Meeting Title: US x BF | Sprint Kickoff Date: 2025-06-10 Meeting participants: Alex K, Emily Giant, Amber Lin, Uttam Kumaran, Demilade Agboola, Caio Velasco
WEBVTT
1 00:02:25.160 ⇒ 00:02:26.200 Uttam Kumaran: Hey, guys.
2 00:02:26.200 ⇒ 00:02:30.900 Alex K: Morning, slash, evening slash wherever you are good to see you.
3 00:02:31.620 ⇒ 00:02:32.640 Uttam Kumaran: Good to see you.
4 00:02:32.640 ⇒ 00:02:33.940 Caio Velasco: Good morning!
5 00:02:42.660 ⇒ 00:02:43.630 Uttam Kumaran: Hello!
6 00:02:43.630 ⇒ 00:02:44.370 Alex K: A
7 00:02:46.814 ⇒ 00:02:52.106 Alex K: Emily was having some connection issues. So she’s probably gonna go run and reboot her thing, and then
8 00:02:52.700 ⇒ 00:02:53.680 Alex K: go beyond.
9 00:02:54.020 ⇒ 00:02:55.000 Uttam Kumaran: Okay. Cool.
10 00:03:01.910 ⇒ 00:03:07.089 Amber Lin: Good morning. I am back in la, and
11 00:03:08.310 ⇒ 00:03:11.650 Amber Lin: it was so scary last night to get back because
12 00:03:12.184 ⇒ 00:03:14.699 Amber Lin: our bus had to take a different route
13 00:03:15.000 ⇒ 00:03:18.960 Amber Lin: because there was protests going on, and
14 00:03:19.360 ⇒ 00:03:22.110 Amber Lin: I wasn’t sure if I would be able to get home.
15 00:03:24.010 ⇒ 00:03:24.990 Uttam Kumaran: It’s crazy.
16 00:03:25.610 ⇒ 00:03:29.860 Amber Lin: Yeah, I’m so sorry.
17 00:03:29.860 ⇒ 00:03:31.190 Emily Giant: Been stressful.
18 00:03:31.190 ⇒ 00:03:32.780 Amber Lin: Nice background.
19 00:03:34.290 ⇒ 00:03:34.890 Emily Giant: Me!
20 00:03:36.650 ⇒ 00:03:43.519 Emily Giant: Sometimes I’d like people to see all the various cat art that is in my house. So I move about to different rooms so that you can.
21 00:03:46.140 ⇒ 00:03:48.029 Amber Lin: That’s very, very nice.
22 00:03:48.030 ⇒ 00:03:51.330 Demilade Agboola: I I’ve never gotten this like cut out view
23 00:03:51.728 ⇒ 00:03:57.220 Demilade Agboola: we’ve had many working sessions together. I don’t know what what did I? I think I deserve to say this. I’ll tell you.
24 00:03:57.220 ⇒ 00:03:58.240 Emily Giant: Why, okay.
25 00:03:58.240 ⇒ 00:04:09.999 Emily Giant: we just installed power strips in our kitchen island. And before I couldn’t plug my computer in. So this was like, very recently, so I never would have sat here because there was never an outlet.
26 00:04:10.000 ⇒ 00:04:13.260 Alex K: Guys will say, I don’t think I’ve seen your kitchen area either. So there you go.
27 00:04:13.670 ⇒ 00:04:14.730 Demilade Agboola: Exactly.
28 00:04:16.269 ⇒ 00:04:17.449 Emily Giant: Blue, bar.
29 00:04:17.450 ⇒ 00:04:18.550 Uttam Kumaran: Wow!
30 00:04:18.550 ⇒ 00:04:20.380 Alex K: Oh, nice!
31 00:04:20.380 ⇒ 00:04:22.880 Emily Giant: Beautiful, the Green Farm.
32 00:04:22.880 ⇒ 00:04:23.959 Amber Lin: I think.
33 00:04:23.960 ⇒ 00:04:24.300 Alex K: Go.
34 00:04:24.300 ⇒ 00:04:24.980 Amber Lin: Oh!
35 00:04:24.980 ⇒ 00:04:30.489 Emily Giant: Actually sorry. Then I swear to God I’ll stop. This is the coolest thing. I found this old hardware display at an antique store.
36 00:04:30.877 ⇒ 00:04:33.200 Amber Lin: And it used to like nothing.
37 00:04:33.200 ⇒ 00:04:39.450 Emily Giant: And stuff. And so we got this, and then this is our old barn floor. We took a floor down from one of the halo
38 00:04:40.390 ⇒ 00:04:41.709 Emily Giant: provision to the countertops.
39 00:04:41.710 ⇒ 00:04:43.110 Emily Giant: Nice.
40 00:04:43.110 ⇒ 00:04:45.970 Amber Lin: Oh, you’re so cool!
41 00:04:45.970 ⇒ 00:04:47.489 Emily Giant: Done the show, and tell.
42 00:04:47.490 ⇒ 00:04:51.240 Amber Lin: This is my dried flower. Section.
43 00:04:51.650 ⇒ 00:04:54.199 Emily Giant: I love it very urban stems. S.
44 00:04:57.520 ⇒ 00:05:00.030 Amber Lin: I keep, I keep them company.
45 00:05:00.560 ⇒ 00:05:01.065 Emily Giant: Oh!
46 00:05:01.570 ⇒ 00:05:03.320 Amber Lin: Let me share my screen.
47 00:05:04.480 ⇒ 00:05:09.230 Amber Lin: So thank you all for coming to the kickoff. Let me share this.
48 00:05:10.210 ⇒ 00:05:14.050 Amber Lin: We met internally as a team. To
49 00:05:14.320 ⇒ 00:05:22.659 Amber Lin: group needs to get discussed. And so here’s what we arrived
50 00:05:22.970 ⇒ 00:05:26.400 Amber Lin: at for this current for this cycle.
51 00:05:26.770 ⇒ 00:05:30.809 Amber Lin: And then we can talk about if this is a
52 00:05:31.482 ⇒ 00:05:37.219 Amber Lin: if this is not enough, this is too much. We can see how it’s allocated.
53 00:05:37.560 ⇒ 00:05:44.069 Amber Lin: and see how, if we want to change anything.
54 00:05:44.440 ⇒ 00:05:45.480 Amber Lin: So
55 00:05:49.910 ⇒ 00:05:59.290 Amber Lin: starting off at the top, we have a few ad hoc tickets that was added, and they’re pretty urgent. So as here
56 00:06:00.430 ⇒ 00:06:05.399 Amber Lin: Estimates for them it’ll be great if you guys can add some estimates.
57 00:06:05.400 ⇒ 00:06:08.340 Alex K: I think you’re you’re clipping, or you’re cutting out.
58 00:06:08.770 ⇒ 00:06:10.360 Uttam Kumaran: Yeah, your audio is cutting in and out.
59 00:06:10.750 ⇒ 00:06:11.590 Amber Lin: Yes.
60 00:06:15.430 ⇒ 00:06:16.240 Amber Lin: Okay.
61 00:06:16.550 ⇒ 00:06:20.659 Amber Lin: Do you think my network is not the greatest?
62 00:06:20.770 ⇒ 00:06:26.320 Amber Lin: Say, let me see if I can join my audio here.
63 00:06:26.740 ⇒ 00:06:28.810 Uttam Kumaran: Maybe if you turn off video, too, it should.
64 00:06:28.810 ⇒ 00:06:29.700 Amber Lin: Okay.
65 00:06:29.700 ⇒ 00:06:30.060 Uttam Kumaran: So.
66 00:06:30.060 ⇒ 00:06:40.519 Alex K: While while you’re doing that I was my my wife’s name is Amber. So she like looked over because she works in the same space. Are you talking to me? I’m like no, no, no! Different different amber, different amber.
67 00:06:52.970 ⇒ 00:06:55.630 Amber Lin: How is this? Is this audio? Better?
68 00:06:55.980 ⇒ 00:06:56.660 Alex K: Yes. Yeah.
69 00:06:56.660 ⇒ 00:06:57.360 Demilade Agboola: Much better.
70 00:06:57.360 ⇒ 00:07:00.619 Amber Lin: Okay, okay, I join on my phone for audio.
71 00:07:01.560 ⇒ 00:07:04.089 Amber Lin: So I was looking at
72 00:07:04.220 ⇒ 00:07:13.860 Amber Lin: these tickets. So these are the ad hoc ones that gonna got added and talk as we talked about yesterday, we’re gonna save around 20 to 4, 20,
73 00:07:14.571 ⇒ 00:07:21.209 Amber Lin: to 30% for ad hoc tickets as they come up so we can feel more comfortable about adding them.
74 00:07:21.670 ⇒ 00:07:31.940 Amber Lin: And then and here’s the parts we have for inventory. That’s also oh.
75 00:07:32.850 ⇒ 00:07:36.390 Amber Lin: that’s also an ad hoc. So we have.
