405 00:42:54.510 ⇒ 00:42:57.420 Amber Lin: Okay. What do you? What do you think?
406 00:42:57.420 ⇒ 00:43:08.219 Demilade Agboola: I was. Gonna say, isn’t this like tied? This scaffolding also tied to the audits that we broke down for like discounts and refunds and subscriptions and transactions.
407 00:43:09.900 ⇒ 00:43:12.110 Demilade Agboola: because I would assume that, like
408 00:43:13.210 ⇒ 00:43:18.179 Demilade Agboola: those, will tie into this scaffolding for the revenue mark
409 00:43:22.300 ⇒ 00:43:35.180 Demilade Agboola: because they effectively revenue is just a bunch of all these things put together like what’s going on with subscriptions? What’s going on with transactions? What’s going on with orders? What’s going on? Refunds? What’s going on with discounts. That sort of thing.
410 00:43:35.864 ⇒ 00:43:39.259 Demilade Agboola: So if we have those audits tickets already.
411 00:43:40.254 ⇒ 00:43:46.989 Demilade Agboola: it will be putting things together to be able to have the final house, which is, you know, revenue
412 00:43:47.460 ⇒ 00:44:01.229 Demilade Agboola: revenue. The revenue scaffold, and those tickets were audit tickets. So the idea was not to necessarily build out anything but to like audit, and understand what was going on in each of those individual domains.
413 00:44:07.210 ⇒ 00:44:13.420 Amber Lin: I think that’s for Kyle and Emily to respond. I want us to all be aligned. So I’ll put the
414 00:44:13.780 ⇒ 00:44:15.320 Amber Lin: we want to do.
415 00:44:15.320 ⇒ 00:44:24.139 Caio Velasco: No, it makes sense what, Daniel I just said like I don’t. I just think that, for example, if I had this desk alone, and someone like, Hey, I want help with this. Can you help me find rep?
416 00:44:24.350 ⇒ 00:44:48.559 Caio Velasco: The 1st thing I would do is, how is the order made? And what is the whole process with the all the potential things that can happen along the way? And each note of that process would give me an idea. So oh, here there is a refund. Oh, here there is a discount, if those are the only ones. Refund, discount and subscription. Okay, cool. But we might find also other. We can break down by them.
417 00:44:48.560 ⇒ 00:45:04.530 Caio Velasco: so that I already know that they exist, and then I’ll have to go inside each one of them and see what I can. What I can find. But theoretically, before this, the most important thing to know is, how does the order happen? And then I can also work. Do the working session with Emily, or something like that.
418 00:45:04.920 ⇒ 00:45:08.770 Caio Velasco: but I think breaking out by them. It’s it’s it’s a good attempt already.
419 00:45:15.850 ⇒ 00:45:22.900 Amber Lin: Okay, okay, team. Help me help me look at this, then. So what should I scrap this one?
420 00:45:23.100 ⇒ 00:45:27.679 Amber Lin: Should I keep it? Are we? How are we gonna approach these audits?
421 00:45:28.230 ⇒ 00:45:29.970 Amber Lin: Can we of them take.
422 00:45:30.380 ⇒ 00:45:36.620 Demilade Agboola: Can we link all the audits to the initial like model scaffold tickets.
423 00:45:36.620 ⇒ 00:45:37.480 Amber Lin: Sure.
424 00:45:37.720 ⇒ 00:45:44.419 Emily Giant: That was going to be my suggestion, just making those like nested so that we understand those are the pieces of
425 00:45:44.850 ⇒ 00:45:46.620 Emily Giant: defining the scaffold.
426 00:45:47.440 ⇒ 00:45:48.150 Caio Velasco: Perfect.
427 00:45:48.150 ⇒ 00:45:57.179 Amber Lin: Okay. So I would say, this is a meta does that?
428 00:45:58.300 ⇒ 00:46:00.769 Amber Lin: I mean, I can. I guess I can, delete.
429 00:46:01.780 ⇒ 00:46:05.870 Amber Lin: I guess we don’t have to have this. That’s that’s also like a meta one.
