Meeting Title: US x BF | Standup Date: 2025-07-10 Meeting participants: Caio Velasco, Demilade Agboola, Emily Giant, Amber Lin, Uttam Kumaran
WEBVTT
1 00:00:27.130 ⇒ 00:00:27.900 Caio Velasco: Hello!
2 00:00:28.596 ⇒ 00:00:29.489 Demilade Agboola: Oh, yeah.
3 00:00:30.270 ⇒ 00:00:31.240 Caio Velasco: Good! How are you?
4 00:00:31.950 ⇒ 00:00:34.260 Demilade Agboola: I am pretty alright.
5 00:00:35.200 ⇒ 00:00:43.680 Caio Velasco: That’s good trying to debug this spreadsheet issues each time different issue.
6 00:00:47.590 ⇒ 00:00:50.930 Demilade Agboola: Sounds sounds very frustrating. To be honest.
7 00:00:51.530 ⇒ 00:00:58.349 Caio Velasco: It is, I mean thousands of tables. And then you never know when it’s gonna happen. Something new.
8 00:00:59.860 ⇒ 00:01:06.000 Caio Velasco: The last one I found was really weird. You can see the table and red shit.
9 00:01:06.440 ⇒ 00:01:13.689 Caio Velasco: You can see it in the information schemas, etcetera. But you cannot click on it or query. It
10 00:01:14.060 ⇒ 00:01:17.309 Caio Velasco: generates from there for the world.
11 00:01:17.920 ⇒ 00:01:22.726 Caio Velasco: Let’s see, at least now it’s jumping, and it’s keeping and continuing the job.
12 00:01:23.970 ⇒ 00:01:25.520 Demilade Agboola: As one step forward.
13 00:01:25.990 ⇒ 00:01:26.620 Caio Velasco: Yep.
14 00:01:31.120 ⇒ 00:01:32.139 Demilade Agboola: Hi! Everyone.
15 00:01:34.480 ⇒ 00:01:35.020 Emily Giant: Hello!
16 00:01:36.140 ⇒ 00:01:42.666 Amber Lin: Hi, I want to just go over tickets really quickly. And then we could talk about
17 00:01:44.050 ⇒ 00:01:45.989 Amber Lin: the meeting later.
18 00:01:47.270 ⇒ 00:01:50.940 Amber Lin: So can everyone.
19 00:01:51.350 ⇒ 00:01:53.419 Emily Giant: Update their tickets.
20 00:01:54.630 ⇒ 00:01:58.560 Amber Lin: And comment. If there’s any blockers.
21 00:01:59.460 ⇒ 00:02:03.540 Emily Giant: I need to add 2 tickets, actually only one to this sprint.
22 00:02:05.110 ⇒ 00:02:06.810 Emily Giant: So just a fair warning.
23 00:02:12.510 ⇒ 00:02:14.279 Amber Lin: Are these, one reviewed.
24 00:02:16.522 ⇒ 00:02:40.609 Emily Giant: The polytomic cron schedule. I just reviewed it with Zack, and I need to ping utam. It’s not quite aligned with the schedule. And I I just wanna reshare the schedule with him to make sure that, like all of the components of it, so it’s that one can go back in in progress and assigned to Utam, and then I have a separate ticket that’s assigned to Zack that I’m just managing the like.
25 00:02:41.160 ⇒ 00:02:51.269 Emily Giant: The back and forth in Asana and linear, the Lo-fi Flowchart afs that one
26 00:02:53.250 ⇒ 00:02:59.690 Emily Giant: as long as demalade is finding it useful in its current state, I would say, that’s
27 00:03:00.240 ⇒ 00:03:06.010 Emily Giant: it’s out of stakeholder review, though it’s it’s now just between us internally, here.
28 00:03:09.680 ⇒ 00:03:13.080 Emily Giant: And then the fiscal year one’s done.
29 00:03:13.330 ⇒ 00:03:13.715 Amber Lin: Okay.
30 00:03:28.660 ⇒ 00:03:29.530 Amber Lin: Okay.
31 00:03:38.760 ⇒ 00:03:39.930 Amber Lin: all right.
32 00:03:40.910 ⇒ 00:03:45.440 Amber Lin: Oh, how about these 2?
33 00:03:51.250 ⇒ 00:04:00.850 Emily Giant: The hard good. That is what you can change that to me. We spoke this morning, and I’m gonna draft it, and then
34 00:04:01.080 ⇒ 00:04:03.899 Emily Giant: I will send it to
35 00:04:04.130 ⇒ 00:04:09.149 Emily Giant: a demo lotto for review. But we we kind of parsed out what needs to happen
36 00:04:09.290 ⇒ 00:04:17.230 Emily Giant: for that to be done, and it’s easily done by me.
37 00:04:17.977 ⇒ 00:04:21.790 Emily Giant: So that he can keep working on like the the bigger stuff.
38 00:04:24.040 ⇒ 00:04:24.820 Amber Lin: Okay.
39 00:04:26.290 ⇒ 00:04:30.370 Emily Giant: So I actually done a lot. I do you think that I need to create that ticket? For
40 00:04:30.530 ⇒ 00:04:34.240 Emily Giant: I was writing like hard, good reconciliation, mart.
