Meeting Title: Element Project Sync Date: 2026-03-26 Meeting participants: Advait Nandakumar Menon, Amber Lin
WEBVTT
1 00:01:37.220 ⇒ 00:01:38.290 Amber Lin: Hello!
2 00:01:39.290 ⇒ 00:01:40.010 Advait Nandakumar Menon: Heh.
3 00:01:40.870 ⇒ 00:01:43.620 Amber Lin: Hey, which one did you have a question on?
4 00:01:44.530 ⇒ 00:01:47.520 Advait Nandakumar Menon: Yeah, I appreciate the flexibility, sorry about this, but.
5 00:01:47.520 ⇒ 00:01:53.260 Amber Lin: No, all good. I, I want to help you, I’m just, like, I’m writing a deadline for another project.
6 00:01:53.260 ⇒ 00:01:53.920 Advait Nandakumar Menon: Yeah, yeah.
7 00:01:53.920 ⇒ 00:01:55.790 Amber Lin: They’re, like, jumping out.
8 00:01:56.620 ⇒ 00:02:06.710 Advait Nandakumar Menon: Yeah, I understand that, so I really appreciate it. So it was moving a little fast, so I just want to make sure I am aligned on what is expected of me, so that.
9 00:02:06.710 ⇒ 00:02:13.129 Amber Lin: I can go ahead. I agree. Like, client’s pretty high pressure, so Greg is also…
10 00:02:14.020 ⇒ 00:02:20.510 Amber Lin: face pressure. So, I… I still think the three things I outlined, in this.
11 00:02:20.510 ⇒ 00:02:20.990 Advait Nandakumar Menon: Huh.
12 00:02:20.990 ⇒ 00:02:25.779 Amber Lin: that I talked to you in is… is true. So, V2 branch, which…
13 00:02:25.920 ⇒ 00:02:33.850 Amber Lin: like, I think, awacious reviewing. So number one is in progress.
14 00:02:34.370 ⇒ 00:02:38.080 Amber Lin: So, I think we’re mainly talking about number 2 and number 3.
15 00:02:38.590 ⇒ 00:02:48.110 Advait Nandakumar Menon: Yes, and just for the V2 brands, I think he just sent a message asking you to verify something, and only to make sure there are no errors. I think he just sent that message, maybe he won’t do…
16 00:02:48.110 ⇒ 00:02:49.330 Amber Lin: Oh, cool.
17 00:02:49.330 ⇒ 00:02:50.130 Advait Nandakumar Menon: Yeah.
18 00:02:51.460 ⇒ 00:02:55.120 Amber Lin: Alright, where is that?
19 00:02:55.650 ⇒ 00:03:02.199 Amber Lin: Oh, okay, I see. Clarify and normally… I mean,
20 00:03:02.900 ⇒ 00:03:09.899 Amber Lin: Did you… can you verify that there’s no issues? What… what can I look at to verify?
21 00:03:10.720 ⇒ 00:03:20.410 Advait Nandakumar Menon: Yeah, I have been looking at it since morning. I’m not sure why the wrong version went into main, but there’s no errors in my V2 run, so…
22 00:03:21.450 ⇒ 00:03:26.610 Advait Nandakumar Menon: check it now as well. I can’t see any errors with the sample query.
23 00:03:26.850 ⇒ 00:03:30.569 Advait Nandakumar Menon: Also, the additional context I did yesterday, it’s not.
24 00:03:30.570 ⇒ 00:03:31.210 Amber Lin: Yeah.
25 00:03:31.210 ⇒ 00:03:32.820 Advait Nandakumar Menon: But, yeah, yeah.
26 00:03:32.820 ⇒ 00:03:39.659 Amber Lin: Yeah, here, let’s just check this right now. This is the most up-to-date version, right? This is the.
27 00:03:39.660 ⇒ 00:03:40.210 Advait Nandakumar Menon: Yes.
28 00:03:40.210 ⇒ 00:03:40.980 Amber Lin: I did.
29 00:03:41.080 ⇒ 00:03:45.529 Amber Lin: What is one thing we can check to make sure that this is the most up-to-date?