430 00:46:21.060 ⇒ 00:46:25.739 Amber Lin: Okay, actually, let me.
431 00:46:31.140 ⇒ 00:46:35.880 Amber Lin: I will just copy and paste these over.
432 00:46:36.840 ⇒ 00:46:42.690 Amber Lin: I will say, that’s a duplicate. Okay.
433 00:46:46.390 ⇒ 00:46:52.240 Amber Lin: so are these still good points for the audit?
434 00:46:54.040 ⇒ 00:46:56.280 Amber Lin: I’m gonna see?
435 00:46:56.540 ⇒ 00:46:57.609 Amber Lin: That’s okay.
436 00:47:00.500 ⇒ 00:47:06.430 Amber Lin: Are these still good point point estimates? I’m gonna move that one out?
437 00:47:10.550 ⇒ 00:47:11.939 Amber Lin: For orders?
438 00:47:12.760 ⇒ 00:47:17.489 Amber Lin: Is it still good with 3 points? And what is the priority?
439 00:47:18.521 ⇒ 00:47:20.629 Amber Lin: I guess. Same for transactions.
440 00:47:23.140 ⇒ 00:47:25.359 Emily Giant: I think that because we’re going to
441 00:47:25.970 ⇒ 00:47:36.090 Emily Giant: is subbing in shopify tables instead of the existing tables, these might all take longer, like ideally, we would be using
442 00:47:36.280 ⇒ 00:47:39.920 Emily Giant: like completely new sources.
443 00:47:40.780 ⇒ 00:47:46.489 Emily Giant: not even ideally. But we need to audit that. That’s that needs to be part of the discovery here.
444 00:47:48.230 ⇒ 00:47:56.980 Amber Lin: So we should also audit shopify sources.
445 00:47:59.280 ⇒ 00:48:00.160 Emily Giant: Yes.
446 00:48:00.160 ⇒ 00:48:00.780 Amber Lin: Okay,
447 00:48:05.480 ⇒ 00:48:13.899 Amber Lin: I guess. What is the clear? How long would each of those smaller tasks take? And then I guess we can sum it up to a bigger one.
448 00:48:15.710 ⇒ 00:48:18.239 Amber Lin: I think, Demo, I already did this one.
449 00:48:21.980 ⇒ 00:48:26.970 Demilade Agboola: I I wouldn’t say document identified, and like I I mean, there’s have a sheet.
450 00:48:27.200 ⇒ 00:48:30.579 Demilade Agboola: But like it’s more of how do I put it. It’s more of like my
451 00:48:32.330 ⇒ 00:48:37.590 Demilade Agboola: crappy paper, like a thought process, which I mean I can always like flesh out.
452 00:48:38.180 ⇒ 00:48:47.959 Demilade Agboola: But it’s not like properly, properly documented in like sense of like. Oh, I could. We could hand it over to open stems to use. It’s kind of how I did it to be able to start work.
453 00:48:47.960 ⇒ 00:48:48.350 Amber Lin: Okay.
454 00:48:48.350 ⇒ 00:48:50.244 Demilade Agboola: On some of these things that
455 00:48:50.560 ⇒ 00:48:51.080 Amber Lin: Hmm.
456 00:48:51.910 ⇒ 00:48:56.729 Demilade Agboola: You know, and I, so far it’s been quite hard. I know. I know Emi has started like looking at them and using them.
457 00:48:56.870 ⇒ 00:49:06.189 Demilade Agboola: So. But yeah, just being able to now have that in terms of documentation that, like the urban sense team can use, would probably is a different task.
458 00:49:06.710 ⇒ 00:49:09.970 Amber Lin: Oh, yeah, I I think what I meant is more so.
459 00:49:10.660 ⇒ 00:49:12.420 Amber Lin: Can we have something
460 00:49:12.770 ⇒ 00:49:18.776 Amber Lin: to give to Kyle? So he doesn’t have to start from ground 0 like, is there something that
461 00:49:19.730 ⇒ 00:49:26.470 Amber Lin: Kyle can read to help him understand what what you already know about the orders.