41 00:04:35.250 ⇒ 00:04:41.779 Emily Giant: Or should I just kind of change the parameters on that one to specify the acceptance criteria.
42 00:04:42.070 ⇒ 00:04:43.439 Amber Lin: I think so. I think that would be.
43 00:04:43.440 ⇒ 00:04:47.660 Demilade Agboola: Yeah, I think, yeah, yeah, it’s just easier to change the acceptance criteria and one through 5.
44 00:04:48.120 ⇒ 00:04:49.870 Emily Giant: Cool. All right. I will do that.
45 00:04:50.280 ⇒ 00:04:50.745 Amber Lin: Okay.
46 00:04:56.410 ⇒ 00:05:00.510 Amber Lin: no, this one we’re waiting for.
47 00:05:02.470 ⇒ 00:05:04.580 Amber Lin: If I leave it to get back.
48 00:05:05.723 ⇒ 00:05:09.706 Amber Lin: That one we’re we’re doing today.
49 00:05:16.360 ⇒ 00:05:22.459 Amber Lin: Oh, I guess. Does all these tickets capture what you’re doing?
50 00:05:23.248 ⇒ 00:05:30.469 Amber Lin: I know you guys also talked to Philippe. There might be. Isn’t there some new tickets that we might want to add.
51 00:05:32.022 ⇒ 00:05:37.160 Demilade Agboola: Yeah. So we had some conversations with Felipe, and he had like done
52 00:05:37.310 ⇒ 00:05:41.160 Demilade Agboola: use cases in which we could potentially look into
53 00:05:41.822 ⇒ 00:05:47.309 Demilade Agboola: the one thing I’m looking at today, which is in a street captured here.
54 00:05:47.895 ⇒ 00:05:51.379 Demilade Agboola: Is just like future notes. Consult orders from.
55 00:05:51.670 ⇒ 00:05:53.979 Amber Lin: The numbers that we’re currently getting.
56 00:05:54.120 ⇒ 00:05:57.099 Demilade Agboola: Or the adjustments, inventory balance and adjustments.
57 00:05:59.050 ⇒ 00:05:59.530 Amber Lin: Hmm.
58 00:05:59.530 ⇒ 00:06:03.120 Demilade Agboola: Well, not necessarily filtering out, creating a criteria, for
59 00:06:03.830 ⇒ 00:06:08.370 Demilade Agboola: within a column that we can use to flag household orders
60 00:06:08.570 ⇒ 00:06:12.030 Demilade Agboola: that allows us to know the canceled quantity, and
61 00:06:12.160 ⇒ 00:06:16.029 Demilade Agboola: if people want to like, dig into that portion of it, they can do it.
62 00:06:16.520 ⇒ 00:06:24.920 Amber Lin: Yeah, is there a way that I can that we can make those his requirements into tickets so we could track our progress with them?
63 00:06:26.016 ⇒ 00:06:37.383 Demilade Agboola: So the ones that were from yesterday’s call. There are like tickets, you can the the auto, the auto generated tickets largely work. You might need to change the signees
64 00:06:38.173 ⇒ 00:06:45.390 Demilade Agboola: but like the one for the cancellation was today. I believe we should also have, like an auto generated ticket for that
65 00:06:46.110 ⇒ 00:06:52.290 Demilade Agboola: later. Once the summary comes in, so I can add that.
66 00:06:52.810 ⇒ 00:06:58.979 Emily Giant: I can add it to. If you want me to demo it. I’m I’m like in ticket creating mode here, so.
67 00:07:00.008 ⇒ 00:07:01.891 Demilade Agboola: It’s all good.
68 00:07:03.020 ⇒ 00:07:08.370 Amber Lin: I see. So there’s stuff from yesterday’s meeting, and there’s stuff from today’s meeting right.
69 00:07:09.800 ⇒ 00:07:10.690 Demilade Agboola: Yeah.
70 00:07:10.870 ⇒ 00:07:12.270 Demilade Agboola: Oh, man.
71 00:07:13.681 ⇒ 00:07:21.729 Amber Lin: I can. I can add those, and then while we talk.
72 00:07:22.250 ⇒ 00:07:29.640 Amber Lin: And if maybe if we you guys want to talk about
73 00:07:29.740 ⇒ 00:07:34.580 Amber Lin: revenue. Kyle, have you talked with them a lot today?
74 00:07:36.360 ⇒ 00:07:42.220 Caio Velasco: No, not about this. I was doing a bit of the redshift. Again there was another error.
75 00:07:43.045 ⇒ 00:07:49.810 Caio Velasco: And then I was continuing like tracing the order found like a few new things as well.
76 00:07:50.600 ⇒ 00:07:52.500 Caio Velasco: I know we haven’t talked.
77 00:07:53.810 ⇒ 00:07:59.060 Amber Lin: Okay. How is the progress for the revenue audit going.
78 00:08:00.164 ⇒ 00:08:03.429 Caio Velasco: So, yeah, well, I’m learning, and
79 00:08:03.570 ⇒ 00:08:11.300 Caio Velasco: I can already trace an order. And it’s so borders from
80 00:08:11.420 ⇒ 00:08:20.100 Caio Velasco: the the ingestion source done by evil up to the tableau tableau items. Xf.
