Meeting Title: Element Data Engineering Sync Date: 2026-02-13 Meeting participants: Robert Tseng, Awaish Kumar
WEBVTT
1 00:00:10.920 ⇒ 00:00:11.780 Awaish Kumar: Okay.
2 00:00:12.700 ⇒ 00:00:13.500 Robert Tseng: Anyways…
3 00:00:15.000 ⇒ 00:00:15.610 Awaish Kumar: Yep.
4 00:00:17.420 ⇒ 00:00:34.460 Robert Tseng: Yeah, so two things I want to talk through. One is with… we’ll start with Element first. I’m spending, like, 2 hours in Shivani on Monday. So, I mean, my goal is to get Utam out of, like, the random calls that he does with her, so I kind of just need to be caught up, and…
5 00:00:35.800 ⇒ 00:00:50.830 Robert Tseng: Yeah, I mean, obviously I have cursor, and I can go through the transcripts for some of the details, but I just want to make sure I have all the tools, ready to go, and have a better understanding of, like, where we’re at with… on the data engineering side.
6 00:00:50.930 ⇒ 00:00:55.589 Robert Tseng: She tried to… She called me, like, randomly two days ago, and…
7 00:00:55.630 ⇒ 00:01:13.570 Robert Tseng: was asking me to pull up some orders table that, like, I wasn’t able to show her. So, like, I think just even just making sure that I’m able to do stuff like that and understand, kind of, where you’re at in your progress would help me, in my conversation with her on Monday.
8 00:01:14.420 ⇒ 00:01:15.080 Awaish Kumar: Okay.
9 00:01:15.540 ⇒ 00:01:16.290 Awaish Kumar: Sure.
10 00:01:17.130 ⇒ 00:01:19.649 Awaish Kumar: Should I, show Slow Flake, or…
11 00:01:21.270 ⇒ 00:01:27.429 Robert Tseng: Yeah, you wanna just pull… yeah, you wanna show stuff, like, I’ll have it pulled up on my side, too, I’ll try to follow along.
12 00:01:28.300 ⇒ 00:01:31.290 Awaish Kumar: So, basically, we… for Element right now, we…
13 00:01:31.720 ⇒ 00:01:37.540 Awaish Kumar: mainly on data engineering side, we have polyatomic setup for them, which just ingest data to slow flake.
14 00:01:37.780 ⇒ 00:01:41.420 Awaish Kumar: And then in Snowflake, we have set up the dbt, which runs transformations.
15 00:01:43.240 ⇒ 00:01:48.110 Awaish Kumar: And then we have ingested the Shopify data, if I can… I can show you.
16 00:01:50.690 ⇒ 00:01:51.680 Awaish Kumar: Hopefully good.
17 00:01:54.110 ⇒ 00:01:54.930 Awaish Kumar: Yeah.
18 00:01:57.450 ⇒ 00:02:01.789 Robert Tseng: If I… are we both logging in with the… with UTOM’s credits? Would that be okay?
19 00:02:02.440 ⇒ 00:02:04.099 Awaish Kumar: Yeah, you can just… Okay.
20 00:02:04.100 ⇒ 00:02:06.430 Robert Tseng: Alright, I’ll just be in the Thomas account.
21 00:02:08.340 ⇒ 00:02:15.290 Awaish Kumar: So… This is the… how it looks.
22 00:02:15.580 ⇒ 00:02:16.130 Robert Tseng: Yeah.
23 00:02:16.420 ⇒ 00:02:24.320 Awaish Kumar: in Snowflake. So this share is coming from outside. This is not coming from Polytomic, so this is for immersive data.
24 00:02:24.340 ⇒ 00:02:39.170 Awaish Kumar: Yeah. For retail, and it is coming from how Amazon shares with us. So this is… that’s why it lives outside of our normal raw database. And here, we can see all these 12 tables, which are
25 00:02:39.200 ⇒ 00:02:43.139 Awaish Kumar: Coming from Emerson for Walmart, and 3, like, 3 for Target.
26 00:02:43.530 ⇒ 00:02:49.990 Awaish Kumar: Oh… Yeah, and we have docs explaining all these tables.
27 00:02:50.210 ⇒ 00:02:52.499 Awaish Kumar: In the cursor, like the…
28 00:02:53.130 ⇒ 00:02:55.520 Awaish Kumar: And the, you know, Brain Forger.
29 00:02:55.520 ⇒ 00:03:00.580 Robert Tseng: Are all the latest transcripts, like, automatically going to the, element info?
30 00:03:01.630 ⇒ 00:03:02.710 Awaish Kumar: Hi, Dawn.
31 00:03:03.370 ⇒ 00:03:09.500 Awaish Kumar: I think so, like, I asked for that feature, Utam said he’s on it, I don’t know how far he…
32 00:03:09.500 ⇒ 00:03:10.300 Robert Tseng: Okay.
