Meeting Title: Brainforge Data Governance Sync Date: 2025-07-24 Meeting participants: jessicacampbell, Perry’s Fellow Note Taker, pk.arthur, ianbiles, Emily Giant, Demilade Agboola, felipefaria, Uttam Kumaran, Amber Lin, perry, Alex K
WEBVTT
1 00:02:58.560 ⇒ 00:02:59.946 Demilade Agboola: How long?
2 00:03:01.550 ⇒ 00:03:07.769 Demilade Agboola: Think we can give like a couple more minutes, maybe one or 2 min before everyone joins, and we can start.
3 00:03:16.100 ⇒ 00:03:21.219 Emily Giant: And I’ll look and see that if anyone declined or is out of office today.
4 00:03:21.420 ⇒ 00:03:24.000 Emily Giant: So we’ve got a lot of the group which is good.
5 00:03:27.250 ⇒ 00:03:28.560 Demilade Agboola: That’s exciting.
6 00:04:05.906 ⇒ 00:04:09.239 Demilade Agboola: So this session will be a bit more
7 00:04:10.430 ⇒ 00:04:20.890 Demilade Agboola: interactive in the sense that I would also like to hear opinions from the sales team about things are working, things aren’t working.
8 00:04:21.420 ⇒ 00:04:26.360 Demilade Agboola: and also just in terms of
9 00:04:26.640 ⇒ 00:04:31.559 Demilade Agboola: how we want to proceed with certain things. It will be great to hear from Devon Sam’s team.
10 00:04:33.135 ⇒ 00:04:36.770 Demilade Agboola: So you can kind of get into it right now.
11 00:04:37.330 ⇒ 00:04:42.660 Demilade Agboola: So the overview we’re gonna talk about like deprecation. And
12 00:04:43.090 ⇒ 00:04:45.120 Demilade Agboola: I’ve had some coming along so far.
13 00:04:46.061 ⇒ 00:04:49.270 Demilade Agboola: We’re gonna have a conversation about data governance.
14 00:04:49.600 ⇒ 00:04:50.890 Demilade Agboola: I’m just like
15 00:04:51.080 ⇒ 00:04:58.440 Demilade Agboola: the utility of models that have already been pushed into production and apparent some of the current dashboards.
16 00:05:01.560 ⇒ 00:05:04.619 Demilade Agboola: So we discovered that, like with
17 00:05:05.300 ⇒ 00:05:11.160 Demilade Agboola: the audit process that we did, we figured out some of the logic was just sprawling all over the place.
18 00:05:11.753 ⇒ 00:05:15.830 Demilade Agboola: It was hard to like find central locations for what was going on.
19 00:05:16.585 ⇒ 00:05:27.000 Demilade Agboola: Tables are white where you have like 300 columns in one table, it’s hard to utilize, it can be overwhelming. And also it can also be very hard to debug.
20 00:05:27.850 ⇒ 00:05:38.369 Demilade Agboola: And then with Looker, there were 837 dashboards, a lot of use, a lot of explores not a lot being actively utilized.
21 00:05:39.180 ⇒ 00:05:44.209 Demilade Agboola: and then redshift. There were so many tables, and just like a lot going on there.
22 00:05:45.337 ⇒ 00:05:54.020 Demilade Agboola: But part of what we’ve been doing to just ensure things are in order is that we’ve tried to, you know, rebuild the inventory, flow
23 00:05:54.240 ⇒ 00:05:56.455 Demilade Agboola: from start to finish.
24 00:05:57.150 ⇒ 00:06:02.190 Demilade Agboola: So we have, like cleaner data. Things are in one
25 00:06:02.540 ⇒ 00:06:11.899 Demilade Agboola: central location in the sense that if you want to figure out what’s going on with your orders, with the transactions and inventory.
26 00:06:12.100 ⇒ 00:06:16.259 Demilade Agboola: you don’t necessarily have to go to multiple places. It’s kind of just like
27 00:06:16.690 ⇒ 00:06:19.866 Demilade Agboola: all in one table and one spot.
28 00:06:21.220 ⇒ 00:06:26.379 Demilade Agboola: and we try to make it like as close to real time as possible, which is like every 30 min.
29 00:06:27.020 ⇒ 00:06:35.999 Demilade Agboola: And then with looker we’ve been, we’ve moved things to archive voice off like in our soft deletion process, and we plan to delete things.
30 00:06:36.621 ⇒ 00:06:39.269 Demilade Agboola: About the next couple of sprints.