30 00:03:46.670 ⇒ 00:03:50.540 Advait Nandakumar Menon: I would say the, if you scroll up.
31 00:03:52.200 ⇒ 00:04:04.040 Advait Nandakumar Menon: So, I’ve added the terminology where near element in AI context, where it says revenue means sales minus dashboard… I mean, sorry, minus discounts, minus refunds.
32 00:04:04.040 ⇒ 00:04:12.500 Advait Nandakumar Menon: So, this is something Greg specifically asked just minutes before his call with Element yesterday, and I added it yesterday, like, before his call, so…
33 00:04:12.500 ⇒ 00:04:12.960 Amber Lin: This is cool.
34 00:04:12.960 ⇒ 00:04:13.490 Advait Nandakumar Menon: of the most…
35 00:04:13.490 ⇒ 00:04:17.170 Amber Lin: I’m… I’m going to go merge.
36 00:04:17.950 ⇒ 00:04:18.750 Amber Lin: Cool.
37 00:04:25.990 ⇒ 00:04:28.769 Amber Lin: Anyways, okay, I’m merging this.
38 00:04:29.220 ⇒ 00:04:30.880 Amber Lin: Sure. Merge.
39 00:04:31.290 ⇒ 00:04:32.320 Amber Lin: Alright.
40 00:04:32.530 ⇒ 00:04:39.439 Amber Lin: Alright, so this should be in Maine. Let’s go check now.
41 00:04:39.960 ⇒ 00:04:44.939 Amber Lin: Can you check on your side as well, in Maine? Yeah. If we can see it?
42 00:04:45.650 ⇒ 00:04:46.320 Advait Nandakumar Menon: Sure.
43 00:04:47.520 ⇒ 00:04:56.590 Amber Lin: If yes, and we can test, like, one or two questions, and then we can… Let Greg know.
44 00:04:58.940 ⇒ 00:05:09.190 Advait Nandakumar Menon: Okay, I just checked, and I can’t see the errors, and I can also see the… what we were just talking about a minute ago, I can see that terminology in main, so…
45 00:05:10.110 ⇒ 00:05:11.140 Advait Nandakumar Menon: Yeah. Yeah.
46 00:05:11.300 ⇒ 00:05:19.000 Amber Lin: Quick question, what’s the difference between the product and store and sales and inventory? Should we delete the product and store?
47 00:05:20.080 ⇒ 00:05:36.930 Advait Nandakumar Menon: I didn’t… so, if you remember, day before yesterday, I started reworking on this V2 branch, moving on from my feature branch last week, because, for some reason, Omni was all getting it wrong, so I rebuilt the whole topic, so I thought I.
48 00:05:36.930 ⇒ 00:05:37.410 Amber Lin: Yeah, yeah.
49 00:05:37.410 ⇒ 00:05:47.870 Advait Nandakumar Menon: with another topic instead of, using the previous one, so… Cool. Yeah, if you feel the product and store is something not required, we can remove it.
50 00:05:47.870 ⇒ 00:06:00.339 Amber Lin: Yeah, I think it has… it has all of your… like, the joins are the same, yours has… is just way more robust, so I’m… I’m gonna delete that one so people don’t…
51 00:06:00.780 ⇒ 00:06:01.330 Amber Lin: Good.
52 00:06:01.330 ⇒ 00:06:01.770 Advait Nandakumar Menon: Okay.
53 00:06:01.770 ⇒ 00:06:02.580 Amber Lin: views.
54 00:06:03.140 ⇒ 00:06:05.899 Amber Lin: How can I delete this?
55 00:06:06.480 ⇒ 00:06:08.530 Advait Nandakumar Menon: So, will you be pushing another request for…
56 00:06:08.530 ⇒ 00:06:11.870 Amber Lin: Oh, I have to create a new branch delete file, okay.
57 00:06:12.220 ⇒ 00:06:16.780 Amber Lin: Well, okay.
58 00:06:17.230 ⇒ 00:06:26.449 Amber Lin: But they will… they will for sure ask, so… Fix. Oh my god.