33 00:03:13.070 ⇒ 00:03:15.640 Awaish Kumar: But, yeah, this is basically…
34 00:03:16.420 ⇒ 00:03:24.399 Awaish Kumar: for immersion, then we have raw, where all the raw things live. So if you can, like, raw, Polytopic, Shopify, where we have all the…
35 00:03:24.520 ⇒ 00:03:27.810 Awaish Kumar: Raw data for orders, order line items.
36 00:03:28.450 ⇒ 00:03:30.819 Awaish Kumar: customers from Shopify.
37 00:03:32.730 ⇒ 00:03:37.190 Awaish Kumar: And, the data for wholesale, it comes from Shopify itself.
38 00:03:37.360 ⇒ 00:03:45.829 Awaish Kumar: So if… Shopify has both the e-commerce orders and wholesale orders. Wholesale orders are tagged with wholesale
39 00:03:46.210 ⇒ 00:03:53.260 Awaish Kumar: kind of a string. So there is, in the orders table, there is a… Field, scroll tags.
40 00:03:53.620 ⇒ 00:03:56.550 Awaish Kumar: So, using that, you can… you feel… you have to…
41 00:03:57.630 ⇒ 00:04:02.880 Awaish Kumar: Figure out the wholesale orders, and… but that is modeled in our…
42 00:04:04.420 ⇒ 00:04:17.530 Awaish Kumar: broad mods. Then if you’re going to broad mods, like, we only have worked on wholesale and regional parts, so that’s why we don’t have all the Shopify data in there yet. So, like, we are not touching e-com data.
43 00:04:18.180 ⇒ 00:04:31.510 Awaish Kumar: In our product mods yet. So we have wholesale customers. This is a mod, just for wholesale. And here we have wholesale DM customer, which compiles data from
44 00:04:31.820 ⇒ 00:04:34.689 Awaish Kumar: Shopify and their CRM.
45 00:04:34.800 ⇒ 00:04:38.620 Awaish Kumar: And their wholesale team CRM is… lives in the Google Sheet.
46 00:04:40.740 ⇒ 00:04:42.439 Awaish Kumar: And we haven’t just dabbled.
47 00:04:42.440 ⇒ 00:04:52.480 Robert Tseng: Hold on. So, I’m running into the same issues where I’m trying to load these tables, and it just doesn’t work. I wonder, like, if some… I’m not able to replicate what you’re doing. I just don’t know why.
48 00:04:53.660 ⇒ 00:04:55.210 Awaish Kumar: Can you share screen?
49 00:04:55.210 ⇒ 00:04:55.780 Robert Tseng: Yeah.
50 00:05:05.880 ⇒ 00:05:10.770 Robert Tseng: Yeah, so I’m trying to open up this table, and I’m not able to…
51 00:05:10.970 ⇒ 00:05:12.280 Awaish Kumar: Alright.
52 00:05:14.270 ⇒ 00:05:23.459 Awaish Kumar: Okay, I think this is just an error from… I did got this error a few times for…
53 00:05:23.740 ⇒ 00:05:25.980 Awaish Kumar: Like, yesterday as well.
54 00:05:26.300 ⇒ 00:05:27.080 Awaish Kumar: Professional.
55 00:05:27.080 ⇒ 00:05:30.930 Robert Tseng: Yeah, this is exactly what happened to me on my father, please, yeah.
56 00:05:31.480 ⇒ 00:05:32.750 Awaish Kumar: This is, you know…
57 00:05:34.380 ⇒ 00:05:41.970 Awaish Kumar: What happens if you click on three dots on the right side of table and do the preview? Is it the same?
58 00:05:43.990 ⇒ 00:05:45.100 Robert Tseng: Yes. Yeah.
59 00:05:50.440 ⇒ 00:06:04.930 Awaish Kumar: Yeah, this is not an error, like… sometimes we get an error which says there is no warehouse selected, which we can do, like, how to do that I can show, but this error is completely from Snowflake.
60 00:06:06.890 ⇒ 00:06:07.590 Robert Tseng: Oops.
61 00:06:14.480 ⇒ 00:06:19.300 Robert Tseng: And I take my own credits instead of using UTOM, so, like, look bad. I don’t know if that would help, but…
62 00:06:19.300 ⇒ 00:06:24.740 Awaish Kumar: I can send you the… In white. See, like, if you can…
63 00:06:27.340 ⇒ 00:06:34.970 Robert Tseng: That’s fine, we don’t have to troubleshoot this entirely now, just, yeah, if you send me the invite, I’ll create my own. I’ll spend some time on the weekend looking through it,
64 00:06:35.800 ⇒ 00:06:37.180 Robert Tseng: And then…
65 00:06:42.420 ⇒ 00:06:43.749 Robert Tseng: It was soy meats.