76 00:07:37.676 ⇒ 00:07:38.430 Amber Lin: I think
77 00:07:39.200 ⇒ 00:07:46.799 Amber Lin: Emily is. I was just checking. If these this is done, and then we have these ones that’s in cycle.
78 00:07:49.110 ⇒ 00:07:49.790 Amber Lin: Okay.
79 00:07:50.470 ⇒ 00:07:52.360 Emily Giant: This being sorry.
80 00:07:54.180 ⇒ 00:07:54.710 Amber Lin: This form.
81 00:07:54.710 ⇒ 00:08:02.129 Emily Giant: Yes. Well not. It’s it’s it. The Pr has been issued and is reviewing.
82 00:08:02.710 ⇒ 00:08:05.050 Amber Lin: Okay. Sounds good. Just gonna scoot that.
83 00:08:05.050 ⇒ 00:08:05.410 Emily Giant: I.
84 00:08:05.410 ⇒ 00:08:07.110 Amber Lin: To a different status.
85 00:08:07.700 ⇒ 00:08:09.800 Amber Lin: All good, all good. So
86 00:08:10.170 ⇒ 00:08:23.309 Amber Lin: what we plan for inventory is we’re gonna go over the existing models. The big ones, break them down and then use them to replace the current models. Those 3 steps. And Demo is mostly gonna be in charge with that.
87 00:08:28.560 ⇒ 00:08:32.230 Amber Lin: Yeah, I guess. Let’s talk about. Let’s talk about the due dates
88 00:08:32.539 ⇒ 00:08:35.490 Amber Lin: that we want to assign to.
89 00:08:36.612 ⇒ 00:08:37.517 Amber Lin: You should.
90 00:08:38.659 ⇒ 00:08:40.900 Amber Lin: There’s a different lot of, I guess.
91 00:08:41.179 ⇒ 00:08:44.040 Amber Lin: When do you think these are gonna be done.
92 00:08:46.298 ⇒ 00:08:51.500 Demilade Agboola: So I should be done. So the spring starts. Today. I should be done going with the models.
93 00:08:53.010 ⇒ 00:08:53.650 Amber Lin: By.
94 00:08:53.650 ⇒ 00:08:54.100 Amber Lin: Okay.
95 00:08:54.100 ⇒ 00:08:54.720 Demilade Agboola: Day.
96 00:08:55.934 ⇒ 00:08:57.990 Amber Lin: So this is Thursday.
97 00:08:59.380 ⇒ 00:09:04.510 Amber Lin: And then I know the next step is to break them down when would that be.
98 00:09:06.084 ⇒ 00:09:15.480 Demilade Agboola: So that involves like actually building out the models and testing the models so potentially, that is about
99 00:09:15.850 ⇒ 00:09:19.190 Demilade Agboola: about 5 days of work they’re about.
100 00:09:22.820 ⇒ 00:09:24.960 Demilade Agboola: So it will probably be
101 00:09:28.060 ⇒ 00:09:32.690 Demilade Agboola: so if that’s Thursday we’re looking at like next week, Thursday thereabouts.
102 00:09:33.530 ⇒ 00:09:39.240 Amber Lin: Oh, we said 5 Points. If it’s 5 days, then I don’t think this is a
103 00:09:39.440 ⇒ 00:09:42.440 Amber Lin: I don’t think this is an accurate time. Estimate.
104 00:09:44.270 ⇒ 00:09:44.940 Demilade Agboola: So
105 00:09:49.830 ⇒ 00:09:53.680 Demilade Agboola: what would the accurate time estimate be then in terms of.
106 00:09:53.680 ⇒ 00:09:56.169 Amber Lin: Oh, oh, I mean the point estimates.
107 00:09:56.480 ⇒ 00:10:18.719 Amber Lin: I think that would be if it’s 5 days, and it’s gonna be 8 points. So this is a very large task. I mean 5 days. We are usually referring to, say, 2 days ish, and then 8 8 points is when we need to really break it down. Sounds like to me that this ticket we can. We can break it down further. So it’s not a huge ticket.
108 00:10:20.578 ⇒ 00:10:24.399 Demilade Agboola: Sure, so we could maybe split into building and testing. But like.
109 00:10:27.240 ⇒ 00:10:28.689 Uttam Kumaran: Can you click into this
110 00:10:31.780 ⇒ 00:10:36.049 Uttam Kumaran: like? Is there a list of the models that are going to.
111 00:10:36.680 ⇒ 00:10:39.530 Amber Lin: We don’t have a yeah, because we we need.
112 00:10:39.530 ⇒ 00:10:45.759 Demilade Agboola: Alpute. Yeah, it’s the Alpute of going over these models and then breaking them down to smaller models.
113 00:10:46.780 ⇒ 00:10:48.079 Demilade Agboola: And then
114 00:10:49.180 ⇒ 00:11:00.110 Demilade Agboola: that would be the outcome. Once that’s done, once the auditing, like going over the models and auditing has been done, because then build and test the new models which would then eventually replace
115 00:11:00.710 ⇒ 00:11:02.630 Demilade Agboola: the current models that exist.
116 00:11:03.060 ⇒ 00:11:08.540 Uttam Kumaran: So I think you should just put this as an 8 pointer. Put something in the title that says like needs
117 00:11:08.710 ⇒ 00:11:11.940 Uttam Kumaran: grooming, and then when you get to it, it just break it down.
118 00:11:17.150 ⇒ 00:11:18.470 Uttam Kumaran: So once you do the audit.
119 00:11:18.470 ⇒ 00:11:19.080 Amber Lin: So.
120 00:11:19.270 ⇒ 00:11:23.849 Uttam Kumaran: Then break this down by either like folder or by.
121 00:11:24.440 ⇒ 00:11:30.080 Uttam Kumaran: If you can break into logical like 2 to 5 point chunks. That’s ideal.
122 00:11:37.760 ⇒ 00:11:44.350 Amber Lin: Awesome. I’m gonna put a due date for
123 00:11:52.430 ⇒ 00:11:57.220 Amber Lin: Oh, what? What time is next? Thursday?
124 00:11:58.050 ⇒ 00:11:59.120 Amber Lin: Let’s see.
125 00:12:01.800 ⇒ 00:12:04.259 Amber Lin: Okay, sounds good.
126 00:12:04.390 ⇒ 00:12:07.180 Amber Lin: 19.th
127 00:12:13.840 ⇒ 00:12:20.240 Amber Lin: Okay? And then I imagine this one would be done after that.
128 00:12:20.940 ⇒ 00:12:22.809 Amber Lin: So that will be a Monday.
129 00:12:23.380 ⇒ 00:12:23.980 Amber Lin: Okay.
130 00:12:23.980 ⇒ 00:12:28.940 Demilade Agboola: Yeah. Worst worst case scenario. The building I test is the real heavy load.
131 00:12:29.490 ⇒ 00:12:30.340 Amber Lin: Okay.
132 00:12:31.541 ⇒ 00:12:40.159 Amber Lin: sounds good. And I assigned these 2 to Kyle. So to do the code base cleanup. And I think this would help
133 00:12:40.670 ⇒ 00:12:45.390 Amber Lin: help Kyle get familiar with the inventory Mars.
134 00:12:47.280 ⇒ 00:12:57.730 Amber Lin: And okay, let’s see, yeah. And Kyle. Then when do you think these can be?
135 00:12:58.680 ⇒ 00:13:00.060 Amber Lin: These can be done.
136 00:13:02.145 ⇒ 00:13:04.519 Caio Velasco: I’ll have to take a look at them and then.
137 00:13:04.970 ⇒ 00:13:10.595 Caio Velasco: How many files, and if it’s just really moving, or if it requires something else,
138 00:13:11.780 ⇒ 00:13:15.299 Caio Velasco: then maybe give me a day or 2.
139 00:13:15.560 ⇒ 00:13:17.119 Caio Velasco: and then I can re update.
140 00:13:18.400 ⇒ 00:13:23.759 Uttam Kumaran: So for these, can we just set them all for Friday? Then, if we’re not, if we’re like, at least it’s gonna happen this week.
141 00:13:24.800 ⇒ 00:13:26.289 Caio Velasco: Okay, I like that.
142 00:13:31.480 ⇒ 00:13:32.535 Amber Lin: Alright
143 00:13:34.390 ⇒ 00:13:36.719 Amber Lin: Let’s look at.
144 00:13:37.090 ⇒ 00:13:44.270 Amber Lin: Let’s look at revenue Emily. When we 1st made this ticket, you said you were. Gonna take this.
145 00:13:44.800 ⇒ 00:13:49.679 Amber Lin: How long do you think this would take you? When do you think it can be done?
146 00:13:49.940 ⇒ 00:13:51.910 Emily Giant: For audit revenue. Can you please.
147 00:13:51.910 ⇒ 00:13:52.850 Amber Lin: Click, into.
148 00:13:52.850 ⇒ 00:13:56.970 Emily Giant: I just want to see, like what the acceptance criteria is. List all revenue models.