59 00:06:28.150 ⇒ 00:06:29.290 Amber Lin: Here…
60 00:06:40.000 ⇒ 00:06:42.539 Amber Lin: Cool. Any other questions?
61 00:06:43.300 ⇒ 00:06:47.479 Advait Nandakumar Menon: Yeah, so like I said, we need… I wanted to talk to you mainly about 2 and 3.
62 00:06:47.700 ⇒ 00:06:54.070 Advait Nandakumar Menon: So… Before we get into two, I think three should be done first, right?
63 00:06:55.090 ⇒ 00:07:03.660 Amber Lin: I think they can be done concurrently, but, like, it’s… It’s… it’s fine.
64 00:07:03.990 ⇒ 00:07:04.829 Amber Lin: What do you.
65 00:07:04.830 ⇒ 00:07:05.260 Advait Nandakumar Menon: Okay.
66 00:07:05.260 ⇒ 00:07:09.010 Amber Lin: It’s up to you, because you’re the main one working with Awash.
67 00:07:09.850 ⇒ 00:07:18.170 Advait Nandakumar Menon: Okay, I would say it’s better to do 3 plus because, there is sales velocity and stuff involved within the three metrics, so…
68 00:07:18.170 ⇒ 00:07:18.770 Amber Lin: Hmm.
69 00:07:18.910 ⇒ 00:07:24.989 Advait Nandakumar Menon: Yeah, or it can be done concurrently. I’ll see what, how it goes and work accordingly.
70 00:07:25.130 ⇒ 00:07:33.060 Advait Nandakumar Menon: So for number 3, mainly, it’s… all of the context is there in the linear ticket, right? You have…
71 00:07:34.830 ⇒ 00:07:36.370 Advait Nandakumar Menon: Further?
72 00:07:36.430 ⇒ 00:07:41.169 Amber Lin: Yeah, can you look at the ticket and tell me what’s clear or not clear?
73 00:07:41.650 ⇒ 00:07:43.769 Advait Nandakumar Menon: Yeah, do you want me to share my screen?
74 00:07:44.130 ⇒ 00:07:45.550 Amber Lin: Shirt, yeah.
75 00:07:59.970 ⇒ 00:08:01.369 Advait Nandakumar Menon: You able to see it?
76 00:08:03.260 ⇒ 00:08:04.550 Amber Lin: Yeah, I can see it.
77 00:08:06.020 ⇒ 00:08:06.740 Advait Nandakumar Menon: Okay.
78 00:08:10.900 ⇒ 00:08:20.500 Advait Nandakumar Menon: Yeah, so what exactly is the request? Like, we have to change… should I be changing something within the spreadsheet? I know you’ve changed some of the naming, so I think.
79 00:08:20.500 ⇒ 00:08:21.819 Amber Lin: Are you… yeah.
80 00:08:22.000 ⇒ 00:08:33.020 Amber Lin: I can do everything in the spreadsheets. We need… I think part of this is a way of communicating with him, is we need to change all of… every single metric
81 00:08:33.309 ⇒ 00:08:46.339 Amber Lin: that mentions revenue needs to be sales. I think he can privy… he’ll probably run a cursor query to check that, and I think your main goal is to make sure all the topics
82 00:08:46.950 ⇒ 00:09:02.160 Amber Lin: Anything referenced in there, any field names that’s in there uses sales, which would be helpful if a waste updated a model, and then you updated a topic, because I know some of the fields we just referenced.
83 00:09:02.360 ⇒ 00:09:03.130 Amber Lin: from both.
84 00:09:03.130 ⇒ 00:09:03.770 Advait Nandakumar Menon: Okay.
85 00:09:03.970 ⇒ 00:09:04.530 Amber Lin: Yeah.
86 00:09:04.940 ⇒ 00:09:11.289 Advait Nandakumar Menon: Okay, so by topics, do I mean the one I’m currently working on, or whatever topic is there, right, out there right now?
87 00:09:11.290 ⇒ 00:09:19.829 Amber Lin: Yeah, the one you’re working on. I’m renaming some of the other stuff, so yours is essentially the main one that we’ll go off of.