66 00:06:45.630 ⇒ 00:06:46.160 Awaish Kumar: Duck.
67 00:06:49.690 ⇒ 00:06:50.500 Awaish Kumar: Okay.
68 00:06:50.750 ⇒ 00:06:53.849 Awaish Kumar: So, let’s see, I’ll do that also.
69 00:06:55.600 ⇒ 00:06:59.330 Awaish Kumar: Afterwards, what else?
70 00:07:01.700 ⇒ 00:07:03.080 Awaish Kumar: like…
71 00:07:04.670 ⇒ 00:07:12.849 Awaish Kumar: for Snowflake, I can send you the… the new… create a new user, send you the credits. Apart from that, like, we had a wholesale…
72 00:07:14.540 ⇒ 00:07:20.730 Awaish Kumar: mart and the retail mart, and that both live in the same… Broadmarts.
73 00:07:21.260 ⇒ 00:07:22.510 Awaish Kumar: Snowflake.
74 00:07:22.800 ⇒ 00:07:24.880 Awaish Kumar: So, I think that that’s…
75 00:07:25.050 ⇒ 00:07:34.129 Awaish Kumar: That’s basically it, what we have worked on in terms of modeling. So, she was focusing more on, like, creating weekly views for wholesale.
76 00:07:34.320 ⇒ 00:07:41.320 Awaish Kumar: And then we had DM Customer, which were all the total partners for Wholesale game. For retail, we created similar…
77 00:07:41.520 ⇒ 00:07:42.650 Awaish Kumar: thing, like…
78 00:07:43.070 ⇒ 00:07:56.479 Awaish Kumar: Only one thing to note here is that there are two tables. One says Fact Sales, and then another one says retail fact, Walmart, only sales. So, sales one is basically the POS data.
79 00:07:57.490 ⇒ 00:08:03.590 Awaish Kumar: for retail, which is coming from both Walmart and Target. But Walmart also sends some only…
80 00:08:03.960 ⇒ 00:08:12.679 Awaish Kumar: sales, right, data, which is not POS, but some from… some data from some order management system in their stores.
81 00:08:12.900 ⇒ 00:08:15.910 Awaish Kumar: That lives in a separate table, so…
82 00:08:16.530 ⇒ 00:08:20.359 Awaish Kumar: For total retail revenue, we have to join this together.
83 00:08:20.500 ⇒ 00:08:28.230 Awaish Kumar: Which, I’m working on right now. But apart from that, like, if we just need PWest sales, we can just go in there and get…
84 00:08:30.410 ⇒ 00:08:35.679 Robert Tseng: Okay. When… when… I think, like, a common thing that I’m trying to…
85 00:08:36.880 ⇒ 00:08:51.549 Robert Tseng: that she says… that talks about is she’s always asking about, like, how is what we’re showing her in Snowflake, or whatever model you have, different from what they think that they are. So, like, she’s always trying to compare, like, our data to something else.
86 00:08:51.800 ⇒ 00:09:04.939 Robert Tseng: do you know what those things are? Like, what is she comparing to? And, like, I just feel like she spends a lot of time trying to QA, like, live with us, which, to me, frankly, just feels like a waste of time, because, like, we should just do that on our own and not have to have her
87 00:09:04.940 ⇒ 00:09:13.409 Robert Tseng: breathing down her back on it, but, like, I anticipate that’s, like, what she will… I don’t want her to be able to distract with that.
88 00:09:13.950 ⇒ 00:09:21.280 Awaish Kumar: initially, like, we don’t have… we don’t know, like, I don’t think they have any kind of reporting on this thing in Element.
89 00:09:21.550 ⇒ 00:09:32.450 Awaish Kumar: Right? So, initially, she was more focused on just formatting, formatting, and she wanted to… she was maybe comparing that with her previous work experience. Like, previously, she was working somewhere.
90 00:09:32.660 ⇒ 00:09:42.860 Awaish Kumar: And then she wanted to have the same structure. And then she… when we have everything ready, we send that to wholesale. They also reviewed the data. It kind of looked good.
91 00:09:42.980 ⇒ 00:09:54.160 Awaish Kumar: But the… I don’t know when she sent it to finance, and then it doesn’t match with finance data. Like, that is completely happening randomly. So, like, finance pulls up their own…
92 00:09:54.500 ⇒ 00:09:57.489 Awaish Kumar: Reports from somewhere we never had access to.
93 00:09:57.820 ⇒ 00:10:00.410 Awaish Kumar: So we are doing reconciliation based on
94 00:10:00.670 ⇒ 00:10:03.499 Awaish Kumar: They… what they pulled from their accounting systems.
95 00:10:04.070 ⇒ 00:10:06.469 Robert Tseng: Okay, so you have access to their accounting system?
96 00:10:06.670 ⇒ 00:10:07.940 Awaish Kumar: No, we don’t.