149 00:13:57.180 ⇒ 00:14:01.880 Emily Giant: I think it’ll take 1 point, because I’ve already done the lion’s share of it.
150 00:14:03.160 ⇒ 00:14:10.360 Emily Giant: Okay, so done. 2 points worth for sure. But it is okay.
151 00:14:11.160 ⇒ 00:14:14.499 Amber Lin: Oh, sounds good. So this is actually in progress.
152 00:14:14.680 ⇒ 00:14:15.360 Emily Giant: Yeah.
153 00:14:15.670 ⇒ 00:14:24.060 Amber Lin: Do you want to? Want them to meet with you? Because we talked about it yesterday? It might be helpful if we go through it together.
154 00:14:24.250 ⇒ 00:14:35.849 Emily Giant: Let’s meet if tomorrow. I was planning on meeting with Kyle in the morning during the 1 h meeting session. But if I on Thursday we can.
155 00:14:35.850 ⇒ 00:14:36.480 Amber Lin: Hmm.
156 00:14:36.480 ⇒ 00:14:40.630 Emily Giant: Can use our hour to go over these models.
157 00:14:41.380 ⇒ 00:14:42.020 Amber Lin: Hmm.
158 00:14:42.470 ⇒ 00:14:43.509 Emily Giant: Does that work for you?
159 00:14:43.510 ⇒ 00:14:44.220 Emily Giant: Mobile.
160 00:14:46.540 ⇒ 00:14:48.210 Demilade Agboola: Oh, on Thursday, sure.
161 00:14:48.540 ⇒ 00:14:53.669 Emily Giant: Cool. Okay, I’ll add that to the fellow that that’s what we’re planning to do for Thursday.
162 00:14:55.150 ⇒ 00:15:02.730 Amber Lin: So I would say that I mean, I think the majority of this will be done by Thursday. And then Thursday. You guys can discuss this.
163 00:15:05.770 ⇒ 00:15:06.490 Emily Giant: Yeah.
164 00:15:06.520 ⇒ 00:15:19.970 Amber Lin: Okay, awesome. I’m gonna put this as Thursday and looking at looking at these.
165 00:15:23.790 ⇒ 00:15:31.170 Amber Lin: So Kyle, these, I think these these 2 are from last cycle.
166 00:15:31.840 ⇒ 00:15:37.700 Amber Lin: Think this one probably language.
167 00:15:40.685 ⇒ 00:15:45.600 Amber Lin: So we have flagging it by accuracy.
168 00:15:48.760 ⇒ 00:15:59.929 Amber Lin: And then deprecating unused looker dashboards or marking them to be deprecated. And then we’re gonna scope out the unused
169 00:16:00.070 ⇒ 00:16:05.129 Amber Lin: or the the used but inaccurate dashboards that we need to rebuild.
170 00:16:06.316 ⇒ 00:16:12.280 Amber Lin: I think just quickly, Emily, this one is done right, rating the model’s accuracy.
171 00:16:12.280 ⇒ 00:16:16.185 Amber Lin: No sorry that needs to be bumped to this current sprint.
172 00:16:17.240 ⇒ 00:16:18.080 Emily Giant: Yeah.
173 00:16:18.240 ⇒ 00:16:23.830 Amber Lin: So let’s would that would you be able to do that? Say, today.
174 00:16:25.411 ⇒ 00:16:32.489 Emily Giant: I. So I had a rather critical like very large task pop up with.
175 00:16:32.490 ⇒ 00:16:33.230 Amber Lin: Okay.
176 00:16:33.230 ⇒ 00:16:38.310 Emily Giant: Product tables. So I want to say, yes, but tomorrow would be safe.
177 00:16:39.220 ⇒ 00:16:47.830 Emily Giant: Okay, blocking. I can finish it today. But I really have to make sure.
178 00:16:47.830 ⇒ 00:16:48.830 Amber Lin: I see.
179 00:16:48.830 ⇒ 00:16:49.380 Emily Giant: Phone number.
180 00:16:49.590 ⇒ 00:17:00.720 Amber Lin: Okay, I see. You’re meeting with Kyle tomorrow, right? Maybe this could be something that you guys do together tomorrow in the meeting, because Kyle needs this to
181 00:17:01.000 ⇒ 00:17:04.609 Amber Lin: flag the different looker dashboards.
182 00:17:05.270 ⇒ 00:17:07.889 Emily Giant: Great. Yeah, does that sound? Okay? Kyle.
183 00:17:08.190 ⇒ 00:17:09.821 Caio Velasco: Yes, perfect for me.
184 00:17:10.230 ⇒ 00:17:13.459 Amber Lin: Okay, so I’m gonna mark this to tomorrow.
185 00:17:17.700 ⇒ 00:17:20.299 Amber Lin: Okay? And then.
186 00:17:22.950 ⇒ 00:17:27.959 Amber Lin: So I think this one, we can because we do have usage data.
187 00:17:28.567 ⇒ 00:17:44.109 Amber Lin: I know, Kyle. Yesterday you were able to deprecate the unused ingestion tables. Do you think this is something that we can start right away to start, especially the ones that’s untouched.
188 00:17:44.310 ⇒ 00:17:49.139 Amber Lin: We can do the same that we did for the ingestion tables, and start to deprecate them.
189 00:17:50.680 ⇒ 00:17:51.520 Caio Velasco: Yeah. So I think
190 00:17:52.000 ⇒ 00:17:57.310 Caio Velasco: they are kind of connected. The one that we were talking before. And I think
191 00:17:57.730 ⇒ 00:18:08.909 Caio Velasco: from the meeting we had. I remember that we were also talking about starting with 3 years old, 2 years old, going to that direction. So theoretically, this would need also to be run by Emily
192 00:18:10.770 ⇒ 00:18:13.100 Caio Velasco: And then, remembering also that we.
193 00:18:14.230 ⇒ 00:18:18.417 Amber Lin: We also have the digested people’s part. But then it’s something else. Okay,
194 00:18:20.610 ⇒ 00:18:21.190 Caio Velasco: Yeah, so.
195 00:18:21.620 ⇒ 00:18:24.880 Caio Velasco: I think they are kind of dependent one on on the other.
196 00:18:25.090 ⇒ 00:18:29.621 Caio Velasco: I can. I can try to look and see what I can filter.
197 00:18:30.170 ⇒ 00:18:36.029 Caio Velasco: but this is something that we have to do also within. And I was expecting to do that also in working sessions.
198 00:18:36.400 ⇒ 00:18:40.000 Amber Lin: Oh, okay. So into. So in tomorrow’s session.
199 00:18:40.390 ⇒ 00:18:40.970 Caio Velasco: Yeah.
200 00:18:41.430 ⇒ 00:18:42.050 Amber Lin: I see.
201 00:18:42.050 ⇒ 00:18:49.170 Emily Giant: Yeah, able to finish it during tomorrow’s because we’re doing the other one. We can hit that one on Friday.
202 00:18:49.830 ⇒ 00:18:50.930 Caio Velasco: Perfect perfect.
203 00:18:51.677 ⇒ 00:18:58.639 Caio Velasco: anyway, at least from tomorrow I’ll have some also some more guidance, and then I can also do work until Friday, and then we we can try.
204 00:18:59.620 ⇒ 00:19:00.640 Emily Giant: Yeah, that’s.
205 00:19:03.140 ⇒ 00:19:11.830 Amber Lin: Okay, so right? So that’s gonna be worked on tomorrow.
206 00:19:17.600 ⇒ 00:19:18.889 Amber Lin: let’s see.
207 00:19:19.990 ⇒ 00:19:23.740 Amber Lin: Okay, so this one, we should say, by.
208 00:19:29.350 ⇒ 00:19:30.440 Amber Lin: Oh.
209 00:19:32.730 ⇒ 00:19:36.419 Caio Velasco: Hi, I’m back. I think my connection super unstable today.
210 00:19:36.970 ⇒ 00:19:37.690 Amber Lin: Hmm.
211 00:19:39.384 ⇒ 00:20:00.249 Amber Lin: I I think I want input from, do you think this is a okay? If we do rating the accuracy 1st and then deprecate the dashboards. Later, I my, my instinct tells me that maybe we should start. We should prioritize this 1 1.st
212 00:20:00.977 ⇒ 00:20:03.120 Amber Lin: But what do you guys think.
213 00:20:04.420 ⇒ 00:20:09.260 Demilade Agboola: Yeah, I I think we should deprecate, based off usage. First, st like things.
214 00:20:09.260 ⇒ 00:20:09.700 Amber Lin: I’m hoping.
215 00:20:09.700 ⇒ 00:20:12.209 Demilade Agboola: Use doesn’t really need my phone
216 00:20:12.868 ⇒ 00:20:16.291 Demilade Agboola: and then, once we have a solid
217 00:20:16.950 ⇒ 00:20:21.069 Demilade Agboola: collection of dashboards that we know are being used, we can then start to like. Look at the
218 00:20:22.100 ⇒ 00:20:22.670 Demilade Agboola: one further.