81 00:08:20.922 ⇒ 00:08:29.850 Caio Velasco: I’m like trying to build like a query to just see all the the trace from left to track it from left to right
82 00:08:29.970 ⇒ 00:08:34.040 Caio Velasco: to see if it’s it’s making sense all all the steps.
83 00:08:34.210 ⇒ 00:08:49.010 Caio Velasco: And yeah. And then, after this I would add the price, quantity and some other things to it which would be addressing the other tickets. So yeah, I’m almost done with this one, which could be the audit orders.
84 00:08:49.766 ⇒ 00:08:54.239 Caio Velasco: Yeah. Theoretically, I kind of know now our order is traced.
85 00:08:55.220 ⇒ 00:08:56.110 Amber Lin: Okay.
86 00:08:56.110 ⇒ 00:09:00.530 Caio Velasco: So I was just a bit unsure. If I could mark this as done or not.
87 00:09:02.431 ⇒ 00:09:08.060 Amber Lin: Do you want Emil out it, or Emily to look over it as as like a review.
88 00:09:08.660 ⇒ 00:09:14.199 Caio Velasco: Could be, yeah, yeah, I can post the the query, and they can run in redshift and see if it makes sense.
89 00:09:17.531 ⇒ 00:09:23.010 Amber Lin: Emily, how do you think is the best way to review the audit?
90 00:09:28.401 ⇒ 00:09:30.459 Amber Lin: The the revenue audit right.
91 00:09:30.790 ⇒ 00:09:39.260 Demilade Agboola: Yeah. So for the revenue order for orders. As long as we have a very clear idea of the flow of data.
92 00:09:39.700 ⇒ 00:09:45.620 Demilade Agboola: and where, like the car revenue,
93 00:09:47.260 ⇒ 00:09:51.230 Demilade Agboola: alums are coming from so like order total, all that stuff.
94 00:09:51.390 ⇒ 00:09:58.909 Demilade Agboola: if we understand that. And we’re able to be able to build our own version of it based off the audits. Then we’re good.
95 00:09:59.190 ⇒ 00:10:06.079 Demilade Agboola: If we’re able to rebuild the the current infrastructure in a way that is easier, less convoluted.
96 00:10:06.520 ⇒ 00:10:13.580 Demilade Agboola: But we still get the same sort of numbers like, it’s clear enough that we can still rebuild what’s currently exist. And we’re good.
97 00:10:16.090 ⇒ 00:10:16.790 Caio Velasco: Good.
98 00:10:17.820 ⇒ 00:10:22.170 Caio Velasco: Yeah. Well, I’m starting. All my queries are being done as following one
99 00:10:22.680 ⇒ 00:10:36.290 Caio Velasco: which I had to find after many attempts, because some orders had no many sub orders, so they were not very interesting or not many line items, so they were also not much interesting. So then I found one.
100 00:10:36.410 ⇒ 00:10:45.590 Caio Velasco: and then I’m trying to now, like, join all those tables in the lineage and build, let’s say, a table that shows the lineage from left to right.
101 00:10:45.750 ⇒ 00:10:49.919 Caio Velasco: and if that is correct, for I mean supposedly just one order.
102 00:10:50.408 ⇒ 00:10:57.030 Caio Velasco: Then adding the price, quantity, subscription. And now all the other thing that could be happening along the way.
103 00:10:57.460 ⇒ 00:11:00.099 Caio Velasco: I think that’s what the M. Lade means, Bob.
104 00:11:00.690 ⇒ 00:11:03.289 Caio Velasco: understanding the whole picture of the order.
105 00:11:03.777 ⇒ 00:11:07.050 Caio Velasco: So yeah. And then I can do as as we
106 00:11:07.160 ⇒ 00:11:19.430 Caio Velasco: we discussed, like the audit orders could be just this table tracking an order, and then I don’t know. The refund would be this table, tracking this order, but also with a refund, and and so on, so forth.
107 00:11:21.940 ⇒ 00:11:26.109 Demilade Agboola: Yeah, yeah. So we can just do that. And then ultimately.
108 00:11:26.810 ⇒ 00:11:32.210 Demilade Agboola: at the end, we can kind of just do a comparison. And just be sure we’re getting like the same numbers.
109 00:11:32.430 ⇒ 00:11:38.479 Demilade Agboola: but you know we’re not dropping revenue or dropping refunds or dropping anything anywhere.
110 00:11:38.640 ⇒ 00:11:40.470 Demilade Agboola: but we know that our new
111 00:11:40.810 ⇒ 00:11:44.530 Demilade Agboola: low will get us the same numbers as what currently exist.
112 00:11:44.960 ⇒ 00:11:51.880 Demilade Agboola: But obviously, the way we all do it will be less convoluted than what currently exists because that is a an entire mess.
113 00:11:52.700 ⇒ 00:11:54.479 Caio Velasco: Yeah, yeah, I agree.
114 00:11:54.480 ⇒ 00:12:02.769 Amber Lin: Oh, okay, sounds good. Or W. Do you think we’re still on track to complete these tickets?