97 00:10:08.470 ⇒ 00:10:11.409 Robert Tseng: Then, yeah, like, if she’s gonna…
98 00:10:11.510 ⇒ 00:10:14.469 Robert Tseng: I wonder if she’s gonna just say the same thing to me, so, like.
99 00:10:14.660 ⇒ 00:10:17.549 Robert Tseng: How are you doing this reconciliations?
100 00:10:18.760 ⇒ 00:10:27.209 Awaish Kumar: I think she sent some sheet or something to Utham, and Utham shared that with Amber, which now is working on reconciliation.
101 00:10:27.980 ⇒ 00:10:28.690 Robert Tseng: Okay.
102 00:10:29.270 ⇒ 00:10:33.639 Robert Tseng: So, that’s one part, is this reconciliation work that’s going on.
103 00:10:36.840 ⇒ 00:10:41.660 Robert Tseng: Yeah, I’m, like, obviously not following it super closely, so…
104 00:10:41.770 ⇒ 00:10:45.919 Robert Tseng: I… I don’t exactly know what is gonna happen here.
105 00:10:46.140 ⇒ 00:10:49.810 Robert Tseng: I just see, like, some screenshots, she’s comparing, like, what she’s doing.
106 00:10:50.130 ⇒ 00:10:54.580 Awaish Kumar: The only thing is that our revenue does not match with finance.
107 00:10:54.740 ⇒ 00:10:55.550 Awaish Kumar: Yeah.
108 00:10:56.000 ⇒ 00:10:58.109 Awaish Kumar: And the wholesale team does not have any options.
109 00:10:58.110 ⇒ 00:11:01.810 Robert Tseng: probably, like, less than 10%, so I don’t really see what the problem is, to be honest.
110 00:11:02.840 ⇒ 00:11:10.110 Awaish Kumar: Yeah. And the person team doesn’t have any issues with what we are reporting, right? They don’t ever complain on this.
111 00:11:10.740 ⇒ 00:11:11.300 Robert Tseng: Yeah.
112 00:11:13.390 ⇒ 00:11:21.779 Robert Tseng: Okay, I mean, I feel like this is the same thing we run into every client. Like, accounting never really has… like, they recognize revenue differently than we do. So…
113 00:11:22.720 ⇒ 00:11:26.910 Robert Tseng: I think maybe I just have to challenge her on that, that it’s just not gonna match.
114 00:11:27.020 ⇒ 00:11:31.670 Robert Tseng: Okay, so that’s one topic I imagine we’ll probably spend time on.
115 00:11:31.830 ⇒ 00:11:37.260 Robert Tseng: Yeah, I mean, like, what else do you think is kind of going on in…
116 00:11:38.440 ⇒ 00:11:41.100 Robert Tseng: And, like, how else can I…
117 00:11:41.930 ⇒ 00:11:42.440 Awaish Kumar: Yeah, I know.
118 00:11:42.440 ⇒ 00:11:54.300 Robert Tseng: Anything else you can share about what you’ve observed? Obviously, I’m kind of coming in more with… with less, context here, so, like, I… I just want to be able to…
119 00:11:54.920 ⇒ 00:12:07.890 Awaish Kumar: So these are two, like, the important thing which she’s focusing right now with retail and wholesale, regarding revenue discussions. Second thing is she’s more… would want to have more ingestion.
120 00:12:08.380 ⇒ 00:12:10.819 Awaish Kumar: coming from Polyatomic, I think we are.
121 00:12:11.110 ⇒ 00:12:22.880 Awaish Kumar: On top of it, but we are actually also blocked by Polytomic, so Polytomic is building some connectors for Amazon and Walmart, which we are going to ingest, then she wants also
122 00:12:22.950 ⇒ 00:12:41.459 Awaish Kumar: Also, just add data, so maybe in the next… next week, we will be planning that, like, we’re bringing in some data from Meta, TikTok, Snapchat, and for that, also, maybe if there are no connectors for Snapchat, maybe Google, we are going to ask that.
123 00:12:41.650 ⇒ 00:12:46.410 Awaish Kumar: So, that’s going on for the injections. So she wants… actually, she… what she wants is…
124 00:12:46.630 ⇒ 00:12:49.600 Awaish Kumar: She wants us to ingest as much as possible.
125 00:12:49.880 ⇒ 00:12:53.150 Awaish Kumar: And in parallel with what we are doing right now.
126 00:12:53.400 ⇒ 00:12:58.410 Awaish Kumar: Like, the ad data, or the Salesforce, or… Whatever is ready.
127 00:12:58.560 ⇒ 00:13:05.699 Awaish Kumar: We are… yeah, and… but I think we are on the plan on that. We are on, like, in terms of Gantt chart, we are on track.
128 00:13:05.850 ⇒ 00:13:08.679 Awaish Kumar: Regarding those injections.