462 00:49:28.380 ⇒ 00:49:29.550 Demilade Agboola: Oh, man.
463 00:49:30.350 ⇒ 00:49:42.479 Demilade Agboola: yes, there’s some things we can put like I can put together for him, and also well, that kind of goes out the window. If we’re going to be putting in new sources like Emily just mentioned.
464 00:49:42.900 ⇒ 00:49:46.520 Demilade Agboola: So if new sources are coming in like that, that kind of
465 00:49:47.380 ⇒ 00:49:49.759 Demilade Agboola: isn’t the most helpful anymore. Because.
466 00:49:49.760 ⇒ 00:49:50.080 Amber Lin: Okay.
467 00:49:50.080 ⇒ 00:49:51.340 Demilade Agboola: You know sources? Yeah.
468 00:49:51.630 ⇒ 00:49:53.090 Amber Lin: Okay, I see.
469 00:49:53.953 ⇒ 00:49:57.970 Amber Lin: How long would the shopify sources take.
470 00:50:00.535 ⇒ 00:50:09.404 Emily Giant: I don’t think terribly long, because what them a lot and I have been working with is like our Frankenstein of shopify tables
471 00:50:09.950 ⇒ 00:50:31.460 Emily Giant: through like this soligo flow that we’ve tried to like, manipulate what’s there. So they’re really similar to what’s already in existence. But it would be ideal to like, have it not go through that soligo flow? We might audit it and decide that it’s actually better for us to rely on the tables. But there are certain ones that like
472 00:50:32.270 ⇒ 00:50:42.730 Emily Giant: for discounts and subscriptions and loyalty points that we can’t use anymore, because they have never worked since the migration. It’s hard to say but
473 00:50:43.050 ⇒ 00:50:49.830 Emily Giant: it’s I guess. What? What is the specific thing that we’re trying to
474 00:50:50.300 ⇒ 00:50:53.589 Emily Giant: put a timeline on with the shopify tables just like getting
475 00:50:54.810 ⇒ 00:50:57.379 Emily Giant: familiar with them, and how, and.
476 00:50:57.970 ⇒ 00:50:59.340 Amber Lin: How it goes.
477 00:50:59.340 ⇒ 00:51:08.450 Amber Lin: Guess for an audit of knowing where things are, what they are, and how we will use them.
478 00:51:09.330 ⇒ 00:51:15.050 Emily Giant: That will take probably like 3 to 5 points.
479 00:51:17.690 ⇒ 00:51:20.390 Emily Giant: I would think not much more than that, though.
480 00:51:21.120 ⇒ 00:51:21.650 Amber Lin: Okay.
481 00:51:21.650 ⇒ 00:51:32.249 Emily Giant: Lot a lot of documentation out there about shopify schema. So that was cool, lovely package. There’s like
482 00:51:32.680 ⇒ 00:51:40.919 Emily Giant: more like 5 tran oriented. But you can definitely like, use the compiled code to as a base for.
483 00:51:41.890 ⇒ 00:51:42.910 Emily Giant: Or a lot.
484 00:51:43.430 ⇒ 00:51:44.860 Amber Lin: I see, I see.
485 00:51:45.140 ⇒ 00:51:55.910 Amber Lin: so I don’t know if this can be completed. This cycle. I do think if we manage to finish most of the
486 00:51:56.840 ⇒ 00:52:04.600 Amber Lin: deprecation stuff by Thursday or later Thursday. I think we still have time, Friday and Monday, to look at this one.
487 00:52:04.750 ⇒ 00:52:12.410 Amber Lin: and if it takes, say 3 to 5 points. That’s the like. That’s Max a day. So we should be able to have something.
488 00:52:15.420 ⇒ 00:52:23.029 Amber Lin: I know we have 5 min left. Can I get a priority ranking among these audit items.
489 00:52:23.250 ⇒ 00:52:24.450 Amber Lin: including that.
490 00:52:28.230 ⇒ 00:52:37.920 Emily Giant: I would say from my perspective. Probably transactions would be first.st
491 00:52:39.160 ⇒ 00:52:41.410 Emily Giant: And then discounts.