219 00:20:22.670 ⇒ 00:20:29.353 Amber Lin: Okay, okay, okay, that gives me more confidence. So I’m gonna put this as tomorrow. And I’m gonna move that to
220 00:20:30.130 ⇒ 00:20:31.739 Amber Lin: to a later date.
221 00:20:33.120 ⇒ 00:20:42.759 Amber Lin: So maybe, Emily, can you? Maybe if you have time, you can look on this on your own, and then you got you and Kyle can meet again on Friday on this.
222 00:20:42.930 ⇒ 00:20:47.450 Amber Lin: So let’s say, this is maybe Thursday.
223 00:20:49.200 ⇒ 00:20:50.270 Amber Lin: I know.
224 00:20:50.270 ⇒ 00:20:51.080 Caio Velasco: From my.
225 00:20:52.100 ⇒ 00:20:52.810 Amber Lin: Pardon me.
226 00:20:53.830 ⇒ 00:20:57.642 Caio Velasco: No, I was. I was just gonna say something about these, reduced
227 00:20:58.230 ⇒ 00:21:02.270 Caio Velasco: because we we have the something being used or unused in terms of some.
228 00:21:02.270 ⇒ 00:21:02.710 Amber Lin: Thank you.
229 00:21:02.710 ⇒ 00:21:06.069 Caio Velasco: It or not. But if we also have unused in a
230 00:21:06.240 ⇒ 00:21:11.259 Caio Velasco: use it statistic, for which being we have to define what is used in.
231 00:21:11.260 ⇒ 00:21:11.619 Amber Lin: What do you know?
232 00:21:11.620 ⇒ 00:21:16.739 Caio Velasco: Used first, st but I think kind of this would be to step back to step before that.
233 00:21:16.960 ⇒ 00:21:20.510 Caio Velasco: And that’s why it requires also input from Emily, although I cannot.
234 00:21:20.510 ⇒ 00:21:21.379 Amber Lin: Yeah, I see.
235 00:21:21.380 ⇒ 00:21:22.780 Caio Velasco: It’s something. Yes.
236 00:21:23.083 ⇒ 00:21:31.589 Amber Lin: Yeah. I think tomorrow’s meeting. We can just use to talk about this one. And then we can. We can talk about this later, and maybe on Friday.
237 00:21:32.494 ⇒ 00:21:36.930 Amber Lin: So I’ll say, this is by Fried Friday,
238 00:21:41.080 ⇒ 00:22:09.200 Amber Lin: and then I think this will require, when we scope it out, things that we need to rebuild cause Emily. I remember when we talk when we 1st started this engagement, we said, you guys would be in charge of rebuilding the dashboards. So we were talking about. Okay, we’ll we’ll do the. We’ll try and give you guys as much help you with the requirements as possible. But let let us know how we can assist on this one.
239 00:22:15.400 ⇒ 00:22:20.149 Emily Giant: I I think the assistance is like all of the the work that
240 00:22:20.420 ⇒ 00:22:28.830 Emily Giant: we’re doing to make the data accurate like, it will be much easier to rebuild the dashboards when there are so many
241 00:22:28.960 ⇒ 00:22:42.229 Emily Giant: dated issues that the dashboards may very well be okay once it is reliable. So it’s difficult
242 00:22:42.350 ⇒ 00:22:47.949 Emily Giant: like, are? Is the question more like, what is missing from
243 00:22:48.300 ⇒ 00:22:50.709 Emily Giant: the analysis that we’d like to build.
244 00:22:50.710 ⇒ 00:23:13.722 Amber Lin: Oh, sorry. Sorry. Yeah. My my question was that after we do the audit and we have a list of we’re gonna end up with a list of dashboards that’s inaccurate, because we looked at a Dbt model server, and the the dashboards are not accurate, but it’s used by the different analyst owners. And so this is about
245 00:23:14.450 ⇒ 00:23:43.529 Amber Lin: if we’re gonna just rebuild them from scratch because we’re gonna rebuild the Dbt models that they they’re based off of anyways, we need to scope out each dashboard that needs to be rebuilt. We need to notify and work with the analyst owner. We need to tell them between. Tell them the difference between the new replacement that we build versus the original one they have, and then we need to get sign off, and we know we want to know when to turn off the old one. So each dashboard is
246 00:23:43.530 ⇒ 00:23:46.909 Amber Lin: its own mini project in itself, and I was thinking.
247 00:23:46.910 ⇒ 00:23:58.350 Amber Lin: how do you guys want us to scope that for you? Or do you want to? You want to work directly, work with the analyst owners on that like. How would this? How would this go.
248 00:23:58.590 ⇒ 00:24:06.650 Emily Giant: I feel like this would be a good piece to take that meeting with all of the analysts on Thursdays. We’re trying to plan.
249 00:24:07.050 ⇒ 00:24:07.960 Amber Lin: Oh!
250 00:24:08.180 ⇒ 00:24:16.250 Emily Giant: Would be the primary like point of contact, for, like missing fields like
251 00:24:16.880 ⇒ 00:24:29.479 Emily Giant: how like the analysis that they need versus what they have. But I I’m not sure that I could speak for everyone on that front, and it would probably be a better use of time to just use that
252 00:24:29.740 ⇒ 00:24:34.970 Emily Giant: that meeting so that we’re all on the same page. I’m concerned that like.
253 00:24:35.900 ⇒ 00:24:41.889 Emily Giant: if one of the Brainforge members wasn’t at that meeting that
254 00:24:42.980 ⇒ 00:24:49.020 Emily Giant: like it would be a game of telephone with, like what those stakeholders need.
255 00:24:50.280 ⇒ 00:24:54.960 Emily Giant: I definitely utilize that time to like nail down how
256 00:24:55.500 ⇒ 00:25:01.230 Emily Giant: the dashboards, or what needs to be available in the dashboards, and from there I think the analysts should be able to
257 00:25:02.170 ⇒ 00:25:06.299 Emily Giant: do a lot of this themselves, and then bring it to us.
258 00:25:06.300 ⇒ 00:25:06.770 Amber Lin: Awesome.
259 00:25:06.910 ⇒ 00:25:13.169 Emily Giant: How I imagine it in terms of like giving them agency and understanding.
260 00:25:13.170 ⇒ 00:25:13.820 Amber Lin: And.
261 00:25:15.710 ⇒ 00:25:17.400 Emily Giant: But I don’t know. Maybe that’s
262 00:25:17.880 ⇒ 00:25:23.329 Emily Giant: a backward way to look at it like not building it out for them and saying, Here, this is what you asked for.
263 00:25:23.490 ⇒ 00:25:25.230 Emily Giant: But, Alex, what.
264 00:25:25.230 ⇒ 00:25:27.180 Amber Lin: Like, yeah, what do you guys.
265 00:25:27.180 ⇒ 00:25:31.360 Emily Giant: From like stakeholder, bringing it back to us
266 00:25:31.570 ⇒ 00:25:34.410 Emily Giant: to audit instead of like the other way around.
267 00:25:34.410 ⇒ 00:25:38.800 Alex K: Yeah, it absolutely should be stakeholder exploratory, like exploration
268 00:25:38.900 ⇒ 00:25:43.799 Alex K: with with the stakeholders. Right? Like, I think you have usage stats. You know what they’re using.
269 00:25:44.340 ⇒ 00:25:46.620 Alex K: I’d say you you
270 00:25:46.720 ⇒ 00:25:50.060 Alex K: you can cut a lot of them right like there’s a lot that you can cut
271 00:25:50.370 ⇒ 00:25:51.940 Alex K: that you know. You can cut
272 00:25:52.100 ⇒ 00:25:55.870 Alex K: the ones that you don’t know you can cut. I think you just talk with them about it.
273 00:25:56.160 ⇒ 00:25:58.840 Alex K: and I would err on the side of cutting more.
274 00:25:59.060 ⇒ 00:25:59.600 Emily Giant: Got it.
275 00:25:59.600 ⇒ 00:26:05.000 Alex K: Then what am I trying to say? I would air cut more than we think we need to
276 00:26:05.240 ⇒ 00:26:08.319 Alex K: like? Don’t be safe, is what I’m trying to say, because, like, you can always bring it back.
277 00:26:08.470 ⇒ 00:26:12.259 Alex K: and that will spark the conversation if it’s truly actually used.
278 00:26:12.480 ⇒ 00:26:15.880 Alex K: So if it’s not, if nobody says anything. Then it’s not actually used.
279 00:26:16.920 ⇒ 00:26:17.320 Amber Lin: So.
280 00:26:17.320 ⇒ 00:26:20.090 Alex K: Air err on the side of calling more than less.
281 00:26:23.200 ⇒ 00:26:25.820 Alex K: That’s how we’ll force issues out of the woodwork.
282 00:26:30.030 ⇒ 00:26:31.105 Amber Lin: Awesome.