115 00:12:04.045 ⇒ 00:12:10.969 Amber Lin: For this cycle, or at least say, maybe 2 of these this week.
116 00:12:12.659 ⇒ 00:12:17.450 Caio Velasco: To. Well, for tomorrow. Let’s say that I finish orders, and then
117 00:12:17.620 ⇒ 00:12:29.630 Caio Velasco: I can check. Which do you do like, for example, Emily? Or do you know which other one, like a transaction or refund, which one would be the easiest one? After understanding what? What is an order.
118 00:12:31.100 ⇒ 00:12:36.681 Caio Velasco: refunds, or subscriptions, or discount, or 9 9 little bit.
119 00:12:37.335 ⇒ 00:12:45.840 Demilade Agboola: I will say that if if you want the orders track it’ll it might be easier to get things like discounts and refunds, because it’s kind of
120 00:12:46.720 ⇒ 00:12:53.249 Demilade Agboola: in the same set of tables by the same line. There might be much easier to be able to make sense of
121 00:12:54.130 ⇒ 00:12:58.520 Demilade Agboola: like what is going on in the same rows, but different columns for that.
122 00:12:59.790 ⇒ 00:13:04.289 Caio Velasco: Okay, okay? So I’ll check those 1st and let’s see if we can
123 00:13:05.030 ⇒ 00:13:19.980 Caio Velasco: do a bit more until end of the day tomorrow. Because, for example, when I’m looking at orders, and if I go to the ingestion table, I see like unit price, or I mean many prices and things. So then my question will always be like.
124 00:13:20.140 ⇒ 00:13:27.339 Caio Velasco: why are we using a price from a later table and not from that one? Or you know, those questions will come up.
125 00:13:27.630 ⇒ 00:13:29.369 Caio Velasco: That’s what I’m trying to trace.
126 00:13:30.590 ⇒ 00:13:31.240 Demilade Agboola: See if I can.
127 00:13:31.240 ⇒ 00:13:37.390 Caio Velasco: Yeah, we can do like the orders one and maybe one more. And then that’s what I expect.
128 00:13:38.320 ⇒ 00:13:39.569 Demilade Agboola: Okay, so cool.
129 00:13:40.242 ⇒ 00:13:55.070 Amber Lin: Tag them a lot. If you need anyone to cross, check it to confirm that this is what you guys need to rebuild make sure that you guys talk between yourselves to to make sure you guys can use it for the rebuild.
130 00:13:55.640 ⇒ 00:13:56.819 Caio Velasco: Perfect. We’ll do, we’ll do.
131 00:13:56.820 ⇒ 00:14:10.160 Amber Lin: Okay. Emma, anything, anything here? Do. I assign all of these to you? Do I assign points. I just wanna track that. You’re the work that you are actually doing.
132 00:14:15.190 ⇒ 00:14:16.909 Demilade Agboola: Let me see.
133 00:14:18.900 ⇒ 00:14:24.090 Demilade Agboola: But the local dashboards are not. That’s not work we’re doing. We’re we’re handling the modeling
134 00:14:24.700 ⇒ 00:14:28.139 Demilade Agboola: unless we decide to change things. So
135 00:14:28.720 ⇒ 00:14:33.129 Demilade Agboola: I think it would be a function of just ensuring that
136 00:14:33.440 ⇒ 00:14:42.179 Demilade Agboola: we tell the users. In this case it will be Felipe, like where the data is, which is kind of why the call today is important so that they know where there’s data
137 00:14:42.590 ⇒ 00:14:47.280 Demilade Agboola: players and they can start building and testing and using themselves.
138 00:14:59.970 ⇒ 00:15:02.040 Amber Lin: I guess that would be the thing.
139 00:15:05.110 ⇒ 00:15:08.314 Amber Lin: I know we have a similar ticket for that.
140 00:15:13.100 ⇒ 00:15:15.550 Amber Lin: okay, yeah. I think.
141 00:15:15.550 ⇒ 00:15:18.079 Demilade Agboola: And then stuff like the.
142 00:15:19.640 ⇒ 00:15:22.090 Amber Lin: I’m just gonna merge that in here.
143 00:15:28.920 ⇒ 00:15:31.569 Demilade Agboola: And also the shrinkage, logic,
144 00:15:33.090 ⇒ 00:15:40.430 Demilade Agboola: the shrinkage and spoilage. So 1, 9 is also the same thing. Kind of thanks for that.
145 00:15:46.080 ⇒ 00:15:49.989 Amber Lin: Okay? So that would also go in onboarding.
146 00:15:51.010 ⇒ 00:15:51.720 Demilade Agboola: Yes.
147 00:15:52.610 ⇒ 00:15:53.340 Amber Lin: Okay.
148 00:16:03.292 ⇒ 00:16:04.950 Demilade Agboola: So validating, Marcus.
149 00:16:10.890 ⇒ 00:16:19.650 Demilade Agboola: Marketing sample order. So this is technically Emily versus all me like, we’re kind of working on that trying to figure out where exactly
150 00:16:21.930 ⇒ 00:16:25.400 Demilade Agboola: But I’m looking into it. Obviously, I mean, he has better like
151 00:16:25.540 ⇒ 00:16:33.060 Demilade Agboola: by the senses when it comes to this data. But just basically, if there’s a way to validate where, like the marketing data comes from.