88 00:09:20.690 ⇒ 00:09:25.130 Advait Nandakumar Menon: Okay, okay. So, what you just pushed to main, basically, right now?
89 00:09:25.130 ⇒ 00:09:25.659 Amber Lin: Yeah, yeah, yeah.
90 00:09:25.660 ⇒ 00:09:34.449 Advait Nandakumar Menon: Okay, that’s clear to me. So, for retail, I can do that since I’ve been working with retail.
91 00:09:34.910 ⇒ 00:09:40.370 Advait Nandakumar Menon: So you want a wish to rename whatever is marked in red in Snowflake, right?
92 00:09:41.820 ⇒ 00:09:43.310 Amber Lin: Yes, yes.
93 00:09:43.940 ⇒ 00:09:52.159 Advait Nandakumar Menon: Okay. For wholesale, I’m a little confused, like, I understand there’s the same requirement, whatever you’re marked in red is what needs to be changed.
94 00:09:52.160 ⇒ 00:10:10.410 Amber Lin: Yeah, this, just throw it at a wage, I think you’ll understand. If he… if you don’t, you can point him to me. It’s… it’s the same as changing it for retail, it’s just whatever’s in the mart, and since we’re not doing any topics for wholesale yet.
95 00:10:10.450 ⇒ 00:10:14.530 Amber Lin: Like, just changing it in the mart is fine, but,
96 00:10:14.920 ⇒ 00:10:21.779 Amber Lin: like, I need to know once it gets pushed, because then all the spreadsheets will break, and then we’ll have to go.
97 00:10:21.780 ⇒ 00:10:27.149 Advait Nandakumar Menon: Okay. You mean the spreadsheet reporting you guys have for Element right now?
98 00:10:27.150 ⇒ 00:10:30.330 Amber Lin: Based on the So it will… it will break.
99 00:10:31.440 ⇒ 00:10:39.180 Advait Nandakumar Menon: Okay, so I will throw this at Avish, but just for my understanding, we are changing whatever is in red over here, just that, right?
100 00:10:39.850 ⇒ 00:10:55.009 Amber Lin: For retail, I’m more sure as everything in red. In wholesale, there might be more that uses the term revenue, so, like, a cursor query will tell us where things are.
101 00:10:55.690 ⇒ 00:11:03.510 Advait Nandakumar Menon: Okay, and you mentioned model names as well with revenue summary. That’s something I couldn’t find for…
102 00:11:04.260 ⇒ 00:11:07.799 Advait Nandakumar Menon: Wholesale. By model name, you mean this, right? This…
103 00:11:07.800 ⇒ 00:11:08.180 Amber Lin: That…
104 00:11:08.790 ⇒ 00:11:19.210 Amber Lin: Yeah, yeah, that’s essentially the dbt mart. You know, you were working with, like, the dbt models under that marts,
105 00:11:19.730 ⇒ 00:11:28.539 Amber Lin: are named with wholesale monthly revenue, or retail monthly revenue, right? Those need to change, because we’re… we’re.
106 00:11:28.540 ⇒ 00:11:29.260 Advait Nandakumar Menon: Oh, God.
107 00:11:29.260 ⇒ 00:11:30.310 Amber Lin: sales.
108 00:11:31.440 ⇒ 00:11:33.170 Advait Nandakumar Menon: Okay. Okay.
109 00:11:33.330 ⇒ 00:11:36.659 Advait Nandakumar Menon: And I did see,
110 00:11:40.310 ⇒ 00:11:45.500 Advait Nandakumar Menon: What about something like this wholesale monthly revenue by SKU? Is that something…
111 00:11:45.610 ⇒ 00:11:48.909 Advait Nandakumar Menon: There needs to be, like, wholesale monthly sales, basically, you know?
112 00:11:49.130 ⇒ 00:11:49.990 Amber Lin: Yeah.
113 00:11:50.220 ⇒ 00:11:54.589 Amber Lin: Yeah, so… so he’ll need to run, like, a cursor query.