31 00:06:39.490 ⇒ 00:06:45.660 Demilade Agboola: We have some dashboards left, and then we’ve also archived a lot of the tables and
32 00:06:46.060 ⇒ 00:06:50.399 Demilade Agboola: unused views which would also be ready for deletion very soon.
33 00:06:52.110 ⇒ 00:06:59.350 Demilade Agboola: Right now we’re currently looking at revenue and we’re trying to like nail down the business logic of everything.
34 00:07:00.406 ⇒ 00:07:05.820 Demilade Agboola: And then we plan to like, construct and build things out, get the
35 00:07:06.220 ⇒ 00:07:11.709 Demilade Agboola: buying from stakeholders and rolled out like dashboards. People can utilize them
36 00:07:12.190 ⇒ 00:07:17.100 Demilade Agboola: and also document them so that everyone knows what’s going on with revenue
37 00:07:20.190 ⇒ 00:07:24.490 Demilade Agboola: But that also leads us to like data governance discussions.
38 00:07:25.250 ⇒ 00:07:34.889 Demilade Agboola: And I feel like it’s important that we come to a spot where we have a good understanding of the principles that guides the open, the same team and looker.
39 00:07:35.460 ⇒ 00:07:43.030 Demilade Agboola: and I think, high level. What this looks like is I always.
40 00:07:43.330 ⇒ 00:07:49.049 Demilade Agboola: I always recommend the appointment of data stewards like 1, 2, or 3 people who
41 00:07:50.190 ⇒ 00:08:00.060 Demilade Agboola: they keep an eye out on, just like the data sanctity internally of like the like. Looker. So what does that look like? Ensuring that like
42 00:08:02.690 ⇒ 00:08:12.449 Demilade Agboola: when we have dashboards. If you look at the bottom, we have a dashboard for under user. Still, dashboards and looks just people who will look out for that
43 00:08:12.690 ⇒ 00:08:15.059 Demilade Agboola: so that numbers don’t go out of hand.
44 00:08:16.126 ⇒ 00:08:20.740 Demilade Agboola: People who ensure that like things that are
45 00:08:20.850 ⇒ 00:08:24.439 Demilade Agboola: unused can be archived and eventually deleted.
46 00:08:25.238 ⇒ 00:08:29.229 Demilade Agboola: People who just always remind the team of
47 00:08:29.520 ⇒ 00:08:36.250 Demilade Agboola: the meeting look once like single use looks if you create a look or a
48 00:08:36.470 ⇒ 00:08:49.120 Demilade Agboola: project or report, and you’re done with it, just reminding the team that you know, we need to get rid of these things so that it will accumulate over, you know, years. And we have a lot of things that becomes too hard to manage.
49 00:08:49.410 ⇒ 00:08:56.669 Demilade Agboola: also just standardizing the folder nomenclature, so just ensuring that, like naming conversions, are pretty standard and pretty clear
50 00:08:57.150 ⇒ 00:09:02.470 Demilade Agboola: and just ensuring that whatever means that are utilized
51 00:09:02.860 ⇒ 00:09:05.540 Demilade Agboola: ensures that everyone knows what exists.
52 00:09:05.800 ⇒ 00:09:08.319 Demilade Agboola: and and she knows where to look for things.
53 00:09:08.720 ⇒ 00:09:13.130 Demilade Agboola: So what that means is, if you are looking for
54 00:09:13.510 ⇒ 00:09:18.279 Demilade Agboola: something on revenue or something on inventory or something on.
55 00:09:18.620 ⇒ 00:09:29.160 Demilade Agboola: you know, marketing, or whatever you know where to go to. So you don’t end up building things that other people have built, and we just have like duplicates. Things happen all over
56 00:09:29.350 ⇒ 00:09:31.130 Demilade Agboola: our local infrastructure.
57 00:09:32.170 ⇒ 00:09:38.390 Demilade Agboola: 3 would also be like reviewing, who needs to be able to do looks and dashboards.
58 00:09:39.245 ⇒ 00:09:40.970 Demilade Agboola: I know that
59 00:09:41.350 ⇒ 00:09:47.760 Demilade Agboola: sometimes, because of the availability of data, everyone, you know hops in there and just tries to build their own thing.
60 00:09:47.870 ⇒ 00:09:52.989 Demilade Agboola: which obviously has its utility and cell service, is definitely very helpful.
61 00:09:55.120 ⇒ 00:09:57.129 Demilade Agboola: But just kind of figuring out like
62 00:09:57.310 ⇒ 00:10:00.880 Demilade Agboola: oh, like is, should there be a process to building these things?
63 00:10:01.050 ⇒ 00:10:02.279 Demilade Agboola: Would there be
64 00:10:02.480 ⇒ 00:10:07.739 Demilade Agboola: a safeguard to building these things? And what does that safeguard look like in your best team.