152 00:16:33.716 ⇒ 00:16:40.130 Demilade Agboola: how that is marked and how it is stored in their database. As like. So could you know.
153 00:16:41.780 ⇒ 00:16:44.159 Emily Giant: Where you can merge that with 1, 94.
154 00:16:44.870 ⇒ 00:16:47.600 Emily Giant: I think it’s the same notion.
155 00:16:47.950 ⇒ 00:16:48.996 Amber Lin: Oh, okay.
156 00:17:13.930 ⇒ 00:17:19.230 Amber Lin: okay. So I’m gonna delete badge.
157 00:17:20.510 ⇒ 00:17:24.930 Amber Lin: Is this similar to the non-floral bits.
158 00:17:27.334 ⇒ 00:17:34.449 Demilade Agboola: Not particularly. This is an investigation as to why something is wrong with the products.
159 00:17:35.752 ⇒ 00:17:40.820 Demilade Agboola: But then we also have on, I mean, is this quite? Is this?
160 00:17:42.190 ⇒ 00:17:48.280 Demilade Agboola: This is a unique issue? Yes, but like, is this also a function of the bundles that we’re supposed to work on.
161 00:17:50.370 ⇒ 00:17:51.959 Demilade Agboola: I’ve bundled skews.
162 00:17:53.400 ⇒ 00:17:56.119 Emily Giant: Which one sorry the Move model Mart. Logic.
163 00:17:56.120 ⇒ 00:18:00.130 Demilade Agboola: No. 1, 9, 7. The investigating, the missing glass centerpiece.
164 00:18:01.650 ⇒ 00:18:07.649 Emily Giant: That is going to be rolled up into what I’m working on today with the non-floral mart
165 00:18:08.020 ⇒ 00:18:16.059 Emily Giant: that the reason it’s missing is because we were actively filtering out hard goods without lots from that table.
166 00:18:16.920 ⇒ 00:18:25.330 Demilade Agboola: Gotcha. So the fix that we worked on today will will cover both this as well as
167 00:18:26.090 ⇒ 00:18:28.689 Demilade Agboola: 1, 2, 5. Yeah, okay.
168 00:18:31.180 ⇒ 00:18:33.869 Amber Lin: Okay, does this still state a ticket.
169 00:18:34.500 ⇒ 00:18:34.920 Emily Giant: No.
170 00:18:34.920 ⇒ 00:18:35.270 Demilade Agboola: No.
171 00:18:35.740 ⇒ 00:18:38.268 Emily Giant: Go into 1, 3, 5, and
172 00:18:39.580 ⇒ 00:18:42.344 Emily Giant: yeah, it will be fixed by that.
173 00:18:43.700 ⇒ 00:18:49.080 Amber Lin: Okay, what was the ticket that you guys are currently working on.
174 00:18:50.140 ⇒ 00:18:53.079 Emily Giant: One sorry. Go ahead.
175 00:18:53.080 ⇒ 00:18:54.413 Amber Lin: There was a new one
176 00:18:54.680 ⇒ 00:18:58.089 Demilade Agboola: Yeah. So that’s what I was trying to say. So there’s the fill
177 00:18:59.620 ⇒ 00:19:03.680 Demilade Agboola: on filtering out, or like plug in canceled orders.
178 00:19:03.900 ⇒ 00:19:04.480 Amber Lin: Oh!
179 00:19:09.408 ⇒ 00:19:12.520 Demilade Agboola: In inventory. Yeah? So that’s basically.
180 00:19:13.560 ⇒ 00:19:15.589 Amber Lin: Are you doing that.
181 00:19:15.590 ⇒ 00:19:16.340 Demilade Agboola: Yes.
182 00:19:16.340 ⇒ 00:19:17.230 Amber Lin: Points.
183 00:19:17.560 ⇒ 00:19:19.070 Demilade Agboola: I’ll take 2 points.
184 00:19:19.390 ⇒ 00:19:20.310 Amber Lin: Okay.
185 00:19:21.190 ⇒ 00:19:21.900 Amber Lin: Oh.
186 00:19:25.840 ⇒ 00:19:28.829 Amber Lin: are you finishing it this Friday, or.
187 00:19:28.960 ⇒ 00:19:31.070 Demilade Agboola: Yeah, that’s Friday. I’m working on it today.
188 00:19:31.450 ⇒ 00:19:32.240 Amber Lin: Okay.
189 00:19:33.940 ⇒ 00:19:35.170 Amber Lin: Sounds good.
190 00:19:38.400 ⇒ 00:19:40.899 Amber Lin: Medium, high priority.
191 00:19:42.270 ⇒ 00:19:43.309 Demilade Agboola: I’ll take medium.
192 00:19:43.540 ⇒ 00:19:44.125 Amber Lin: Okay.
193 00:19:44.870 ⇒ 00:19:46.583 Amber Lin: Sounds good.
194 00:19:49.350 ⇒ 00:19:56.230 Amber Lin: alright, don’t have much time. You think we’re on track to finish all of these this cycle right?