283 00:26:32.820 ⇒ 00:26:43.180 Amber Lin: alright cause we are aiming for a meeting on thursday, so it can either be this thursday, or it can be next Thursday, and it’ll be great.
284 00:26:43.180 ⇒ 00:26:46.129 Alex K: You’re gonna need multiple meetings right? This is not like a
285 00:26:46.250 ⇒ 00:26:54.130 Alex K: one and done thing. This is like a overtime kind of thing. So I don’t know how you want to break that down, but the least that’s how I see this like there’s no way this is getting done in one.
286 00:26:54.130 ⇒ 00:26:55.770 Uttam Kumaran: Yeah, there’s
287 00:26:55.770 ⇒ 00:27:01.749 Uttam Kumaran: this is gonna take, like, a probably like 4 or 5 meetings with, like each person individually, probably owning one area.
288 00:27:02.300 ⇒ 00:27:08.349 Amber Lin: Okay, I need to meet join.
289 00:27:09.320 ⇒ 00:27:10.840 Amber Lin: Make sure it’s
290 00:27:13.070 ⇒ 00:27:26.340 Amber Lin: okay. I think, if possible, I’m gonna try and make this Thursday meeting work I’ve got, I think, 3 responses so far, I think they’re continuing to respond. So whoever I can get on Thursday’s meeting, I’m gonna
291 00:27:26.590 ⇒ 00:27:38.290 Amber Lin: try and get as much requirements from them as possible. And then, once we have more data, I can, we’ll do another Thursday meeting. So I’m going to.
292 00:27:39.130 ⇒ 00:27:41.319 Amber Lin: This is a big task.
293 00:27:43.410 ⇒ 00:27:48.390 Amber Lin: Ideally, I’m gonna aim for, I think, aim for the
294 00:27:48.980 ⇒ 00:27:53.139 Amber Lin: end of cycle. I also need, I think, should break this down.
295 00:27:54.240 ⇒ 00:27:54.619 Uttam Kumaran: Take a shirt.
296 00:27:54.620 ⇒ 00:27:55.210 Amber Lin: Take the standby.
297 00:27:55.210 ⇒ 00:27:56.320 Uttam Kumaran: Domain.
298 00:27:56.550 ⇒ 00:28:00.920 Amber Lin: Yeah. Need to.
299 00:28:05.830 ⇒ 00:28:07.820 Amber Lin: Okay. Sounds good.
300 00:28:12.990 ⇒ 00:28:16.950 Amber Lin: Okay, duplicate unused dashboards.
301 00:28:19.340 ⇒ 00:28:29.309 Amber Lin: cost estimate of turning off ingestion tables. I think once we turn them off, and we can start to look at
302 00:28:29.956 ⇒ 00:28:35.319 Amber Lin: what is the cost equivalent of turning off those tables?
303 00:28:36.370 ⇒ 00:28:41.896 Amber Lin: And this one
304 00:28:44.720 ⇒ 00:28:48.329 Amber Lin: I was think I was looking at. Where’s the other?
305 00:28:49.310 ⇒ 00:28:52.130 Amber Lin: It’s good. So the 1, 2,
306 00:28:56.000 ⇒ 00:28:59.540 Amber Lin: this one there’s a lot of.
307 00:28:59.770 ⇒ 00:29:05.080 Amber Lin: So the dashboards that’s
308 00:29:08.290 ⇒ 00:29:15.749 Amber Lin: So for each DVD model to look at the da looker dashboards that it’s that it’s supporting.
309 00:29:18.300 ⇒ 00:29:20.939 Amber Lin: Has there been any progress on that one.
310 00:29:22.465 ⇒ 00:29:23.814 Demilade Agboola: Not particularly
311 00:29:25.410 ⇒ 00:29:33.560 Demilade Agboola: I would have to look at that today. And then I’ll look at the look. Ml, that powers the different dashboards.
312 00:29:33.750 ⇒ 00:29:38.470 Demilade Agboola: and then use that, but potentially
313 00:29:39.790 ⇒ 00:29:45.519 Demilade Agboola: it will be something where it’ll it’ll be best to look at it from the perspective of
314 00:29:47.480 ⇒ 00:29:59.859 Demilade Agboola: the used dashboards. So not necessarily just like every single dashboard, because there’s a lot going on there. But potentially also just factor in like, are we just like, which of the these dashboards.
315 00:30:00.740 ⇒ 00:30:04.219 Demilade Agboola: Are we like linking them to
316 00:30:06.360 ⇒ 00:30:08.610 Demilade Agboola: And that would be helpful. So it’s not.
317 00:30:09.410 ⇒ 00:30:10.710 Demilade Agboola: Seriously. A lot going on.
318 00:30:11.760 ⇒ 00:30:15.760 Amber Lin: I see, okay.
319 00:30:16.960 ⇒ 00:30:20.369 Demilade Agboola: Also at this point I need to drop now. Unfortunately.
320 00:30:21.040 ⇒ 00:30:21.470 Amber Lin: Oh!
321 00:30:21.470 ⇒ 00:30:23.060 Demilade Agboola: Oh, yeah.
322 00:30:24.725 ⇒ 00:30:25.100 Amber Lin: Yeah.
323 00:30:25.100 ⇒ 00:30:27.290 Uttam Kumaran: Yeah, go ahead, Demilotti, I mentioned, I can cover.
324 00:30:27.570 ⇒ 00:30:42.339 Amber Lin: Okay, sounds good. Let me just quickly look at each person’s assignments by demote. Let me look at assignments and see how we are in terms of effort. I think Demo has a lot more than Kyle, currently.
325 00:30:43.250 ⇒ 00:30:47.569 Amber Lin: And looking at these.
326 00:30:59.110 ⇒ 00:31:02.950 Amber Lin: okay, all right.
327 00:31:04.170 ⇒ 00:31:05.730 Amber Lin: So
328 00:31:25.320 ⇒ 00:31:31.440 Amber Lin: think this one will come after after the audit.
329 00:31:43.500 ⇒ 00:31:44.300 Amber Lin: Okay?
330 00:31:48.390 ⇒ 00:31:51.590 Amber Lin: I guess Utam, I want your input. On
331 00:31:52.430 ⇒ 00:31:56.820 Amber Lin: this. I’m thinking of moving some of dam lotties tasks to
332 00:31:57.140 ⇒ 00:32:01.109 Amber Lin: Kyle, based on what we see with the points here.
333 00:32:02.400 ⇒ 00:32:03.080 Amber Lin: Oh.
334 00:32:03.470 ⇒ 00:32:07.389 Uttam Kumaran: Yeah. So I mean, I don’t think some of these aren’t pointed.
335 00:32:08.660 ⇒ 00:32:09.700 Uttam Kumaran: So
336 00:32:09.850 ⇒ 00:32:14.809 Uttam Kumaran: can we just assign points to some of them right now and then you can get a better picture.
337 00:32:15.150 ⇒ 00:32:19.109 Amber Lin: Yeah, Emily. Sorry. Emily, can you help with.
338 00:32:19.690 ⇒ 00:32:24.759 Uttam Kumaran: I can help with. I can help with assigning points. So let’s just click through every everyone that doesn’t have points.
339 00:32:24.760 ⇒ 00:32:29.390 Amber Lin: Okay, so right here, this one.
340 00:32:29.390 ⇒ 00:32:32.670 Uttam Kumaran: So can you open it? I don’t. I don’t know what’s what this is.
341 00:32:34.880 ⇒ 00:32:37.529 Uttam Kumaran: This is. Gonna be like 1 point
342 00:32:48.568 ⇒ 00:32:51.150 Uttam Kumaran: this is, gonna be like 2 points.
343 00:32:56.190 ⇒ 00:32:56.889 Uttam Kumaran: Same thing.
344 00:32:56.890 ⇒ 00:33:01.559 Amber Lin: That’s Mpi Review. Okay, that’s Npr. Review.
345 00:33:01.730 ⇒ 00:33:03.080 Uttam Kumaran: Let’s just assign points.
346 00:33:03.080 ⇒ 00:33:08.359 Amber Lin: Okay, 2 points.
347 00:33:09.030 ⇒ 00:33:11.290 Amber Lin: And last one, this one.
348 00:33:14.461 ⇒ 00:33:16.430 Uttam Kumaran: This is gonna be like 5 points.
349 00:33:20.120 ⇒ 00:33:26.309 Amber Lin: This is the one that’s got that has gotten broken down. So I wasn’t sure if I should cancel this one.
350 00:33:30.430 ⇒ 00:33:31.890 Emily Giant: Yeah, you can.
351 00:33:32.180 ⇒ 00:33:34.150 Amber Lin: Okay. Sounds good.
352 00:33:34.660 ⇒ 00:33:37.070 Uttam Kumaran: And say canceled.
353 00:33:39.050 ⇒ 00:33:40.150 Amber Lin: All right.
354 00:33:40.540 ⇒ 00:33:44.610 Uttam Kumaran: And then, can we? Can we point everything that’s on Emily’s play as well.