65 00:10:07.840 ⇒ 00:10:14.279 Demilade Agboola: just so that we don’t, you know, have so much going on there, and they’re just like
66 00:10:14.937 ⇒ 00:10:17.262 Demilade Agboola: clean up on a regular cadence
67 00:10:17.790 ⇒ 00:10:21.659 Demilade Agboola: before might be here, but like it could be.
68 00:10:21.900 ⇒ 00:10:23.710 Demilade Agboola: But the idea is, there needs to be
69 00:10:24.140 ⇒ 00:10:28.630 Demilade Agboola: conscious effort to ensure that things just don’t get out of hand.
70 00:10:29.590 ⇒ 00:10:33.730 Demilade Agboola: and that whenever things are being built
71 00:10:34.650 ⇒ 00:10:38.290 Demilade Agboola: and they’re not being utilized, they can be gotten rid of.
72 00:10:38.860 ⇒ 00:10:43.829 Demilade Agboola: And finally, we just basically having like a dashboard of underused or still dashboards and looks.
73 00:10:44.545 ⇒ 00:10:49.600 Demilade Agboola: That allows us to be able to quickly see what’s going on with the data
74 00:10:49.980 ⇒ 00:10:54.109 Demilade Agboola: dashboards, looks and can figure out which ones can we get rid of
75 00:10:54.917 ⇒ 00:11:11.990 Demilade Agboola: and potentially even see opportunities to merge certain things into other existing dashboards or looks? It’s possible. Someone has a look. And it’s like, okay, so this is valuable information. But this also just fits into this dashboard rather than have been a
76 00:11:12.980 ⇒ 00:11:17.279 Demilade Agboola: look that is not being utilized as much, or, you know.
77 00:11:17.570 ⇒ 00:11:24.919 Demilade Agboola: isn’t necessarily the best. It’s just standing alone. How are we integrated into a dashboard that currently exists.
78 00:11:25.130 ⇒ 00:11:28.690 Demilade Agboola: and that allows us to have one less thing to take care of.
79 00:11:29.090 ⇒ 00:11:33.394 Demilade Agboola: So this is especially. This part is especially where
80 00:11:33.910 ⇒ 00:11:39.379 Demilade Agboola: things should be interactive. The idea is, everyone here walks through data
81 00:11:39.590 ⇒ 00:11:45.080 Demilade Agboola: fairly, consistently, and that allows us to know the issues we’re seeing
82 00:11:45.914 ⇒ 00:11:55.660 Demilade Agboola: and how can we all like come together to figure out how to not get into a state where we have so many unused data objects.
83 00:11:56.770 ⇒ 00:11:58.810 Demilade Agboola: But right now the flows will continue on.
84 00:12:12.010 ⇒ 00:12:18.340 felipefaria: Hey, de Milady, I just have a question here on this effort, and just to clean up
85 00:12:18.620 ⇒ 00:12:29.339 felipefaria: unused that. And this is essentially mainly around dashboards, or look, or does it apply to looks as well? Because, I’m thinking.
86 00:12:31.330 ⇒ 00:12:39.230 felipefaria: we might create several looks that we might not use regularly right. But if it’s all coming from the same sort of
87 00:12:39.810 ⇒ 00:12:51.849 felipefaria: data set, and that data set is maintained, and make sure that all the measures there are working properly, then. That wouldn’t necessarily be
88 00:12:52.220 ⇒ 00:13:01.310 felipefaria: an issue right of having like several looks there. So I just want to understand, kind of like, the the effort to clean up? Is it?
89 00:13:01.550 ⇒ 00:13:15.399 felipefaria: Is it mainly so? There is less maintenance on these dashboards, or is there like a cost factor that we that we incur with some of these providers, where, like, you know, the more dashboards, the more looks we have, the more we pay.
90 00:13:17.770 ⇒ 00:13:18.270 Demilade Agboola: So
91 00:13:19.120 ⇒ 00:13:25.299 Demilade Agboola: of it definitely, there’s some looks or dashboards are not going to be utilized every day or every week.
92 00:13:25.530 ⇒ 00:13:29.319 Demilade Agboola: Some are potentially monthly dashboards or monthly looks.
93 00:13:29.878 ⇒ 00:13:36.980 Demilade Agboola: I think those are clearly those will be clearly stated and clearly organized, and we can always know what those are.
94 00:13:37.190 ⇒ 00:13:45.490 Demilade Agboola: I think the issue is when there are dashboards or looks that have existed for years and months unutilized.