195 00:19:57.310 ⇒ 00:20:00.969 Demilade Agboola: Yeah, nothing. Nothing jumps out as off track right now.
196 00:20:01.240 ⇒ 00:20:09.489 Amber Lin: Awesome. Emily, would you ping Utam on what you need for this? Oh, 5 min ago.
197 00:20:09.490 ⇒ 00:20:11.400 Demilade Agboola: What time is, what time is actually on the call.
198 00:20:11.970 ⇒ 00:20:12.720 Amber Lin: Oh! What!
199 00:20:12.860 ⇒ 00:20:13.390 Uttam Kumaran: It’s finish.
200 00:20:16.050 ⇒ 00:20:19.280 Amber Lin: Okay.
201 00:20:19.280 ⇒ 00:20:33.480 Uttam Kumaran: I’m just gonna watch this week. I’m not. Since a new feature. I just wanna check that. It’s working. The other thing is polytomic. And this is pretty typical for any Etl, is that it’s all Utc, so you just have to make sure to convert it.
202 00:20:34.195 ⇒ 00:20:39.380 Uttam Kumaran: So then, what you see in the Cron will just be 4 h shifted.
203 00:20:40.560 ⇒ 00:20:43.949 Uttam Kumaran: but like this should match what we need.
204 00:20:44.930 ⇒ 00:20:45.880 Amber Lin: Okay.
205 00:20:46.860 ⇒ 00:20:50.939 Emily Giant: And then I’ll just ping Zach with your updates on this.
206 00:20:51.440 ⇒ 00:20:51.980 Uttam Kumaran: Okay.
207 00:20:52.200 ⇒ 00:20:57.318 Emily Giant: I know that, like he’s, I’m pulling him in just to review it for like budgetary purposes.
208 00:20:57.830 ⇒ 00:21:03.519 Emily Giant: I just want to make sure it’s aligning with what he’s got set for for the budget, because he keeps it pretty tight and tidy.
209 00:21:04.760 ⇒ 00:21:05.300 Uttam Kumaran: Check.
210 00:21:06.250 ⇒ 00:21:10.967 Emily Giant: Thanks for doing that. By the way, I so I really appreciate it.
211 00:21:16.750 ⇒ 00:21:17.650 Amber Lin: Also.
212 00:21:18.790 ⇒ 00:21:19.340 Amber Lin: Okay.
213 00:21:20.040 ⇒ 00:21:22.729 Demilade Agboola: I don’t know. I sent you the slides. Oh, yes, I just wanted you to.
214 00:21:22.730 ⇒ 00:21:23.180 Amber Lin: Yeah.
215 00:21:23.180 ⇒ 00:21:24.010 Demilade Agboola: Like an owner.
216 00:21:24.410 ⇒ 00:21:32.210 Amber Lin: Yeah, I want to. That want us to look at it together. Okay, so objective.
217 00:21:32.730 ⇒ 00:21:38.119 Amber Lin: Okay, wow, where are we? Right now?
218 00:21:38.500 ⇒ 00:21:40.550 Amber Lin: We’re like, here.
219 00:21:40.930 ⇒ 00:21:48.120 Demilade Agboola: Yeah, we’re basically at the end of the consolidation phase, where we’re like the adjustment type modeling and rolling out into dashboard.
220 00:21:48.230 ⇒ 00:21:53.169 Demilade Agboola: So right now, we’re also going to be looking at it like platform documentation and going forward.
221 00:21:53.880 ⇒ 00:21:58.150 Demilade Agboola: We’re going to be adding, like the non floral goods and hard goods, which is what we’re talking about.
222 00:21:58.560 ⇒ 00:22:08.070 Demilade Agboola: doing and just funding edge cases, and also setting up more tests and observability tools and then bring out the new data into like more dashboards and stuff.
223 00:22:09.370 ⇒ 00:22:10.170 Amber Lin: Okay.
224 00:22:11.160 ⇒ 00:22:11.700 Demilade Agboola: Oh.
225 00:22:14.350 ⇒ 00:22:22.579 Demilade Agboola: yeah. So this is kind of like the new models like the net, new tables that have come out and like what the data contains right now.
226 00:22:23.449 ⇒ 00:22:26.089 Demilade Agboola: where they can be found and what layers?
227 00:22:27.720 ⇒ 00:22:32.640 Amber Lin: The stakeholders. Do you think the stakeholders in this meeting understands these?
228 00:22:32.890 ⇒ 00:22:34.989 Amber Lin: They have no problem with that right.
229 00:22:36.040 ⇒ 00:22:37.210 Demilade Agboola: I mean by stable.
230 00:22:37.210 ⇒ 00:22:37.680 Amber Lin: Before.
231 00:22:38.550 ⇒ 00:22:39.349 Demilade Agboola: I mean.
232 00:22:39.350 ⇒ 00:22:40.160 Demilade Agboola: Obviously I won’t miss you.
233 00:22:40.160 ⇒ 00:22:42.340 Emily Giant: And Felipe will understand the rest of them.
234 00:22:42.340 ⇒ 00:22:46.779 Amber Lin: Okay, okay, okay, does this impact the rest of them?