355 00:33:48.270 ⇒ 00:33:49.459 Uttam Kumaran: So can you click into it?
356 00:33:55.845 ⇒ 00:34:03.500 Emily Giant: This one is the foundational elements of this are in Pr, but it was like a 2.
357 00:34:04.580 ⇒ 00:34:05.170 Amber Lin: Hmm.
358 00:34:07.370 ⇒ 00:34:15.929 Emily Giant: I will need to. Once I have my meeting with the stakeholders today, though I’m I’m gonna need to add on to that ticket. But should I just create
359 00:34:16.610 ⇒ 00:34:18.138 Emily Giant: for the additional like?
360 00:34:19.199 ⇒ 00:34:23.270 Emily Giant: For that was like the building block that needed to happen to move forward.
361 00:34:23.270 ⇒ 00:34:23.850 Amber Lin: Okay.
362 00:34:23.850 ⇒ 00:34:32.620 Emily Giant: But it will have, like additional models that will be built based on stakeholder needs. So do you want.
363 00:34:32.909 ⇒ 00:34:41.659 Amber Lin: Yeah, let’s let’s make a new. Yeah. Let’s make a new ticket. I’m trying not to do subtax because it gets lost in linear.
364 00:34:42.270 ⇒ 00:34:45.524 Emily Giant: Okay, I will do that today. During or after that meeting.
365 00:34:45.820 ⇒ 00:34:47.020 Amber Lin: Sounds good.
366 00:34:48.120 ⇒ 00:34:50.400 Amber Lin: Dvd model accuracy.
367 00:34:53.190 ⇒ 00:34:53.670 Emily Giant: Oh!
368 00:34:53.679 ⇒ 00:34:58.270 Uttam Kumaran: I think this is like 2 points, probably contact sometime.
369 00:35:02.700 ⇒ 00:35:03.760 Amber Lin: This one.
370 00:35:07.297 ⇒ 00:35:12.439 Emily Giant: One. I mean it won’t take, and let’s do 2 instead, because the testing.
371 00:35:20.670 ⇒ 00:35:21.853 Emily Giant: I already did this.
372 00:35:22.400 ⇒ 00:35:22.970 Amber Lin: Oh!
373 00:35:23.820 ⇒ 00:35:26.494 Emily Giant: It was probably 3 points, but.
374 00:35:26.940 ⇒ 00:35:27.760 Amber Lin: I see.
375 00:35:28.550 ⇒ 00:35:33.320 Emily Giant: I think maybe I was looking at this sprint a lot accidentally during our last.
376 00:35:36.000 ⇒ 00:35:36.760 Emily Giant: Okay.
377 00:35:39.230 ⇒ 00:35:42.379 Amber Lin: Okay, and Otam for you. You have 2 tickets.
378 00:35:44.252 ⇒ 00:35:49.869 Uttam Kumaran: Yeah, these are both like just conversations I need to have. So both of these are one points.
379 00:35:52.890 ⇒ 00:35:57.269 Uttam Kumaran: like, can you just put like explore, like, we’re not gonna use any of these tools? I just need to like.
380 00:35:57.270 ⇒ 00:35:58.699 Uttam Kumaran: I see, okay.
381 00:35:59.040 ⇒ 00:36:00.290 Amber Lin: Sounds good.
382 00:36:06.000 ⇒ 00:36:08.180 Uttam Kumaran: Or this is like a spike, basically.
383 00:36:12.070 ⇒ 00:36:18.940 Amber Lin: okay, sounds good. Oh.
384 00:36:24.870 ⇒ 00:36:32.130 Amber Lin: I want due dates on these and the ad, hoc, tasks.
385 00:36:35.130 ⇒ 00:36:40.130 Uttam Kumaran: Don’t I? I mean, I would just make sure everything, at least, has like end of this week or end of next week.
386 00:36:40.310 ⇒ 00:36:43.080 Amber Lin: It’s only 2 weeks. So yeah,
387 00:36:44.490 ⇒ 00:36:48.089 Amber Lin: Emily, I mean, I imagine these are urgent.
388 00:36:48.450 ⇒ 00:36:48.970 Amber Lin: Right?
389 00:36:49.630 ⇒ 00:36:53.290 Amber Lin: So I, this means.
390 00:36:53.290 ⇒ 00:36:57.459 Emily Giant: The create test. And dbt, we? He did that. That’s done.
391 00:36:57.460 ⇒ 00:36:58.520 Amber Lin: Okay.
392 00:36:59.052 ⇒ 00:37:02.777 Emily Giant: So the analysis is not urgent. No,
393 00:37:03.310 ⇒ 00:37:03.840 Amber Lin: Okay.
394 00:37:04.570 ⇒ 00:37:07.457 Emily Giant: But will be very helpful in the future.
395 00:37:08.180 ⇒ 00:37:10.749 Amber Lin: So I think I’ll make this next Friday.
396 00:37:11.370 ⇒ 00:37:12.259 Emily Giant: Yeah, that’s fine.
397 00:37:12.260 ⇒ 00:37:14.740 Amber Lin: Okay, active.
398 00:37:15.560 ⇒ 00:37:20.620 Amber Lin: Next Friday, Friday.
399 00:37:24.640 ⇒ 00:37:30.670 Amber Lin: This is today. It has been done all right.
400 00:37:32.120 ⇒ 00:37:41.180 Amber Lin: This one is for revenue. So identify what it can be, it will have to go after.
401 00:37:41.460 ⇒ 00:37:45.420 Amber Lin: Well, after we audit the revenue models.
402 00:37:45.710 ⇒ 00:37:51.819 Amber Lin: So if that’s June 12, th when is June 12? th So maybe.
403 00:37:52.640 ⇒ 00:37:53.580 Amber Lin: Hmm.
404 00:38:00.560 ⇒ 00:38:05.809 Amber Lin: I think, Demolade said he, will add requirements on this later.
405 00:38:07.370 ⇒ 00:38:10.520 Amber Lin: Once we have the audit state, I’m thinking,
406 00:38:17.530 ⇒ 00:38:19.970 Amber Lin: Friday, Monday.
407 00:38:24.900 ⇒ 00:38:34.660 Amber Lin: And then, lastly, for for this one Emily is, that is, when do you think you would do that?
408 00:38:36.433 ⇒ 00:38:39.070 Emily Giant: That can be due by end of week this week.
409 00:38:39.070 ⇒ 00:38:41.819 Amber Lin: Okay, it sounds good.
410 00:38:42.130 ⇒ 00:38:47.428 Emily Giant: It’s deployed. I just need to like. Add it into the looker.
411 00:38:54.390 ⇒ 00:38:55.790 Amber Lin: Sounds good. Yeah.
412 00:38:57.010 ⇒ 00:39:06.879 Amber Lin: Okay, let’s look at the workload for everyone. I think me I’m thinking, moving some stuff from Demode to Kyle.
413 00:39:07.590 ⇒ 00:39:14.080 Amber Lin: Think for, and maybe for this one.
414 00:39:25.790 ⇒ 00:39:27.819 Caio Velasco: Yeah, this one makes sense to be.
415 00:39:28.640 ⇒ 00:39:30.310 Caio Velasco: Do the Unders? Yes.
416 00:39:30.660 ⇒ 00:39:31.580 Amber Lin: Okay.
417 00:39:32.710 ⇒ 00:39:39.890 Amber Lin: So then, maybe today might be a little.
418 00:39:40.130 ⇒ 00:39:42.619 Amber Lin: do you think this can be due today?
419 00:39:43.890 ⇒ 00:39:45.729 Amber Lin: Or you need more time.
420 00:39:47.990 ⇒ 00:39:50.370 Caio Velasco: I think this is also dependent on
421 00:39:50.800 ⇒ 00:39:56.650 Caio Velasco: the rest. I don’t know if the miller has ended the All the Dbt model list.
422 00:39:57.500 ⇒ 00:39:58.070 Amber Lin: Okay.
423 00:40:00.780 ⇒ 00:40:02.649 Caio Velasco: Do we have the list of all the DVD.
424 00:40:02.650 ⇒ 00:40:03.990 Uttam Kumaran: Hey? Can you open this ticket.
425 00:40:03.990 ⇒ 00:40:05.060 Caio Velasco: Already.
426 00:40:06.600 ⇒ 00:40:10.029 Uttam Kumaran: Yeah, I mean, do we have? Do we have a list of all the Dbt models.
427 00:40:10.470 ⇒ 00:40:13.870 Amber Lin: I guess that’s a question for.
428 00:40:14.190 ⇒ 00:40:16.220 Emily Giant: Yeah, it. Looks like it.
429 00:40:17.050 ⇒ 00:40:19.069 Amber Lin: I mean, I believe we did
430 00:40:19.290 ⇒ 00:40:23.070 Amber Lin: have a full list when we did the initial Dbt.
431 00:40:23.510 ⇒ 00:40:24.710 Amber Lin: Sponsors.