95 00:13:45.620 ⇒ 00:13:51.529 Demilade Agboola: And when it’s like, Hey, who owns this? What’s going on here, and it’s like, Well, we’ve not used this in so long.
96 00:13:52.030 ⇒ 00:13:55.939 Demilade Agboola: It’s not necessarily the cost factor. It’s more of the
97 00:13:56.080 ⇒ 00:14:02.480 Demilade Agboola: fairly nice. I think the idea is creating a structure in which everyone knows where everything is.
98 00:14:02.670 ⇒ 00:14:07.100 Demilade Agboola: and can easily utilize what they need quite quickly.
99 00:14:07.210 ⇒ 00:14:14.050 Demilade Agboola: I can also see what developments other people are making across the teams. So, for instance, if they’re
100 00:14:14.930 ⇒ 00:14:23.779 Demilade Agboola: is there, if I’m working in, if I have a dashboard that I’m utilizing, being able to easily see
101 00:14:23.940 ⇒ 00:14:43.980 Demilade Agboola: what’s happening across board across the open sense team and landscape allows us to be able to maybe see number one potentially, there’s new data that we’re not aware of to potentially, there is a way to be able to represent data that could be more useful to you than what you currently have, but, like these things are harder to
102 00:14:44.080 ⇒ 00:14:48.200 Demilade Agboola: to see or observe. And we have over 800 dashboards
103 00:14:48.440 ⇒ 00:14:50.899 Demilade Agboola: right? It’s harder to be able to figure out
104 00:14:52.470 ⇒ 00:14:56.960 Demilade Agboola: how to handle things when you have so much, because at the end day
105 00:14:57.160 ⇒ 00:14:59.519 Demilade Agboola: you will just kind of find
106 00:15:00.370 ⇒ 00:15:06.539 Demilade Agboola: one or 2 things that you utilize. And if you want to build, if you want to find new data as well.
107 00:15:06.680 ⇒ 00:15:20.260 Demilade Agboola: you’re not going to go through 800 dashboards and figure out if that already exists for years. But we’re gonna create a look for yourself and get things done. And that continues to create that process where you have just more and more stuff. And it’s harder to utilize across. It’s harder to
108 00:15:21.340 ⇒ 00:15:28.130 Demilade Agboola: yeah. It’s hard to basically have that wealth of information that we can build on and just being able to have. That is very important
109 00:15:28.240 ⇒ 00:15:34.639 Demilade Agboola: to being able to see what people are doing and just being able to hop on that, and build off of that.
110 00:15:36.216 ⇒ 00:15:37.330 felipefaria: Got it?
111 00:15:39.330 ⇒ 00:15:40.230 felipefaria: Yeah.
112 00:15:40.450 ⇒ 00:16:08.529 felipefaria: And I see, like, I do agree that having a little bit more visibility into kind of like all of the other teams, dashboards, and clearly kind of like what are the most important dashboards that everybody uses and what is showing would be helpful. I know that in looker right now we do have a folder for essentially each of our teams right? But we also have some folders that are
113 00:16:08.780 ⇒ 00:16:12.519 felipefaria: that could potentially be merged within a specific
114 00:16:13.170 ⇒ 00:16:17.449 felipefaria: team right? Like our merge within a different folder here.
115 00:16:18.262 ⇒ 00:16:25.450 felipefaria: Maybe that. And that’s 1 way to kind of start. This processes
116 00:16:26.420 ⇒ 00:16:53.230 felipefaria: kind of from all the looks that are available, are they in a folder or not? Like, you know, and then just assigning kind of like this on Sem. Look, you should go in the look in the sem folder, and then each team could then do a swipe and see which of those looks. Dashboards are still relevant or not, because I understand that there’s a lot of
117 00:16:53.380 ⇒ 00:17:15.240 felipefaria: dashboards that were built like years ago, and they’re not necessarily accurate or relevant anymore. So so that’s 1 way that I would potentially go about cleaning things up is essentially just start putting those them in buckets and then assign each of the teams to just review everything and organize into.