114 00:11:55.620 ⇒ 00:12:02.439 Amber Lin: Essentially, everything that we’re calling revenue right now, most likely is just, like, gross sales, so…
115 00:12:02.440 ⇒ 00:12:09.599 Advait Nandakumar Menon: Okay. Okay. Yeah, that’s fine, I can throw this at him, and I’ll try to help as much as I can, but…
116 00:12:10.560 ⇒ 00:12:14.840 Advait Nandakumar Menon: I need something even more, I might point him to, that’s okay with you.
117 00:12:15.320 ⇒ 00:12:25.690 Amber Lin: Yeah. Ping me in the channel, whenever it comes up, I’ll respond. I’m just… I’m just, like, stressing on this other client project right now.
118 00:12:25.690 ⇒ 00:12:39.249 Advait Nandakumar Menon: Okay, okay, yeah, I understand. So my, just before I let you go, so my main thing here is to update the topic in Omni once this is pushed in, Snowflake DBT, right? For retail, mainly?
119 00:12:40.120 ⇒ 00:12:41.680 Amber Lin: Yes.
120 00:12:42.310 ⇒ 00:12:43.710 Advait Nandakumar Menon: Okay. Yes. Okay.
121 00:12:43.710 ⇒ 00:12:58.059 Amber Lin: So, anything… any of the fields, because when we change the fields, topics might break, making sure that’s updated, and whatever description we use in the topic or in the context has changed as well, I think a cursor query will help you.
122 00:12:58.740 ⇒ 00:13:06.050 Advait Nandakumar Menon: Okay, and what about the dashboards and the other topics you have published? Do I just not do anything for those now?
123 00:13:06.810 ⇒ 00:13:13.909 Amber Lin: I think the other… The other topics are…
124 00:13:14.100 ⇒ 00:13:16.960 Amber Lin: Oh, I, I… I see.
125 00:13:17.100 ⇒ 00:13:26.570 Amber Lin: I think the other topics uses sales, is… is my, is what I think. So…
126 00:13:27.160 ⇒ 00:13:27.790 Advait Nandakumar Menon: Okay.
127 00:13:27.790 ⇒ 00:13:36.059 Amber Lin: Yeah, I can… We can check, but if anything gets affected, then we’ll know that something used revenue.
128 00:13:36.990 ⇒ 00:13:44.039 Advait Nandakumar Menon: Okay. Okay, so that is with respect to this ticket, and for number 2 as well, I can just coordinate with him.
129 00:13:44.530 ⇒ 00:13:49.929 Amber Lin: Yeah, yeah, so for… I think for number two, it’s the three metrics. I think.
130 00:13:49.930 ⇒ 00:13:50.360 Advait Nandakumar Menon: Okay.
131 00:13:50.360 ⇒ 00:13:57.609 Amber Lin: Anything that you’ll need to work with Awash on is, how are we going to get these metrics into the topic?
132 00:13:57.720 ⇒ 00:14:02.019 Amber Lin: Because you’re in charge of that topic you created, right? I don’t know.
133 00:14:02.020 ⇒ 00:14:02.810 Advait Nandakumar Menon: Right.
134 00:14:02.810 ⇒ 00:14:15.219 Amber Lin: Awish will do the modeling, but you’ll have to pick, hey, this needs to go into this model, or help me do a join, or… like, ultimately, it needs to make its way into the topic, and…
135 00:14:15.220 ⇒ 00:14:15.870 Advait Nandakumar Menon: Huh.
136 00:14:15.870 ⇒ 00:14:22.249 Amber Lin: Just make sure after he models it, you know where the model is, and you’re able to
137 00:14:22.350 ⇒ 00:14:24.590 Amber Lin: Like, put it into your topic.
138 00:14:25.380 ⇒ 00:14:32.100 Advait Nandakumar Menon: Okay, and by model, do you mean the tables and views, like, underneath each schema here? Is that what you’re…
139 00:14:32.200 ⇒ 00:14:34.229 Advait Nandakumar Menon: Mean by model, because…
140 00:14:34.230 ⇒ 00:14:40.029 Amber Lin: Yeah, yeah, he will be… all the schema here is just a reflection of Prodmar in…
141 00:14:40.030 ⇒ 00:14:41.290 Advait Nandakumar Menon: Yeah, Snowflake.
