Meeting Title: EdenOS Modeling Needs for Omni Date: 2026-03-31 Meeting participants: Ashwini Sharma, Amber Lin, Awaish Kumar
WEBVTT
1 00:00:12.230 ⇒ 00:00:13.110 Amber Lin: Hello!
2 00:00:13.590 ⇒ 00:00:14.429 Ashwini Sharma: I am, bud.
3 00:00:14.980 ⇒ 00:00:17.160 Amber Lin: Hi, do you know if Awish is joining?
4 00:00:17.480 ⇒ 00:00:20.529 Ashwini Sharma: He should be joining, so wait for some time.
5 00:00:21.120 ⇒ 00:00:22.750 Amber Lin: Cool, sounds good.
6 00:00:23.930 ⇒ 00:00:30.759 Amber Lin: Alright, can you walk me through what new models got created?
7 00:00:32.090 ⇒ 00:00:40.320 Ashwini Sharma: Okay, so there will be some changes to the models that were created, because the earlier model tried to replicate what was there in the
8 00:00:40.490 ⇒ 00:00:56.039 Ashwini Sharma: the previous boss-related models. There will be some changes right now, considering, the discussion that I had with Avish. It’s mainly on the product, sales summary by transaction, that’s the one model, and the other model would be,
9 00:00:56.580 ⇒ 00:00:58.190 Ashwini Sharma: Order sales summary.
10 00:00:59.180 ⇒ 00:01:02.059 Ashwini Sharma: So we’re trying to replicate these two models right now.
11 00:01:02.220 ⇒ 00:01:08.329 Ashwini Sharma: And, I think, we also wanted to focus this discussion on
12 00:01:08.600 ⇒ 00:01:22.080 Ashwini Sharma: You know, understanding the dashboard, what exactly is needed, and then dive down into the actual model and create a model that can answer the questions that the client is looking for.
13 00:01:24.140 ⇒ 00:01:24.810 Amber Lin: Cool.
14 00:01:26.590 ⇒ 00:01:27.499 Ashwini Sharma: I wish I did.
15 00:01:28.330 ⇒ 00:01:29.200 Amber Lin: Hey, Rich.
16 00:01:29.900 ⇒ 00:01:31.229 Amber Lin: Hi,
17 00:01:31.430 ⇒ 00:01:46.419 Amber Lin: Okay, I went through the top 10 dashboards, and I… I looked through this query, so I know what it needs, but how would I give you the right engineering requirements? Because I…
18 00:01:47.740 ⇒ 00:01:49.570 Amber Lin: Like, I…
19 00:01:49.570 ⇒ 00:01:50.100 Awaish Kumar: Thank you.
20 00:01:51.430 ⇒ 00:01:54.859 Awaish Kumar: Actually, like, I think that’s where we…
21 00:01:55.140 ⇒ 00:01:58.620 Awaish Kumar: take it on, like, for this V1 iteration.
22 00:01:59.230 ⇒ 00:02:06.939 Awaish Kumar: instead of going through a full loop of, like, Amber figuring out each and every Table, column name…
23 00:02:07.170 ⇒ 00:02:08.240 Awaish Kumar: Metro game.
24 00:02:08.570 ⇒ 00:02:14.910 Awaish Kumar: We should just, like… Go from dashboard, what table it’s using, and…
25 00:02:15.510 ⇒ 00:02:22.049 Awaish Kumar: Yeah, you can ask clarification questions, but then that’s how we should be… Thinking about it.
26 00:02:23.880 ⇒ 00:02:29.480 Ashwini Sharma: Yeah, so maybe, Amber, if you can share the… some of the dashboards that,
27 00:02:30.150 ⇒ 00:02:34.400 Ashwini Sharma: That are related to orders, or metrics related to orders.
28 00:02:34.510 ⇒ 00:02:37.890 Ashwini Sharma: And probably we can, you know.
29 00:02:37.890 ⇒ 00:02:43.300 Awaish Kumar: Let me… let… let’s start with, like, Amber, the… for Josh’s report is… Is it…
30 00:02:44.010 ⇒ 00:02:45.569 Awaish Kumar: Really important one, right?
31 00:02:46.050 ⇒ 00:02:46.620 Awaish Kumar: We’re gonna.
32 00:02:46.620 ⇒ 00:02:47.440 Amber Lin: Yeah.
33 00:02:47.440 ⇒ 00:02:50.800 Awaish Kumar: That only requires fact transaction, plus due product.
34 00:02:51.430 ⇒ 00:03:02.820 Amber Lin: Yeah, let me, let me pull up the ones. Before, Josh Report is not, very used, but I understand it’s important.
35 00:03:02.930 ⇒ 00:03:08.229 Amber Lin: The most used one we have is Product ROS and LTV.
36 00:03:08.590 ⇒ 00:03:15.350 Amber Lin: It has, like, 300-something views, but let me pull up the Fort Josh report, and we can start there.
37 00:03:16.320 ⇒ 00:03:21.010 Awaish Kumar: for product ROS and LTV, we have… we need product sales summary by transaction table, right?