118 00:17:15.430 ⇒ 00:17:33.999 felipefaria: like, you know, either subdivisions of that team like in our team. Snop, for example, there’s the demand side, and there’s the supply side. So there will be kind of like 2 different subfolders with, in which, within the snop folder, where, like, you know, all of our documents are separated, but also
119 00:17:34.080 ⇒ 00:17:57.819 felipefaria: some main dashboards that the Snlp team creates that are relevant for the whole company that wouldn’t necessarily be in those subfolders. Right? It would just be under the snlp folder, which is kind of like the daily inventory. Send one that and that Perry has, and it’s look it’s looked by a lot of people like for the care team. My understanding they might have like a lot of different
120 00:17:57.990 ⇒ 00:18:02.740 felipefaria: reports, kind of like, you know, on the nitty gritty. But
121 00:18:02.880 ⇒ 00:18:12.609 felipefaria: we would also wanna have like on my end. For example, if I’m looking for a dashboard from a different team like it would be for the care. So I can have, like an easy view of
122 00:18:12.720 ⇒ 00:18:17.070 felipefaria: what were the quality complaints by skew
123 00:18:18.010 ⇒ 00:18:20.810 felipefaria: for last week, or for a range of time.
124 00:18:20.920 ⇒ 00:18:24.933 felipefaria: And I know that they had this. But
125 00:18:25.590 ⇒ 00:18:33.390 felipefaria: It’s not very easy to access right now, like, especially if like if I go to the care
126 00:18:33.560 ⇒ 00:18:37.519 felipefaria: folder here like there’s actually like no, a bunch of different.
127 00:18:37.800 ⇒ 00:18:56.602 felipefaria: not a bunch of different. But there’s several different folders like there’s a care folder, and then there’s a care. Reports migrated from mode analytics folder, and then there’s a Qa. Folder all of these should could probably fall under the care
128 00:18:57.630 ⇒ 00:19:04.500 felipefaria: like, you know, main folder and then kind of like looking for that specific report that I know that it exists
129 00:19:04.800 ⇒ 00:19:14.019 felipefaria: right, but it’s not like easily accessible right now, but overall. I think that that and that should be an initiative of ours just to organize looker
130 00:19:14.190 ⇒ 00:19:16.769 felipefaria: and have kind of like, you know, each team
131 00:19:17.270 ⇒ 00:19:28.089 felipefaria: having, like main dashboards that is accessible and maintained for the visibility of the whole organization. Essentially, I don’t know if that’s the helpful. But that’s like my my thought on it.
132 00:19:29.960 ⇒ 00:19:55.090 Emily Giant: I I totally agree with you, Felipe. I think, also utilizing boards. For the reports that we know are shared like interdepartmentally. I’m a big user of looker boards. And then for the folder structure that’s more like internal team. But I also think, like on in addition to what you’re saying, because I think that’s all necessary for us to do. Is us being like the appointed
133 00:19:55.676 ⇒ 00:20:02.760 Emily Giant: cleaner uppers for our respective teams. Since we’re all the main report builders and just having like.
134 00:20:03.410 ⇒ 00:20:05.969 Emily Giant: even if it’s part of like, once we’ve
135 00:20:06.180 ⇒ 00:20:21.960 Emily Giant: got these new marts established, and we do a weekly meeting like taking 5 min of silence to like clean up our folders, just adding it into like a cadence of getting rid of things. We don’t need making sure our boards are up to date and like.
136 00:20:25.710 ⇒ 00:20:30.910 Emily Giant: if we have other members that are building, just making sure that they’re like
137 00:20:31.020 ⇒ 00:20:35.960 Emily Giant: staying within, like the parameters that we’ve set to keep it tidy.
138 00:20:37.950 ⇒ 00:20:53.939 Emily Giant: and also having like documentation on the governance, too. I think that, like a lot of initiatives that we’ve had to clean looker up. We’ve done it. It’s great for a minute, and then it explodes again, because there’s no like sop around
139 00:20:54.370 ⇒ 00:20:57.715 Emily Giant: any of it. We’re all just kind of like doing
140 00:20:58.350 ⇒ 00:21:25.299 Emily Giant: what we can as our own teams. So making sure that, like the care team, for example, that’s like my Frankenstein’s monster, those folders. I I did that yikes but if you needed to go and find something unless you asked me which folder because I didn’t ever document. What like the naming conventions mean? You could still wind up, clicking around for 25 min. So I think just like making sure that there’s definitions, and like
141 00:21:26.021 ⇒ 00:21:42.649 Emily Giant: where in looker, you can add, like the description of a folder or board like, make sure that those elements are also filled out. I’m trying to do that with like the new fields that we’re adding is to always add a description, and I think that that should just go like another layer of like making sure that
142 00:21:42.860 ⇒ 00:21:48.013 Emily Giant: people know what things are. So they don’t have to build it again in the 1st place, and
143 00:21:48.510 ⇒ 00:21:58.600 Emily Giant: just having, like someone, as the appointed oversight or manager of your departments, folder and board structure.
144 00:22:00.730 ⇒ 00:22:02.460 Demilade Agboola: Yeah, I agree with that.