235 00:22:50.310 ⇒ 00:22:54.405 Emily Giant: No, Jess, Jess. Yes, Jess needs this
236 00:22:55.400 ⇒ 00:22:57.279 Emily Giant: the only ones it won’t impact.
237 00:22:57.580 ⇒ 00:23:03.765 Emily Giant: Carrie. His name is not Carrie. Oh, my God! I can’t believe I said, that worked here 3 years ago.
238 00:23:05.080 ⇒ 00:23:07.200 Emily Giant: Dk and
239 00:23:09.120 ⇒ 00:23:10.360 Amber Lin: Yeah.
240 00:23:10.790 ⇒ 00:23:13.710 Emily Giant: It won’t matter, but, like he also is.
241 00:23:14.830 ⇒ 00:23:18.760 Emily Giant: Pk is the only one that it won’t directly impact.
242 00:23:19.220 ⇒ 00:23:21.883 Amber Lin: Okay, so leave it.
243 00:23:23.220 ⇒ 00:23:26.100 Amber Lin: I don’t know about Stephanie.
244 00:23:26.890 ⇒ 00:23:28.500 Amber Lin: Walter.
245 00:23:28.500 ⇒ 00:23:37.169 Emily Giant: She definitely will be impacted. Yes, she works for Perry. So oh, okay, they were very intertwined.
246 00:23:37.530 ⇒ 00:23:41.299 Amber Lin: Okay, that’s good. That
247 00:23:46.385 ⇒ 00:23:48.030 Amber Lin: should we?
248 00:23:48.490 ⇒ 00:23:49.970 Amber Lin: And next steps?
249 00:23:51.990 ⇒ 00:23:56.700 Amber Lin: 8.
250 00:23:58.140 ⇒ 00:24:04.680 Amber Lin: Is there any follow up meetings that we want to book with the stakeholders
251 00:24:07.690 ⇒ 00:24:16.959 Amber Lin: to onboard them to say, Dvt, show them like a video walkthrough of where things are for those that are directly impacted.
252 00:24:18.050 ⇒ 00:24:23.759 Demilade Agboola: No so effectively. These Dvt models already exist in their.
253 00:24:24.090 ⇒ 00:24:26.709 Amber Lin: Dima, which is actually kind of what I’m adding now.
254 00:24:26.860 ⇒ 00:24:42.319 Demilade Agboola: But like this. So once they go to like analytics, blah blah, they can see this data. Now, ideally, you want to be able to use this data, the map models, which is what we would recommend, because that’s the models that we’re trying to like. Put
255 00:24:42.810 ⇒ 00:24:49.309 Demilade Agboola: the high level information that they would want to use in their visualizations. But the idea is.
256 00:24:49.870 ⇒ 00:25:15.980 Demilade Agboola: everyone has visibility into the logic that goes into it. So if they ever want to like query or figure out like, why stuff is broken, or why certain numbers seem weird. They know where, like the logic of that is being created. They feel like the presale committed number seem weird. They can look at the end. Presale committed table from this and go. Actually, that’s probably the logic that you’re using inappropriately.
257 00:25:16.600 ⇒ 00:25:28.139 Demilade Agboola: So the idea of this is that they get like full context of what’s going on. They can also contribute in terms of like knowing what’s happening, but they also get exposed
258 00:25:28.270 ⇒ 00:25:34.230 Demilade Agboola: to the models that they can use to be able to like. Get the answers on a daily.
259 00:25:35.930 ⇒ 00:25:36.700 Amber Lin: Okay.
260 00:25:37.040 ⇒ 00:25:41.110 Amber Lin: 8.
261 00:25:42.180 ⇒ 00:25:50.620 Amber Lin: I was just, I think I think that’s really awesome. I think what I was thinking about was that, how do we help
262 00:25:50.810 ⇒ 00:25:59.630 Amber Lin: bridge the gap between. We have the march, and then stakeholders actually building dashboards with our marts like
263 00:26:00.562 ⇒ 00:26:10.869 Amber Lin: for some, I feel like there will be friction there just because they don’t. It’s very new for them, and they might not want to use it to build new look or dashboards.
264 00:26:10.870 ⇒ 00:26:14.829 Uttam Kumaran: Do they have a choice like? Are there? Are the old models available.
265 00:26:15.320 ⇒ 00:26:17.469 Emily Giant: They are right now. They won’t be soon.
266 00:26:17.900 ⇒ 00:26:18.420 Amber Lin: Okay.
267 00:26:18.420 ⇒ 00:26:19.010 Uttam Kumaran: Yeah. So the next.
268 00:26:19.010 ⇒ 00:26:19.410 Amber Lin: Double.
269 00:26:19.410 ⇒ 00:26:20.769 Uttam Kumaran: Really no choice, right.
270 00:26:20.770 ⇒ 00:26:23.279 Emily Giant: Yeah, it’s gonna be like a.
271 00:26:23.280 ⇒ 00:26:24.890 Uttam Kumaran: I will say, you have to like, yeah.
272 00:26:24.890 ⇒ 00:26:34.480 Uttam Kumaran: we have to build a relationship with them. I don’t think anybody is like particularly hard headed about using those. I think the plan should be to replicate whatever dashboards
273 00:26:34.820 ⇒ 00:26:37.629 Uttam Kumaran: currently exist with the new models.