129 00:13:11.020 ⇒ 00:13:13.860 Awaish Kumar: But, yeah, that’s for ingestion, and then,
130 00:13:14.570 ⇒ 00:13:20.939 Awaish Kumar: BI tool, I think we are also starting with BI tool today, I think. We have, only…
131 00:13:21.960 ⇒ 00:13:25.840 Awaish Kumar: team will be giving demo to Element directly, and then,
132 00:13:26.000 ⇒ 00:13:28.590 Awaish Kumar: Maybe we will be starting some trial.
133 00:13:30.520 ⇒ 00:13:33.340 Awaish Kumar: For an instance, and then, yeah, we started the
134 00:13:33.600 ⇒ 00:13:36.520 Awaish Kumar: We’ll be starting for only reporting as well.
135 00:13:40.360 ⇒ 00:13:45.200 Awaish Kumar: So, yeah, it’s, like, next week is going to be pressing, in a sense that, like.
136 00:13:45.340 ⇒ 00:13:52.120 Awaish Kumar: We will start with Injesha, then Omni, and, all the… like…
137 00:13:52.420 ⇒ 00:14:04.599 Awaish Kumar: everything at the same time, and, like, because OMI tool will be there, then she will obviously going to ask, like, okay, I now need to duplicate all this work you’ve done in Sheets, now it should be in the OMI as well.
138 00:14:05.000 ⇒ 00:14:10.450 Awaish Kumar: So, we’ll be spending time to move all these reporting from sheets to… Probably.
139 00:14:13.400 ⇒ 00:14:20.240 Robert Tseng: Okay. I think there’s also kind of this mismatch where, obviously, like, we give progress updates, and that’s kind of…
140 00:14:20.350 ⇒ 00:14:24.579 Robert Tseng: our way of, like, communicating what’s being done. Like, we’re telling her, like.
141 00:14:24.980 ⇒ 00:14:37.490 Robert Tseng: this is the Gantt, we’re at this stage, whatever. To her, like, she’s not really thinking about it that way. She’s thinking about, like, can I use what you give me? And so I need to be able to help her to understand how to use that better.
142 00:14:38.320 ⇒ 00:14:52.440 Awaish Kumar: So, there are two things. Number one, obviously, once Omni’s there, they can play with it. Second thing, Utham said, like, I want to give her some Snowflake AI Analyst. I just sent Utham a Zoom clip, where actually I built a
143 00:14:53.030 ⇒ 00:14:55.250 Awaish Kumar: AI analyst here in…
144 00:14:55.360 ⇒ 00:15:01.450 Awaish Kumar: In this, and you can basically chat. So, this is what Utam wants her, to go.
145 00:15:01.450 ⇒ 00:15:10.499 Robert Tseng: Yeah, I guess more than just this capability, like, let me just pick one specific question, just from what you’ve told me. You have this model where you’ve joined Walmart data with… what did you join it with?
146 00:15:12.310 ⇒ 00:15:14.310 Awaish Kumar: Did you say Walmart and Target?
147 00:15:15.450 ⇒ 00:15:25.269 Awaish Kumar: Yeah, these are two different sources. We have, like… I joined with, like, sales data with the products, for example, table, to come up with…
148 00:15:25.270 ⇒ 00:15:32.870 Robert Tseng: Debbie, you showed me a model earlier where you had joined Walmart and Target Data. I’m just trying to pick an example, right? Is that something… is that what you said?
149 00:15:33.640 ⇒ 00:15:36.350 Awaish Kumar: Yeah. I’m one of the subject fields.
150 00:15:36.460 ⇒ 00:15:38.010 Awaish Kumar: I joined them together.
151 00:15:38.010 ⇒ 00:15:48.909 Robert Tseng: Yeah, I’m trying to put myself in her shoes, right? So I’m like, okay, she sees that you took two different data sources, you put them together in one model. She’s… she’s… in her mind, she’s going to be thinking, like,
152 00:15:49.300 ⇒ 00:15:56.310 Robert Tseng: what, what’s… like, what’s the difference between these sources? And, like, you know, maybe you’re seeing, like.
153 00:15:56.430 ⇒ 00:16:01.269 Robert Tseng: There’s, like, a… X percent difference in
154 00:16:01.670 ⇒ 00:16:08.330 Robert Tseng: In sales, when you… when you look at these two sources together, compared to, like, if you look at the platform separately.
155 00:16:10.180 ⇒ 00:16:17.700 Robert Tseng: like, and then she’ll ask us, well, what, like, what do you… what can we do to, like, reconcile that, right? And,
156 00:16:18.000 ⇒ 00:16:25.000 Robert Tseng: you know, maybe Walmart recognizes revenue at a different… maybe slightly different, Time…
157 00:16:25.810 ⇒ 00:16:37.180 Robert Tseng: in a slightly different way than Target, and that creates some sort of discrepancy, that when you go into each of those platforms, and you look at revenue, it’s going to be different than what we’re showing on the model.