145 00:22:03.130 ⇒ 00:22:11.659 felipefaria: Yeah. And I’m guilty of this. I’m actually, I’m gonna review all, all of my looks and make sure that they are within the snop folder, because I bet that a lot of them are not.
146 00:22:12.291 ⇒ 00:22:14.400 felipefaria: But I also bring this up
147 00:22:14.620 ⇒ 00:22:21.079 felipefaria: with Dean. Because I think that it’s just a conversation that needs to be like, you know, discussed on the
148 00:22:21.520 ⇒ 00:22:29.522 felipefaria: on the upper management level. Just just so. Everybody is aligned with that. But on my end we can start like, you know, just
149 00:22:30.140 ⇒ 00:22:32.206 felipefaria: just digging through it and
150 00:22:33.030 ⇒ 00:22:50.709 felipefaria: organizing things within the snlp folder and deleting any looks that are not relevant. I do keep some looks still just until like the new version is ready. And I know that, you know we’ve been working on some of the of the documents, Emily, and there’s a couple
151 00:22:50.900 ⇒ 00:23:00.260 felipefaria: that is still like, haven’t we? Haven’t really gotten to it yet. But and I’ll keep those kind of like separated as well. Kind of like on the
152 00:23:00.430 ⇒ 00:23:02.500 felipefaria: should be worked on sort of
153 00:23:02.970 ⇒ 00:23:07.139 felipefaria: files that they are not as urgent, but they are
154 00:23:07.280 ⇒ 00:23:11.779 felipefaria: kinda good you have, for, like, you know, analysis and and stuff like that. So.
155 00:23:16.480 ⇒ 00:23:19.069 Demilade Agboola: Okay, that’s great. I at least start.
156 00:23:19.190 ⇒ 00:23:28.700 Demilade Agboola: I like that. We’re already like trying to think of how to be proactive about this. And we can definitely help with the data governance, Doc, just something to help
157 00:23:29.100 ⇒ 00:23:32.710 Demilade Agboola: Bates, an awareness of how things should be.
158 00:23:33.110 ⇒ 00:23:39.339 Demilade Agboola: and hopefully, that helps with like the cadence of cleaning up and ensuring that things don’t get out of hand
159 00:23:40.195 ⇒ 00:23:49.959 Demilade Agboola: and also a huge benefit is, even though, like people use different data, things can also be related. So if you’re working revenue and see a lot of revenue data.
160 00:23:50.150 ⇒ 00:23:56.749 Demilade Agboola: it’s possible you could look at the inventory. There’s a randomly because it’s easy to access. I realize that something seems off.
161 00:23:57.000 ⇒ 00:23:59.959 Demilade Agboola: because if there’s a huge spike in revenue
162 00:24:00.360 ⇒ 00:24:13.779 Demilade Agboola: and the inventory doesn’t seem to follow suit. You can kind of figure out something is off somewhere with either one of your data, there’s being able to get to the like better data quality and better data awareness across the company is very important.
163 00:24:14.490 ⇒ 00:24:20.250 Demilade Agboola: Alright? And then finally, oh, man, I think
164 00:24:20.370 ⇒ 00:24:28.569 Demilade Agboola: we’ve been able to build out some of the numbers so far. We’re building out more, pulling them out slowly and queuing them.
165 00:24:28.800 ⇒ 00:24:31.099 Demilade Agboola: We’ve had some sessions with Felipe.
166 00:24:31.220 ⇒ 00:24:33.079 Demilade Agboola: We had one with Perry this week.
167 00:24:34.960 ⇒ 00:24:38.970 Demilade Agboola: However, we also know some of the numbers we’ve built
168 00:24:39.592 ⇒ 00:24:42.759 Demilade Agboola: especially for, like mother’s day, already exist.
169 00:24:43.200 ⇒ 00:24:48.679 Demilade Agboola: And so the question is, are those numbers being utilized? And if not.
170 00:24:49.500 ⇒ 00:24:58.130 Demilade Agboola: is there anything missing with them? Because I know I’ve heard that sometimes dashboards may break, some of those older dashboards may break.
171 00:24:58.270 ⇒ 00:25:04.223 Demilade Agboola: and even though they have broken. No one notices that they’ve broken for a bit.
172 00:25:04.760 ⇒ 00:25:06.539 Demilade Agboola: Obviously, you know.
173 00:25:06.690 ⇒ 00:25:25.430 Demilade Agboola: utility of data. The idea of data is that it’s utilized. And it’s very important that when things go south everyone like notices that things are going south. Obviously, the idea is, you know, if it’s not, if it’s not being noticed. Then something is wrong somewhere like, is there something missing?