142 00:14:41.290 ⇒ 00:14:47.080 Amber Lin: Like, so, like, once he changes it there, this should be automatically updated.
143 00:14:47.680 ⇒ 00:14:50.580 Advait Nandakumar Menon: Okay, and I should take it from here and put it in the topic.
144 00:14:51.070 ⇒ 00:15:05.029 Amber Lin: Yeah, yeah, you can also tell him to say, hey, can you put this in this model, just to make sure that it’s actually the model you’re using, because he might end up putting it in the monthly summary, and I don’t think you use the monthly summary in your.
145 00:15:05.030 ⇒ 00:15:05.570 Advait Nandakumar Menon: Nope.
146 00:15:05.570 ⇒ 00:15:06.190 Amber Lin: So, just…
147 00:15:06.190 ⇒ 00:15:07.669 Advait Nandakumar Menon: I, I use the fact…
148 00:15:07.670 ⇒ 00:15:08.520 Amber Lin: used.
149 00:15:09.090 ⇒ 00:15:12.520 Advait Nandakumar Menon: Yeah, I use the facts sales table and…
150 00:15:12.730 ⇒ 00:15:15.270 Advait Nandakumar Menon: the… some of the calendar product, and…
151 00:15:15.270 ⇒ 00:15:16.020 Amber Lin: Yeah.
152 00:15:16.020 ⇒ 00:15:17.530 Advait Nandakumar Menon: Dimension labels…
153 00:15:17.530 ⇒ 00:15:22.529 Amber Lin: Usually, it would… we would put it in the inventory by location.
154 00:15:23.000 ⇒ 00:15:27.510 Amber Lin: Model, because then you have, like, the weakest stock, the…
155 00:15:27.510 ⇒ 00:15:28.030 Advait Nandakumar Menon: Huh.
156 00:15:28.030 ⇒ 00:15:28.920 Amber Lin: golf…
157 00:15:29.240 ⇒ 00:15:43.029 Amber Lin: I don’t know where sell-through would go, like, we… I also don’t know where we excess stock would go. Hmm. Maybe that’s a new model? I don’t know. Like, you’ll have to work with him on that. I don’t know where best to put that.
158 00:15:43.910 ⇒ 00:15:44.640 Advait Nandakumar Menon: Okay
159 00:15:44.880 ⇒ 00:15:50.300 Advait Nandakumar Menon: Okay. If I’m putting it in a whole other model, I should just join it and make sure…
160 00:15:50.460 ⇒ 00:15:54.209 Advait Nandakumar Menon: The… Yeah. Yeah, okay, okay.
161 00:15:54.210 ⇒ 00:15:58.630 Amber Lin: As long as you know how to join it, and you feel comfortable joining it, that should be…
162 00:15:58.630 ⇒ 00:15:59.350 Advait Nandakumar Menon: Huh.
163 00:15:59.350 ⇒ 00:16:00.449 Amber Lin: That should be good.
164 00:16:01.010 ⇒ 00:16:07.849 Advait Nandakumar Menon: Okay, cool. So, yeah, I have a little more clarity now, so, again, sorry for,
165 00:16:07.850 ⇒ 00:16:09.000 Amber Lin: No, okay, okay.
166 00:16:09.000 ⇒ 00:16:11.880 Advait Nandakumar Menon: Spending your time, but yeah, this is helpful.
167 00:16:12.340 ⇒ 00:16:13.470 Amber Lin: Yeah, of course.
168 00:16:13.880 ⇒ 00:16:14.710 Amber Lin: Sounds good.
169 00:16:14.710 ⇒ 00:16:17.119 Advait Nandakumar Menon: Okay, I’ll let it go. Thanks for this.
170 00:16:17.120 ⇒ 00:16:18.340 Amber Lin: Thanks! Bye!
171 00:16:18.340 ⇒ 00:16:18.970 Advait Nandakumar Menon: Bye-bye.