158 00:16:37.190 ⇒ 00:16:45.959 Robert Tseng: I think she wants… I think that’s the type of conversation that she would probably want us to call out.
159 00:16:46.880 ⇒ 00:17:02.329 Awaish Kumar: Yeah, that, like, she wants us to… she wanted us to build something as a base before going to retail. So, once we have something, like, we have revenue, like, we have sales, right? We have… we brought that in. Now, what is the definition for that, for example, net revenue?
160 00:17:02.600 ⇒ 00:17:14.639 Awaish Kumar: either we had revenue minus discounts, or refunds, or what, like, that we need to discuss with Will, for example, from revenue. Like, how do you define this… this net revenue for you?
161 00:17:14.640 ⇒ 00:17:17.380 Robert Tseng: And have we had those conversations yet? Or, like, kind of…
162 00:17:17.380 ⇒ 00:17:18.430 Awaish Kumar: We just met him.
163 00:17:18.430 ⇒ 00:17:19.220 Robert Tseng: active.
164 00:17:19.220 ⇒ 00:17:25.200 Awaish Kumar: We just met once with Will in a discovery call, where we just learned overall about retail, but…
165 00:17:26.359 ⇒ 00:17:37.929 Awaish Kumar: never… we never met with him afterwards, but now… that’s what we did with wholesale also. Like, with wholesale, we just met once with them, and then we built a mart for them, and some…
166 00:17:38.069 ⇒ 00:17:57.549 Awaish Kumar: tables, and with whatever we had, we just showed them, and after that, they basically commented, okay, we are calculating this differently, or I need more… few more fields, I need has refrigerator column, I need that column, right? Then we started to add more and more.
167 00:17:57.709 ⇒ 00:17:58.439 Awaish Kumar: For them.
168 00:17:59.120 ⇒ 00:17:59.700 Robert Tseng: Okay.
169 00:18:02.310 ⇒ 00:18:03.590 Robert Tseng: Yeah, so then…
170 00:18:03.690 ⇒ 00:18:14.010 Robert Tseng: So you’ve gone… you’ve gone back, you’re adding some more things, is there another call scheduled? Well, I’m trying to, like, understand what’s, like, the feedback loop here, like, how are we… like, how do I tell her, like, just…
171 00:18:14.250 ⇒ 00:18:29.699 Robert Tseng: trust this process. Like, we already got the requirements from Will, we’re working it. Like, I don’t need her to, like, come in and tell us, like, how to engineer a thing. Like, I think she’s just… she’s just sticking her hands into too many things, and, like, I want to be able to
172 00:18:29.700 ⇒ 00:18:36.720 Robert Tseng: set better guardrails where she does actually come in and ask us. Obviously, Utah just picks up the phone anytime he calls, which is…
173 00:18:36.720 ⇒ 00:18:39.419 Robert Tseng: I just… I just don’t really think that’s… that’s,
174 00:18:39.530 ⇒ 00:18:51.109 Robert Tseng: it’s not gonna work. She has to create… he has to create some distance from her. Like, that’s what we did with Eden, like, you know, they have to let us do… do… do… do our work. So, that’s where I… that’s where I’m coming from.
175 00:18:51.600 ⇒ 00:18:52.250 Awaish Kumar: Yeah.
176 00:18:53.160 ⇒ 00:18:56.429 Awaish Kumar: Yeah, that’s, like, that’s all…
177 00:18:56.680 ⇒ 00:19:01.200 Awaish Kumar: like, we then worked on that feedback from Wholesale, and then…
178 00:19:01.310 ⇒ 00:19:15.610 Awaish Kumar: After that, like, actually, the thing is that she is in the middle, like, she don’t want us… so far, she don’t want us to go directly with any… anyone. So, like, now, like, whenever she approves that we are going to meet with wholesale.
179 00:19:15.710 ⇒ 00:19:16.670 Robert Tseng: Okay.
180 00:19:17.260 ⇒ 00:19:28.749 Awaish Kumar: Like, and even before, like, and then also, like, right, so she asked… also asked for a few things, we did that, and then now she also said, like, we should pause on…
181 00:19:28.950 ⇒ 00:19:36.880 Awaish Kumar: developing anything for wholesale after that. Like, the new requests will just go to backlog. We don’t work on that.
182 00:19:36.980 ⇒ 00:19:49.440 Awaish Kumar: That was also one… at one time, that was also part of the plan, that, okay, whatever we have built, we gave them something, and now that the new request will just go to backlog, and we are going to…
183 00:19:49.580 ⇒ 00:20:03.290 Awaish Kumar: moved towards, like, retail and ingesting new… ingesting and modeling new, like, the domains of the business. So we moved on to retail, we started ingesting, we started modeling, we started some basic reporting as she wanted.