174 00:25:25.660 ⇒ 00:25:28.400 Demilade Agboola: Our question is that it’s not answering.
175 00:25:29.280 ⇒ 00:25:32.949 Demilade Agboola: you know. I think that’s more of the general question.
176 00:25:37.220 ⇒ 00:26:00.586 felipefaria: So, and and I’m not entirely sure about like the old dashboards like. I know that we have like mother’s day, like dashboards, that every year we might use the template for the prior year, and just say, Hey, we need to rebuild this and make sure that it’s working. And I think that that’s when we might notice that some things might be off. If there’s specific metrics, because sometimes for mother’s day we we tweak
177 00:26:01.250 ⇒ 00:26:21.689 felipefaria: a few a few things, or we, we add different tables that are specific for mother’s day, right? And we, since we don’t use that on a day to day. We might just notice when we ask, should we build? But in terms of the older data, the only thing is sometimes like, even if I’m using the new tables right? Like
178 00:26:22.050 ⇒ 00:26:43.480 felipefaria: I I and sometimes I will wanna look at. Let’s say, a period of one year in the past or 2 years in the past. So as long as that is good with the new data, and it’s kind of like backtracking and is able to provide information from the past. Then then I’m good, essentially.
179 00:26:48.000 ⇒ 00:26:55.590 Demilade Agboola: Thank you. I’m not sure. If anyone here also uses inventory data. If they do, it’ll be very helpful to know if
180 00:26:56.230 ⇒ 00:27:03.119 Demilade Agboola: or any issues that you’ve been having with that like, what currently exists with the new, like polytonic inventory data.
181 00:27:03.230 ⇒ 00:27:06.110 Demilade Agboola: And if there are any things that have been missing.
182 00:27:07.887 ⇒ 00:27:11.470 jessicacampbell: My team will use it for
183 00:27:11.730 ⇒ 00:27:17.349 jessicacampbell: looking back like one week, or maybe 2, to see.
184 00:27:18.030 ⇒ 00:27:26.639 jessicacampbell: How did the inventory change throughout the week. We have a report that’s like called non-optimal shipments.
185 00:27:26.780 ⇒ 00:27:31.000 jessicacampbell: and we kind of have to explain why all orders
186 00:27:31.270 ⇒ 00:27:39.589 jessicacampbell: why those orders shipped like not ground and inventory is usually a big component of it.
187 00:27:41.270 ⇒ 00:27:57.810 jessicacampbell: and so that’s when we use it. And I know, Emily, you’re probably a little closer to this than I am, but like I know, we didn’t notice our report broke, because I would say, scm is maybe not as in tune to our inventory as snop. So we’re still like trying to fix it.
188 00:27:59.190 ⇒ 00:28:00.170 Emily Giant: I think.
189 00:28:00.680 ⇒ 00:28:17.490 Emily Giant: Demo, the report that broke is the snapshot data. So it’s hard for them to know, like at this point data. It’s data inventory at a specific time when an order was booked. And I know that is on our roadmap to rebuild that.
190 00:28:17.830 ⇒ 00:28:19.489 Emily Giant: But that
191 00:28:19.860 ⇒ 00:28:33.709 Emily Giant: would be not currently working. So that makes sense that that report is broken. Just do you have. Can you send the link in the chat of that report, or you can slack it to me, and I’ll add it to the Brainforge board so that we can take a look at that and rebuild it with the new stuff.
192 00:28:40.510 ⇒ 00:28:47.219 jessicacampbell: Sorry I was on mute. I will get the report. I don’t know if I have the link easily. I just know people on my team need it.
193 00:28:47.830 ⇒ 00:28:48.910 Demilade Agboola: Okay. Sounds. Good.
194 00:28:50.245 ⇒ 00:28:50.940 Demilade Agboola: Yeah.
195 00:28:52.390 ⇒ 00:28:58.750 felipefaria: And then when you say inventory data, are you talking about the inventory? Xf, yeah.
196 00:28:59.196 ⇒ 00:29:05.439 Demilade Agboola: Referring more to like the new models that we’re building out through polytonic
197 00:29:05.981 ⇒ 00:29:08.630 Demilade Agboola: but obviously, if there are things with inventory
198 00:29:08.980 ⇒ 00:29:12.139 Demilade Agboola: us that are being powered by infantry access.
199 00:29:13.150 ⇒ 00:29:16.770 Demilade Agboola: We would also want to replace that with what we’re building. So.
200 00:29:16.770 ⇒ 00:29:23.450 felipefaria: Okay, no. With the inventory data. Yeah. I think I’ve been talking to you, Emily, right? Like, just about the
201 00:29:23.780 ⇒ 00:29:34.539 felipefaria: the issue that we caught in terms of forced upgrades. So well. So that’s 1 thing that I flagged to to Emily, and I believe that she’s working on.