274 00:26:38.597 ⇒ 00:26:44.149 Uttam Kumaran: And then, ideally, they can create new ones with functionality that previously didn’t exist. You know.
275 00:26:44.620 ⇒ 00:26:49.219 Demilade Agboola: Yeah, part of why I’m also showing all of this is because we actually have data
276 00:26:49.440 ⇒ 00:26:52.980 Demilade Agboola: that is at the level that they they didn’t necessarily have before.
277 00:26:53.210 ⇒ 00:27:05.559 Demilade Agboola: but now we can see like shrinkage quantity, and like some numbers that they couldn’t see before. But now we actually have like an advantage to using our numbers, which is part of why I wanted to show them like
278 00:27:05.680 ⇒ 00:27:18.530 Demilade Agboola: these are your tables. These are what the numbers are coming from. And so, if you want to integrate it, these are the tables you need to use integrated into your current dashboard. But obviously the idea is, we don’t want to integrate. We want to like, move over like.
279 00:27:18.640 ⇒ 00:27:22.989 Demilade Agboola: which completely don’t integrate, just actually build out new dashboards. Using this.
280 00:27:22.990 ⇒ 00:27:24.000 Amber Lin: Oh, huh!
281 00:27:24.270 ⇒ 00:27:29.639 Amber Lin: I see. So I I guess we could give them an option to
282 00:27:30.090 ⇒ 00:27:37.967 Amber Lin: book meetings with us if they need like extra extra advice when they’re building their dashboards.
283 00:27:38.866 ⇒ 00:27:46.190 Emily Giant: I think that you’re right in that. Maybe we wait until this is in a really good spot.
284 00:27:47.110 ⇒ 00:27:55.260 Emily Giant: even if it’s in a different sprint in like 2 weeks from now, like a video presentation or something that they can re-watch after we
285 00:27:55.560 ⇒ 00:28:06.889 Emily Giant: build out like foundational dashboards would be super helpful, like everyone. It’s such a lean company that I’m afraid whenever we give the opportunity
286 00:28:07.190 ⇒ 00:28:24.009 Emily Giant: to book meetings with us, they’ll always default to getting their work done, even though their work is not getting done efficiently because they don’t have the data. So I’m fine. And I think Zach and the organization is fine with like pushing out these touch bases to a time when, like.
287 00:28:24.240 ⇒ 00:28:27.530 Emily Giant: we’re no longer doing Qa with anyone
288 00:28:28.687 ⇒ 00:28:34.202 Emily Giant: and that way they can pass it on to like their direct reports as well.
289 00:28:35.410 ⇒ 00:28:43.679 Emily Giant: But I don’t think we’re there yet, I think like maybe in a week and a half or 2 weeks from now. That would be a really great thing to do.
290 00:28:44.660 ⇒ 00:28:48.070 Amber Lin: Okay. Sounds good. Yeah. Go ahead.
291 00:28:48.850 ⇒ 00:29:05.389 Demilade Agboola: I think the the issue right now is that we don’t necessarily have like dashboards, to like show the numbers, but in terms of the numbers being available, which is kind of why I was thinking of doing this in this format is like showing that these numbers do exist.
292 00:29:05.991 ⇒ 00:29:15.090 Emily Giant: Now if we were that so I think we need to like, if are we in the spots, to just be able to look at dashboards, because if we’re going to be able to look at dashboards in terms of like.
293 00:29:15.330 ⇒ 00:29:16.730 Demilade Agboola: Sample dashboards.
294 00:29:17.160 ⇒ 00:29:26.359 Demilade Agboola: That’s a different like like we can do that. But obviously that will take, you know, some time, maybe next week, and we can have, like dashboards out showing all these numbers.
295 00:29:27.050 ⇒ 00:29:34.750 Emily Giant: Yeah, cause part of my friend is making those available in looker. So half of what we’re showing them, and demoing isn’t even in looker yet for them to play with.
296 00:29:35.370 ⇒ 00:29:39.052 Emily Giant: Oh, I’m so sorry I have a meeting that I must go to, but
297 00:29:39.270 ⇒ 00:29:40.400 Amber Lin: No worries.
298 00:29:40.420 ⇒ 00:29:42.219 Emily Giant: That portion is gonna be done.
299 00:29:42.220 ⇒ 00:29:42.550 Amber Lin: Cheers.
300 00:29:42.550 ⇒ 00:29:46.200 Emily Giant: By tomorrow, I think, is the due date, for, like adding this stuff to looker.
301 00:29:46.480 ⇒ 00:29:49.730 Amber Lin: Okay, it is that in the ticket.
302 00:29:49.940 ⇒ 00:29:50.500 Emily Giant: Hmm.
303 00:29:51.070 ⇒ 00:29:51.820 Amber Lin: Okay.
304 00:29:52.370 ⇒ 00:29:56.780 Amber Lin: Awesome. Thanks. Thanks. Everyone. We have to hop to.
305 00:29:58.360 ⇒ 00:29:59.150 Demilade Agboola: Okay? Bye.
306 00:29:59.150 ⇒ 00:29:59.770 Amber Lin: Bye.