184 00:20:03.870 ⇒ 00:20:11.890 Awaish Kumar: Then, like, all of a sudden, there are some… New requests from her.
185 00:20:12.390 ⇒ 00:20:14.300 Awaish Kumar: herself, that, okay, I need…
186 00:20:14.990 ⇒ 00:20:19.339 Awaish Kumar: something for wholesale again. So, I don’t… so this is how it’s happening right now.
187 00:20:20.500 ⇒ 00:20:21.130 Robert Tseng: Okay.
188 00:20:21.360 ⇒ 00:20:31.389 Robert Tseng: Alright, let’s wrap this part up. So, yeah, hopefully I get my own access to Snowflake, I’ll be able to look for the tables myself, I need to cut off on what is actually in here.
189 00:20:31.650 ⇒ 00:20:38.250 Robert Tseng: And then I need time to put all the transcripts of everything that he has into the repo, otherwise I’m not going to be able to…
190 00:20:38.760 ⇒ 00:20:48.060 Robert Tseng: she’s gonna expect that, like, I already know all the questions that they’re talking about, and I just don’t, so I just need to be able to… I need a way to be able to reference that.
191 00:20:48.350 ⇒ 00:20:51.040 Robert Tseng: So I think those are… those are the takeaways for me.
192 00:20:54.360 ⇒ 00:21:04.620 Robert Tseng: Okay, if we could spend a few minutes on the Eden stuff. So, I’m going to go back to linear,
193 00:21:08.260 ⇒ 00:21:14.080 Robert Tseng: Yeah, we have this show high level.
194 00:21:17.350 ⇒ 00:21:18.180 Robert Tseng: -Oh.
195 00:21:31.650 ⇒ 00:21:38.900 Robert Tseng: I need to go to Platform… Who’s a known moment?
196 00:22:04.670 ⇒ 00:22:06.979 Robert Tseng: Come on, I think the next shop, okay.
197 00:22:11.210 ⇒ 00:22:24.220 Robert Tseng: Yeah, so February 20th is their last day. They’re gonna get off of this platform, and they need the high-level instability to be, to be integrated. So, that’s really the gist of it, and .
198 00:22:24.300 ⇒ 00:22:27.359 Awaish Kumar: They’re going off of what platform? Like, GHL?
199 00:22:30.180 ⇒ 00:22:32.440 Robert Tseng: No, it’s,
200 00:22:42.460 ⇒ 00:22:46.569 Robert Tseng: this… I’ll just share with you this call, like, this is…
201 00:22:49.910 ⇒ 00:22:53.980 Robert Tseng: Like, any question that you ask me, I’m gonna reference this, because I only had one call with them.
202 00:22:57.410 ⇒ 00:23:07.570 Robert Tseng: They had a previous agency that was managing their GHL and Zenody integration. They have their own platform, they set up integration with them.
203 00:23:07.790 ⇒ 00:23:15.490 Robert Tseng: they’re moving off of it, and they just want to be able to have… they want… they want BrainForge to maintain this moving forward, so…
204 00:23:18.010 ⇒ 00:23:18.740 Awaish Kumar: Okay.
205 00:23:19.660 ⇒ 00:23:24.400 Awaish Kumar: So, like, is there someone I can talk to? Like, like, what they…
206 00:23:24.520 ⇒ 00:23:29.749 Awaish Kumar: what that integration was actually doing, like, there are multiple endpoints in both.
207 00:23:29.750 ⇒ 00:23:38.550 Robert Tseng: Yeah, I think you could watch that… that… watch that video. It will give you the demo. Like I… like I mentioned, it’s literally just, like, a,
208 00:23:39.600 ⇒ 00:23:46.959 Robert Tseng: Yeah, like, I think it’s a 15-minute long video. You’ll be able to see, like, it’s just two CRMs passing data back and forth.
209 00:23:49.720 ⇒ 00:23:51.090 Awaish Kumar: Okay, we are.
210 00:23:54.580 ⇒ 00:24:03.450 Robert Tseng: And if you need to talk to more people, you can ask Alicia, but, like, I kind of feel like we just… we need to get moving on this, because it’s… we have, like, about a week.
211 00:24:03.710 ⇒ 00:24:05.409 Awaish Kumar: Yeah, I… what I just…
212 00:24:05.780 ⇒ 00:24:24.210 Awaish Kumar: I want to, like, narrow down some scope, because there are a lot of endpoints, and if we had to sync all the data, then there will be a lot of endpoints, and we don’t have any direct integration between these tools, so if I would be using, maybe, Segment, or Polyatomic, or maybe…
213 00:24:24.360 ⇒ 00:24:29.720 Awaish Kumar: some Zapier kind of thing, then, like, I have to, like.