492 00:52:46.200 ⇒ 00:52:47.730 Emily Giant: and then refunds.
493 00:52:51.660 ⇒ 00:52:58.739 Emily Giant: And subscriptions. I just have this feeling that it’s going to have to be like moved out of this discovery phase because it’s a different.
494 00:52:59.508 ⇒ 00:53:05.490 Emily Giant: It’s a different system entirely that we don’t have currently, like integrated in our.
495 00:53:05.490 ⇒ 00:53:06.000 Amber Lin: Right.
496 00:53:06.400 ⇒ 00:53:08.699 Emily Giant: Dbt. In redshift. Nothing.
497 00:53:18.220 ⇒ 00:53:22.580 Amber Lin: How are we tracking? It? Then like, how is that? How is that working.
498 00:53:24.080 ⇒ 00:53:31.999 Emily Giant: Not? Well, they’re doing a lot of work in like the native software program reporting. So they’re doing a lot of like sheets
499 00:53:32.190 ⇒ 00:53:32.760 Emily Giant: stuff.
500 00:53:33.320 ⇒ 00:53:44.579 Emily Giant: And then I have, like Frankenstein, logic with what I am able to pull and lots of assumptions. But it’s really going to get skewed over time because of the amount of assumptions.
501 00:53:44.580 ⇒ 00:53:51.369 Amber Lin: I see I see that sounds pretty important. It just sounds a lot harder.
502 00:53:51.370 ⇒ 00:53:58.711 Emily Giant: Yeah, it’s pretty. It’s pretty messy. I’ve been avoiding it because we don’t have the
503 00:53:59.430 ⇒ 00:54:01.969 Emily Giant: There really isn’t a way without
504 00:54:04.540 ⇒ 00:54:09.069 Emily Giant: integrating the data from loop. Our subscriptions provider.
505 00:54:09.670 ⇒ 00:54:17.820 Emily Giant: Into redshift and we’ve been talking about switching providers. So I’ve been like really avoiding it on the chance that we might
506 00:54:17.940 ⇒ 00:54:21.659 Emily Giant: need to scrap swoop stuff as soon as we.
507 00:54:22.350 ⇒ 00:54:24.870 Emily Giant: Do it because we’re getting a new provider.
508 00:54:24.870 ⇒ 00:54:30.910 Amber Lin: When is the latest date that loop might be switched was I remember it was like August.
509 00:54:31.070 ⇒ 00:54:38.410 Emily Giant: I think so. Yeah, it’s coming up, and I doubt we will like the closer we get to August without a decision, the more likely stay with them.
510 00:54:38.900 ⇒ 00:54:56.159 Amber Lin: I see I mean, the least we can do is at least look at the current spreadsheets and stuff we are using, and talk about how bad it is, or to get to give like a sense to us, so we can inform our decision better of. Are we? Should we switch from loop.
511 00:54:57.100 ⇒ 00:54:57.750 Emily Giant: Yes.
512 00:54:57.750 ⇒ 00:54:58.850 Amber Lin: Okay, so.
513 00:54:58.850 ⇒ 00:55:04.439 Emily Giant: So a lot of the subscription work. I would I would really pull that out of that.
514 00:55:05.500 ⇒ 00:55:12.530 Emily Giant: I know it’s definitely revenue affecting, and is a huge component, but it’s.
515 00:55:12.530 ⇒ 00:55:13.110 Amber Lin: Hmm.
516 00:55:13.110 ⇒ 00:55:18.110 Emily Giant: To be its own subset of work.
517 00:55:21.320 ⇒ 00:55:28.149 Amber Lin: so if we ever did get the data from loop, that will be we will put that into the dbt revenue mark.
518 00:55:28.380 ⇒ 00:55:29.070 Emily Giant: Yes.
519 00:55:29.070 ⇒ 00:55:35.249 Amber Lin: Okay. But before we do that, we need to go audit the loop data.
520 00:55:36.510 ⇒ 00:55:40.710 Emily Giant: Yes or figure out what it would take to integrate.