432 00:40:24.990 ⇒ 00:40:28.760 Emily Giant: Yeah, we do 50.
433 00:40:28.760 ⇒ 00:40:30.990 Uttam Kumaran: Can we? Can we link? Can we link it in here.
434 00:40:31.140 ⇒ 00:40:33.660 Amber Lin: Yeah, I’m good. I’m looking for that.
435 00:40:34.240 ⇒ 00:40:35.549 Emily Giant: I got it I’ll send it to you in the.
436 00:40:35.550 ⇒ 00:40:37.410 Amber Lin: Oh, okay, thanks.
437 00:40:38.740 ⇒ 00:40:41.290 Amber Lin: The tab is just called Dbt models.
438 00:40:41.730 ⇒ 00:40:43.030 Amber Lin: Oh, okay.
439 00:40:45.460 ⇒ 00:40:46.000 Emily Giant: Yeah.
440 00:40:46.280 ⇒ 00:40:52.120 Amber Lin: Got. It sounds good.
441 00:40:53.060 ⇒ 00:40:55.649 Amber Lin: So we have all DVD models that we can
442 00:40:57.180 ⇒ 00:41:00.220 Amber Lin: note which looker dashboard is supporting.
443 00:41:02.120 ⇒ 00:41:02.900 Amber Lin: Oh.
444 00:41:07.100 ⇒ 00:41:09.070 Amber Lin: what happened?
445 00:41:15.320 ⇒ 00:41:16.160 Amber Lin: Yeah.
446 00:41:21.190 ⇒ 00:41:29.750 Amber Lin: think we add, okay, and
447 00:41:35.100 ⇒ 00:41:36.630 Amber Lin: I think it probably.
448 00:41:36.840 ⇒ 00:41:50.389 Amber Lin: Kyle, you’ll be able to help Demode. And once he breaks down this task, probably you guys can work together to break down the bigger models.
449 00:41:52.950 ⇒ 00:41:56.410 Caio Velasco: Yeah, yeah, anything related to models?
450 00:41:56.590 ⇒ 00:41:59.290 Caio Velasco: Yeah, I just need to be speeded up on.
451 00:42:00.210 ⇒ 00:42:00.889 Caio Velasco: What on the.
452 00:42:00.890 ⇒ 00:42:01.230 Amber Lin: Okay.
453 00:42:01.230 ⇒ 00:42:03.760 Caio Velasco: On the model side. And yeah, I can catch up with him.
454 00:42:08.100 ⇒ 00:42:09.680 Amber Lin: Breakdown.
455 00:42:21.910 ⇒ 00:42:23.540 Amber Lin: Okay? Sounds good.
456 00:42:23.810 ⇒ 00:42:28.800 Amber Lin: Think last 2 things. We’re gonna look at these 2 ones. This is after.
457 00:42:29.070 ⇒ 00:42:41.600 Amber Lin: Think, after the initial revenue audit that Emily is going to do so, I would say, Gotcha
458 00:42:51.360 ⇒ 00:42:53.650 Amber Lin: think maybe, by
459 00:42:58.810 ⇒ 00:42:59.690 Amber Lin: hmm!
460 00:43:06.440 ⇒ 00:43:12.109 Amber Lin: Let’s say next Tuesday, then this one.
461 00:43:14.100 ⇒ 00:43:21.490 Amber Lin: So this one relates 1 14 relates to 1 13.
462 00:43:21.960 ⇒ 00:43:30.640 Amber Lin: So say this, we can do maybe end of this week.
463 00:43:31.470 ⇒ 00:43:36.730 Amber Lin: Okay, let’s look at the due days and then see if they are, they make sense?
464 00:43:37.830 ⇒ 00:43:40.330 Amber Lin: Can someone help me? I don’t think this is.
465 00:43:40.670 ⇒ 00:43:41.960 Amber Lin: I don’t think this.
466 00:43:41.960 ⇒ 00:43:42.599 Uttam Kumaran: Yeah, maybe we can.
467 00:43:42.600 ⇒ 00:43:43.420 Amber Lin: Can do this.
468 00:43:43.420 ⇒ 00:43:44.379 Uttam Kumaran: Fine amber, I think.
469 00:43:44.380 ⇒ 00:43:44.790 Amber Lin: Okay.
470 00:43:44.790 ⇒ 00:43:46.719 Uttam Kumaran: Maybe we can take a look at this after.
471 00:43:46.720 ⇒ 00:43:48.630 Uttam Kumaran: Okay, look at all the dates.
472 00:43:48.800 ⇒ 00:43:49.450 Amber Lin: Great
473 00:43:50.541 ⇒ 00:43:57.759 Amber Lin: I think workload is pretty good after Demoda assigns the rebuilding to Kyle. I think we’ll balance out.
474 00:43:58.070 ⇒ 00:44:02.040 Amber Lin: and then I’ll adjust the due date, so that it works for everyone.
475 00:44:03.680 ⇒ 00:44:10.490 Uttam Kumaran: Okay? So then, by this Friday, like, we’re like, what are the top? What are the high level items that we’re like hoping to get done.
476 00:44:12.070 ⇒ 00:44:18.240 Amber Lin: So this Friday, I think that’s why that’s mark a few by priority, then.
477 00:44:20.280 ⇒ 00:44:21.140 Amber Lin: So.
478 00:44:21.140 ⇒ 00:44:21.700 Uttam Kumaran: All right.
479 00:44:22.603 ⇒ 00:44:32.769 Amber Lin: Let’s just get assigned priorities to each one. So the ones high priority deprecate unused high priority
480 00:44:33.590 ⇒ 00:44:35.250 Amber Lin: flag, flag.
481 00:44:35.450 ⇒ 00:44:36.330 Amber Lin: Think.
482 00:44:50.280 ⇒ 00:45:03.080 Uttam Kumaran: I think maybe it’s fine. Maybe let’s maybe I I don’t want to waste everyone’s time here. Maybe we can take take a look at all the due dates after this and take a look at the priorities, and then we can send a little update in slack on, like what we’re hoping to get done this week.
483 00:45:03.080 ⇒ 00:45:08.170 Amber Lin: Sounds good. Do you want? Can you stay on me for another 15 min?
484 00:45:08.520 ⇒ 00:45:09.850 Uttam Kumaran: Yeah, I can stay on.
485 00:45:09.850 ⇒ 00:45:11.470 Amber Lin: Okay. Sounds good.
486 00:45:12.390 ⇒ 00:45:13.010 Uttam Kumaran: Okay.
487 00:45:13.500 ⇒ 00:45:17.590 Amber Lin: Yeah, thank you. Everyone. We’ll send an update to you guys later.
488 00:45:18.190 ⇒ 00:45:18.960 Emily Giant: Thanks.
489 00:45:19.070 ⇒ 00:45:19.770 Alex K: Thank you.
490 00:45:20.070 ⇒ 00:45:21.760 Amber Lin: Okay, bye-bye.
491 00:45:26.750 ⇒ 00:45:29.120 Amber Lin: Hi, help help!
492 00:45:29.910 ⇒ 00:45:31.670 Uttam Kumaran: I just don’t alright. I send a.
493 00:45:31.670 ⇒ 00:45:32.110 Amber Lin: Interesting.
494 00:45:32.110 ⇒ 00:45:32.900 Uttam Kumaran: Back.
495 00:45:32.900 ⇒ 00:45:37.799 Amber Lin: Yeah, I just don’t know why we got to this meeting without all this stuff set up yet.
496 00:45:38.800 ⇒ 00:45:39.380 Amber Lin: I know.
497 00:45:39.380 ⇒ 00:45:42.530 Uttam Kumaran: Like like we.
498 00:45:43.450 ⇒ 00:45:46.929 Uttam Kumaran: I just, I mean, I think, overall, my feedback is like we.
499 00:45:47.720 ⇒ 00:45:53.229 Uttam Kumaran: We clearly didn’t have, like most of the tickets weren’t assigned or had points, or
500 00:45:53.710 ⇒ 00:45:56.030 Uttam Kumaran: like had due dates, I think, like
501 00:45:58.080 ⇒ 00:46:01.379 Uttam Kumaran: Also this, like, I sent a couple of notes in the project channel.
502 00:46:02.130 ⇒ 00:46:08.529 Uttam Kumaran: There’s some reading to do, I think on like how to run a good kickoff like we shouldn’t be sort of like
503 00:46:08.910 ⇒ 00:46:11.430 Uttam Kumaran: winging this one cause, I think.
504 00:46:12.100 ⇒ 00:46:15.799 Uttam Kumaran: it’s like how to run a kickoff is pretty like
505 00:46:16.310 ⇒ 00:46:20.090 Uttam Kumaran: determined we we shouldn’t, it should. This is not a grooming session
506 00:46:20.550 ⇒ 00:46:23.149 Uttam Kumaran: so like anything that isn’t groomed, we should just
507 00:46:23.290 ⇒ 00:46:26.460 Uttam Kumaran: move the kickoff, because otherwise this meeting is gonna be really tough.