214 00:24:30.120 ⇒ 00:24:32.930 Awaish Kumar: Pick individual endpoints and do that syncing.
215 00:24:34.080 ⇒ 00:24:51.229 Robert Tseng: Okay, yeah, well, I mean, I had this call with her 10 days ago, so I was hoping we would have already figured that out by now. You know, 10 days ago, we had, like, maybe 3 weeks to get it done, now we only have 1 week. So, yeah, I guess this just needs to be expedited, like, I don’t… whatever…
216 00:24:51.360 ⇒ 00:24:54.989 Robert Tseng: Like, yeah, I need you to… I need you to make those decisions.
217 00:24:56.480 ⇒ 00:24:57.549 Awaish Kumar: Yeah, so…
218 00:24:58.370 ⇒ 00:25:08.079 Awaish Kumar: Yeah, I get it, what you’re saying. What I understood was more like, okay, if the spike is, like, to understand if there’s a way to…
219 00:25:08.220 ⇒ 00:25:09.170 Awaish Kumar: do that.
220 00:25:10.020 ⇒ 00:25:11.970 Awaish Kumar: But what exactly is Suitel?
221 00:25:12.370 ⇒ 00:25:17.589 Awaish Kumar: I was, like, aware of it, but yeah, I will… I will try to make that happen.
222 00:25:21.420 ⇒ 00:25:22.010 Robert Tseng: Okay.
223 00:25:22.550 ⇒ 00:25:32.930 Robert Tseng: Yeah, well, I mean, if you can look into it, you can ask some questions to them. I mean, ideally, we wouldn’t start this sprint until next week, but, like, yeah, I mean, but, like,
224 00:25:33.090 ⇒ 00:25:41.720 Robert Tseng: yeah, I don’t… I just… it feels like it’s really tight. I just don’t know how you’re gonna be able to do it, and they’re gonna be off this platform in 7 days, so…
225 00:25:42.120 ⇒ 00:25:45.569 Robert Tseng: Yeah, like, I… I… If we need to…
226 00:25:49.210 ⇒ 00:25:54.220 Robert Tseng: I don’t… doesn’t look like you’re doing anything else for Eden, like, this week, so… it feels like…
227 00:25:54.900 ⇒ 00:25:58.989 Awaish Kumar: This week is, like, just today, it’s funny.
228 00:25:59.310 ⇒ 00:26:07.240 Awaish Kumar: I’m… I’m not… Yeah, I’ve been, like, kind of, doing violence for…
229 00:26:07.700 ⇒ 00:26:13.099 Awaish Kumar: did modeling for Eton, I’m reviewing Zoran’s PR, then I am doing modeling for Eden OS as well.
230 00:26:16.170 ⇒ 00:26:24.749 Awaish Kumar: I’m doing that, like, the… All the world, like, the more, like, we… Discuss, like, all the…
231 00:26:24.900 ⇒ 00:26:26.719 Awaish Kumar: The same… similar to what we have right now.
232 00:26:27.070 ⇒ 00:26:30.629 Awaish Kumar: So, I’m… I plan to finish that today.
233 00:26:31.100 ⇒ 00:26:35.310 Robert Tseng: Okay, yeah, well, I mean, if you need to hand it to Dave Miladi or someone else, like,
234 00:26:35.410 ⇒ 00:26:42.810 Robert Tseng: Like, I just feel like if we don’t have an answer by today, or just don’t really think we’re gonna get it done by Friday next week.
235 00:26:44.940 ⇒ 00:26:45.640 Awaish Kumar: Okay.
236 00:26:47.140 ⇒ 00:26:56.280 Robert Tseng: Right, like, I think that… watch the video, the deadline’s very clear, I think the demo is very clear, too, like, I think it has everything we need. So.
237 00:26:57.130 ⇒ 00:26:58.000 Awaish Kumar: Okay.
238 00:26:58.260 ⇒ 00:26:58.800 Robert Tseng: Yeah.
239 00:27:00.780 ⇒ 00:27:02.440 Awaish Kumar: Okay, yeah, I’ll watch that.
240 00:27:02.580 ⇒ 00:27:03.360 Awaish Kumar: Thanks.
241 00:27:04.710 ⇒ 00:27:11.229 Robert Tseng: Okay, so, I mean, I’ll probably mention it when we stand up, so hopefully, like, you’ll have an answer by stand up.
242 00:27:13.020 ⇒ 00:27:13.950 Awaish Kumar: Okay, yep.
243 00:27:14.190 ⇒ 00:27:14.840 Robert Tseng: Yeah.
244 00:27:14.960 ⇒ 00:27:15.720 Robert Tseng: Okay.
245 00:27:17.080 ⇒ 00:27:18.039 Awaish Kumar: Good, thank you.
246 00:27:18.350 ⇒ 00:27:18.840 Robert Tseng: It’s…