521 00:55:41.440 ⇒ 00:55:43.549 Emily Giant: It is redshift, compatible. All that.
522 00:55:45.120 ⇒ 00:55:45.950 Amber Lin: I have.
523 00:55:45.950 ⇒ 00:55:47.010 Emily Giant: No clue.
524 00:55:51.120 ⇒ 00:55:56.060 Amber Lin: but it has to be an outstanding ticket for a long time from stakeholders. So I see
525 00:55:56.600 ⇒ 00:56:02.629 Amber Lin: I, guess demo and Kyle, should we? Should we just take on that task?
526 00:56:02.780 ⇒ 00:56:08.269 Amber Lin: Oh, I can make a separate ticket for that. I think that’s pretty important for us to do
527 00:56:08.560 ⇒ 00:56:09.710 Amber Lin: as well.
528 00:56:11.340 ⇒ 00:56:17.899 Demilade Agboola: What you mean, redshift compatible? Is it suitable ingesting it into redshift? Or do that redshift compatible? Okay.
529 00:56:21.780 ⇒ 00:56:23.690 Emily Giant: We have had our programs.
530 00:56:24.320 ⇒ 00:56:27.659 Emily Giant: It’s the ingested, always. My first.st
531 00:56:29.560 ⇒ 00:56:32.289 Demilade Agboola: Sir, you you were cutting out. I didn’t hear what you said.
532 00:56:32.290 ⇒ 00:56:44.429 Emily Giant: Oh, we’ve had software programs in the past where redshift was not able to ingest any of the data. So I haven’t even asked the basic questions from loop, because it’s just not
533 00:56:44.820 ⇒ 00:56:47.779 Emily Giant: made it to like priority standing yet.
534 00:56:48.520 ⇒ 00:56:50.389 Emily Giant: There’s a lot of discovery there.
535 00:56:50.610 ⇒ 00:56:59.070 Amber Lin: I see. So I’ll say that it is blocking the walking.
536 00:56:59.360 ⇒ 00:57:05.609 Amber Lin: the subscriptions. One. So I’ll mark it as high priority that so that we remember
537 00:57:05.950 ⇒ 00:57:09.710 Amber Lin: to do that? How many points do you think that would be.
538 00:57:13.210 ⇒ 00:57:16.210 Emily Giant: Not very many. I don’t think. Probably like 2.
539 00:57:17.390 ⇒ 00:57:19.180 Amber Lin: Okay, that’s awesome.
540 00:57:20.400 ⇒ 00:57:29.500 Amber Lin: Okay, we are over in time. Just to give you guys a sense of what’s left. So we have some stuff left in
541 00:57:30.470 ⇒ 00:57:33.100 Amber Lin: revenue that we still need to groom
542 00:57:34.094 ⇒ 00:57:37.600 Amber Lin: and then there’s some stuff for
543 00:57:38.300 ⇒ 00:57:43.970 Amber Lin: a little bit left for redshift stuff and
544 00:57:46.730 ⇒ 00:57:54.650 Amber Lin: a few things left for looker as well. So next time we have grooming we can go look at these.
545 00:57:56.670 ⇒ 00:57:57.280 Emily Giant: Okay.
546 00:57:57.580 ⇒ 00:57:58.150 Amber Lin: Yeah.
547 00:57:58.300 ⇒ 00:58:09.139 Amber Lin: yeah, thank you. I think that made us a lot more clear on what needs to get done in inventory. And also at least we know what the immediate next steps will look like for Fred, for revenue.
548 00:58:09.800 ⇒ 00:58:11.080 Emily Giant: Yeah, agreed.
549 00:58:11.080 ⇒ 00:58:11.720 Amber Lin: Great.
550 00:58:11.920 ⇒ 00:58:13.109 Amber Lin: Thank you all.
551 00:58:13.440 ⇒ 00:58:15.050 Caio Velasco: Hey? See? You guys, tomorrow.
552 00:58:15.520 ⇒ 00:58:17.340 Amber Lin: See you bye enjoy it.
553 00:58:17.340 ⇒ 00:58:18.160 Demilade Agboola: Bye.