508 00:46:27.310 ⇒ 00:46:28.810 Amber Lin: I felt like.
509 00:46:29.150 ⇒ 00:46:33.779 Uttam Kumaran: Yeah, but like, there’s stuff with no points, there’s stuff with no, none of the stuff of priority.
510 00:46:34.220 ⇒ 00:46:37.499 Uttam Kumaran: Some of the tickets still don’t have descriptions
511 00:46:38.340 ⇒ 00:46:43.450 Uttam Kumaran: like, I just felt like this was kind of like a like. We just didn’t get a lot of work done before this.
512 00:46:44.050 ⇒ 00:46:46.852 Amber Lin: You know, I know I agree.
513 00:46:48.500 ⇒ 00:46:51.590 Uttam Kumaran: So like, what what should we do like.
514 00:46:52.360 ⇒ 00:46:53.130 Amber Lin: Okay.
515 00:46:53.680 ⇒ 00:46:56.360 Uttam Kumaran: Like, what’s what’s the what’s the next step here?
516 00:46:56.360 ⇒ 00:47:10.239 Amber Lin: I mean at this point we unfortunately spent that session a bit of time doing what we should have done before. So right now I want your help to assign the due, assign the priorities, and then help me look at the due dates.
517 00:47:11.540 ⇒ 00:47:16.129 Uttam Kumaran: I. So I think, in terms of due dates. I think you have to get that from the engineers like
518 00:47:16.260 ⇒ 00:47:25.479 Uttam Kumaran: we can’t just throw due dates around. Otherwise nothing’s gonna get done. I mean, the number one thing is, you 1st have to commit to all this work is, gonna get done this sprint
519 00:47:26.230 ⇒ 00:47:33.350 Uttam Kumaran: right? Like everything’s gonna get done in the next 2 weeks. So that’s the 1st commitment. And there’s there’s a couple of other articles I sent on like what other
520 00:47:33.350 ⇒ 00:47:35.109 Uttam Kumaran: commitments to get.
521 00:47:35.320 ⇒ 00:47:42.619 Uttam Kumaran: I think, like I don’t like. I’m not the best one. I think you have to go meet with Kyle and demalada, and getting all the info on these.
522 00:47:42.960 ⇒ 00:47:43.300 Amber Lin: Hmm.
523 00:47:43.300 ⇒ 00:47:55.099 Uttam Kumaran: It is a. It is a meeting that has to happen. And if you need 2 or 3, 4 h of groom, that’s what has to happen like I’m not the best. I’m not taking on these tickets like the details should come from them.
524 00:47:57.750 ⇒ 00:48:01.880 Uttam Kumaran: Like I I just I I know we only it looks like we only had just the one.
525 00:48:02.450 ⇒ 00:48:07.799 Uttam Kumaran: We only had the one grooming meeting, but like it’s clear you need another 2 or 3 h to meet with just with them.
526 00:48:07.800 ⇒ 00:48:08.880 Uttam Kumaran: So you should
527 00:48:08.880 ⇒ 00:48:14.299 Uttam Kumaran: grab time with with those 2 to meet like you don’t need to wait. I’m not. There’s no way I can join those.
528 00:48:14.870 ⇒ 00:48:16.500 Amber Lin: No, that’s okay.
529 00:48:16.800 ⇒ 00:48:27.000 Uttam Kumaran: So I would just call them and see if they can meet today and and like, make sure that all of these have due dates, have estimations, and have priorities, and have filled tickets.
530 00:48:27.900 ⇒ 00:48:28.860 Amber Lin: Okay.
531 00:48:29.810 ⇒ 00:48:32.879 Uttam Kumaran: That’s my suggestion. I’m like I I can’t. I can’t.
532 00:48:32.880 ⇒ 00:48:40.210 Amber Lin: Yeah, I agree. I agree. I just realized that how much grooming needs to go into this. Oh, dear.
533 00:48:41.270 ⇒ 00:48:42.020 Uttam Kumaran: Yeah.
534 00:48:42.270 ⇒ 00:48:50.312 Amber Lin: Okay. Sounds good. I’ll go try and catch them a lot of 1st I need him to help me with the priorities, and then I’ll go call Kyle.
535 00:48:50.790 ⇒ 00:48:56.480 Uttam Kumaran: Yeah, it’s not. They have to help you with those things like, and you have to hound them until they get you all the information.
536 00:48:56.890 ⇒ 00:49:02.119 Uttam Kumaran: Because it’s clear like, even in this meeting it wasn’t clear like, what’s getting done. Who’s doing it? All those things so.
537 00:49:02.660 ⇒ 00:49:03.809 Uttam Kumaran: I I mean, like
538 00:49:04.200 ⇒ 00:49:09.979 Uttam Kumaran: we, I think, like we should probably just run an Async kickoff a as soon as, like all those things are done.
539 00:49:09.980 ⇒ 00:49:10.330 Uttam Kumaran: and you can
540 00:49:10.330 ⇒ 00:49:16.470 Uttam Kumaran: share like what’s gonna get done? Because for me, I want to know what’s getting done this week. What’s getting done next week
541 00:49:16.570 ⇒ 00:49:21.529 Uttam Kumaran: that way when Friday comes, and those things aren’t done, I could say, Hey, where are those things? That’s what I need to know.
542 00:49:21.530 ⇒ 00:49:22.420 Amber Lin: Hmm! I see.
543 00:49:23.830 ⇒ 00:49:28.879 Uttam Kumaran: You know. So those are the big that’s like, that’s what’s important to me, as like the
544 00:49:29.170 ⇒ 00:49:32.059 Uttam Kumaran: on the sales side, just to know, like what I can promise.
545 00:49:32.890 ⇒ 00:49:35.710 Uttam Kumaran: Because we also want to translate that to Zack and Alex.
546 00:49:43.000 ⇒ 00:49:44.800 Amber Lin: sounds good.
547 00:49:45.970 ⇒ 00:49:53.919 Amber Lin: next time, also, just feel free in the meeting mid meeting, if it if you think it’s going a wrong direction. Just
548 00:49:54.340 ⇒ 00:49:56.660 Amber Lin: just chime in and tell me.
549 00:49:57.240 ⇒ 00:50:02.172 Uttam Kumaran: No, I I sent you a zoom. Oh, I try. So I tried to send a slack, and I was like, Oh, I don’t know.
550 00:50:02.370 ⇒ 00:50:02.769 Amber Lin: To you.
551 00:50:02.770 ⇒ 00:50:05.549 Uttam Kumaran: I wanted to see. I wanted to see how it’s gonna go.
552 00:50:05.900 ⇒ 00:50:06.480 Uttam Kumaran: But
553 00:50:07.270 ⇒ 00:50:17.820 Amber Lin: That didn’t go that well, I felt like I was dragging, but it was because I’ve I felt under mid meeting. I was like, I feel so unprepared and feel like it’s.
554 00:50:17.820 ⇒ 00:50:21.600 Uttam Kumaran: It should just be like yo. This we’re clearly not there yet. We shouldn’t do this right now.
555 00:50:21.600 ⇒ 00:50:22.510 Amber Lin: Okay.
556 00:50:22.730 ⇒ 00:50:23.140 Uttam Kumaran: Yeah.
557 00:50:23.140 ⇒ 00:50:23.860 Amber Lin: Sounds good.
558 00:50:23.860 ⇒ 00:50:27.820 Uttam Kumaran: Because it’s gonna confuse. It’s just gonna lead to a lot of confusion from everybody.
559 00:50:29.300 ⇒ 00:50:29.960 Uttam Kumaran: You know.
560 00:50:30.350 ⇒ 00:50:32.069 Amber Lin: Okay, I agree.
561 00:50:32.930 ⇒ 00:50:38.159 Amber Lin: Alright. Thank you. I’m gonna go see when Timah is free.
562 00:50:38.320 ⇒ 00:50:40.839 Uttam Kumaran: Okay, you got it just like I, I would just like.
563 00:50:40.840 ⇒ 00:50:41.400 Amber Lin: Yeah.
564 00:50:41.560 ⇒ 00:50:45.820 Uttam Kumaran: Th those meetings like have to go to have to be crisp because there’s a
565 00:50:46.300 ⇒ 00:50:51.030 Uttam Kumaran: it’s just. It’s hard to get all 5 of of these people on the on the phone at 1 point. So.
566 00:50:51.030 ⇒ 00:50:52.510 Amber Lin: Yeah. Totally.
567 00:50:53.500 ⇒ 00:50:54.100 Uttam Kumaran: Okay.
568 00:50:54.350 ⇒ 00:50:55.150 Amber Lin: Okay.
569 00:50:55.150 ⇒ 00:50:55.860 Uttam Kumaran: Okay. Cool.
570 00:50:55.860 ⇒ 00:50:57.660 Amber Lin: Talk to you later. Bye, bye.