202 00:29:34.680 ⇒ 00:29:38.490 felipefaria: I’m kind of like, a solution there, just because
203 00:29:39.000 ⇒ 00:29:42.429 felipefaria: course upgrades are inflating the sales numbers. But yeah.
204 00:29:42.830 ⇒ 00:29:44.449 Emily Giant: It does look like
205 00:29:44.580 ⇒ 00:29:54.510 Emily Giant: that’s like the last edge case thing. Because, prior, we were getting some inflated numbers due to like a join that had to be fixed
206 00:29:55.696 ⇒ 00:30:01.390 Emily Giant: and whenever not to get too nitty gritty on order
207 00:30:02.032 ⇒ 00:30:15.650 Emily Giant: versus on hand a lot of times, because of like our accounting. It will change lots, and every now and then, like an order, would be assigned to 2 lots, and it would mess up the data that’s not happening anymore. It seems like narrowly
208 00:30:15.920 ⇒ 00:30:28.010 Emily Giant: down to this forced upgrade thing, and Alex is creating a custom field in Netsuite, since there is no like surefire identifier in the data tables right now. So
209 00:30:28.130 ⇒ 00:30:29.590 Emily Giant: the logic is like
210 00:30:29.820 ⇒ 00:30:41.429 Emily Giant: pretty convoluted to PIN down but we’ll definitely have an interim fix by the end of the week, like I’m out tomorrow, but like I’m not gonna not finish it. If it isn’t done, cause that’s
211 00:30:42.072 ⇒ 00:30:49.030 Emily Giant: it’s distorting the numbers quite a bit when it happens, because we’ll have like a full rejection, and then it will show like
212 00:30:49.140 ⇒ 00:31:00.809 Emily Giant: 50 orders that didn’t actually use that product. And it is it’s making the reports a bit unusable for Felipe at the moment, but we figured it out quickly.
213 00:31:01.429 ⇒ 00:31:03.469 Emily Giant: I would say. The snapshot data.
214 00:31:03.940 ⇒ 00:31:10.860 Emily Giant: the forced upgrades. And then I still need to bring in right now, we have inventory
215 00:31:11.050 ⇒ 00:31:15.410 Emily Giant: lot data and inventory like suborder data. And I want to make sure that, like
216 00:31:15.680 ⇒ 00:31:40.830 Emily Giant: everything is in one, and they’re still separate because the inventory adjustment or transaction data doesn’t have start spoil dates, and some of the like aggregate lot information, but it will. They’re they’re all there, and it’s all. It’s not gonna change. When I move it over it was just we we built them out for separate purposes at first, st but then realized like it would be much more convenient.
217 00:31:41.160 ⇒ 00:31:42.580 Emily Giant: As long as we’re
218 00:31:43.417 ⇒ 00:31:54.110 Emily Giant: clear about like what to expect aggregation wise with these. That it would be better to just go to one mart and not have to like. Hop around to different explores when you report building.
219 00:31:54.300 ⇒ 00:32:01.359 Emily Giant: But yeah, I’m trying to think of like, because I know I get a lot of feedback from Felipe and Perry. But, like
220 00:32:01.920 ⇒ 00:32:05.948 Emily Giant: with the old inventory. Xf flow.
221 00:32:07.030 ⇒ 00:32:08.410 Emily Giant: Are we overtime?
222 00:32:10.450 ⇒ 00:32:18.540 Emily Giant: Oh, shoot! Never mind, we can do it next time. But if anyone thinks of like old Inventory except reports that don’t work anymore. But they wish did.
223 00:32:19.160 ⇒ 00:32:24.909 Emily Giant: Please slack them to me, and I’ll make sure to add them to our like rebuild plans.
224 00:32:28.230 ⇒ 00:32:29.190 felipefaria: Sounds good.
225 00:32:29.990 ⇒ 00:32:39.200 Demilade Agboola: That’s good, everyone. Thank you. This has been very helpful talk to you in 2 weeks time.
226 00:32:39.570 ⇒ 00:32:47.060 Demilade Agboola: and hopefully by then you would have more numbers available to you, so that you can utilize them for day to day.
227 00:32:48.280 ⇒ 00:32:51.130 felipefaria: Alright. Thank you. Guys.
228 00:32:51.130 ⇒ 00:32:51.800 Demilade Agboola: Bye.
229 00:32:52.360 ⇒ 00:32:53.460 ianbiles: Thank you so much.