38 00:03:21.110 ⇒ 00:03:24.069 Awaish Kumar: And, Ashwini, you are already working on that, right?
39 00:03:24.450 ⇒ 00:03:26.939 Ashwini Sharma: Yeah, yeah, yeah, I’m working on the product, this thing.
40 00:03:27.590 ⇒ 00:03:31.590 Ashwini Sharma: The one that we discussed earlier, right? Product sales summary by transaction.
41 00:03:35.610 ⇒ 00:03:39.720 Amber Lin: Cool, let me pull it up.
42 00:03:44.610 ⇒ 00:03:46.320 Amber Lin: Hmm… okay.
43 00:03:48.040 ⇒ 00:03:54.890 Amber Lin: What other things are we planning to build, and what exactly is different from this and the BASC tables?
44 00:03:56.010 ⇒ 00:03:57.210 Awaish Kumar: So, yeah, what?
45 00:03:57.630 ⇒ 00:03:58.510 Awaish Kumar: What?
46 00:03:59.900 ⇒ 00:04:04.390 Awaish Kumar: So, at the end, the end users want the same dashboards.
47 00:04:06.420 ⇒ 00:04:10.140 Awaish Kumar: like, product raws on LTV, which gives you…
48 00:04:10.540 ⇒ 00:04:16.169 Awaish Kumar: spend by product, revenue, NCAC, and things like that. At the end, a marketing
49 00:04:16.329 ⇒ 00:04:20.920 Awaish Kumar: chief only needs to know those metrics. Yeah. Now it is…
50 00:04:21.380 ⇒ 00:04:24.989 Awaish Kumar: Now it depend… depends on you if you want to…
51 00:04:25.160 ⇒ 00:04:38.819 Awaish Kumar: I mean, if you think there could be a different model, or one or two tables that you need, you can ask the requirement to build that, or you can ask, like, whatever is being used right now, which is products and somebody by transaction.
52 00:04:40.080 ⇒ 00:04:56.120 Awaish Kumar: We have two ways. One is just try to copy whatever there is, and try to come up with similar structure. If there is something missing, we should just let them know that this feature is missing, or this field we couldn’t get from the existing system. But then.
53 00:04:56.540 ⇒ 00:05:00.359 Awaish Kumar: That’s one way to go for it. Second way is that if you think there is
54 00:05:00.760 ⇒ 00:05:04.799 Awaish Kumar: A better way to handle something, maybe you can do it directly from
55 00:05:05.500 ⇒ 00:05:09.519 Awaish Kumar: dim and fact table, and you don’t need a summary table, and things like that.
56 00:05:12.090 ⇒ 00:05:16.839 Amber Lin: Okay. Well, that sounds like it’s gonna be a bit of effort.
57 00:05:17.170 ⇒ 00:05:23.529 Amber Lin: Like, I… I don’t know how much I can deliver if I’m gonna have to go through each dashboard.
58 00:05:24.050 ⇒ 00:05:26.709 Amber Lin: And figure out what to… what to add.
59 00:05:27.110 ⇒ 00:05:31.159 Awaish Kumar: To speed that up, that’s what I did. I told Ashwani also.
60 00:05:31.430 ⇒ 00:05:51.220 Awaish Kumar: speed up that process to actually start delivering work, and then we can revisit if something is not working as expected. So, for product sales summary… for product ROS and LTV dashboard, we know that product sales summary by transaction is the table for that.
61 00:05:51.320 ⇒ 00:05:53.209 Awaish Kumar: And I can deliver you that table.
62 00:05:53.730 ⇒ 00:05:58.190 Awaish Kumar: And then… You have to create the topic, and then dashboard.
63 00:06:00.820 ⇒ 00:06:02.889 Amber Lin: Cool, yeah. The…
64 00:06:03.060 ⇒ 00:06:09.770 Amber Lin: The first topic I would need to create is gonna be the revenue summary one, so… give…
65 00:06:09.770 ⇒ 00:06:10.290 Awaish Kumar: Sure.
66 00:06:10.290 ⇒ 00:06:10.970 Amber Lin: It’s here.
67 00:06:10.970 ⇒ 00:06:22.720 Awaish Kumar: And that is one. Second one is also about, for, like, that one is Ashwin is working right now, but, and he, like, and he will be done, maybe today, and…
68 00:06:22.720 ⇒ 00:06:23.160 Amber Lin: Okay.
69 00:06:24.810 ⇒ 00:06:28.869 Awaish Kumar: The second thing is, about Josh, right?
70 00:06:29.130 ⇒ 00:06:33.570 Awaish Kumar: So, for example, fact… fact orders is already there.
71 00:06:33.780 ⇒ 00:06:37.599 Awaish Kumar: And then, in fact, auto item is already there, and then…
72 00:06:38.350 ⇒ 00:06:42.569 Awaish Kumar: Yeah, yeah, this table only needs, I don’t care.
73 00:06:42.570 ⇒ 00:06:46.040 Amber Lin: fact transactions? I don’t think we have fact transactions.
74 00:06:46.770 ⇒ 00:06:48.280 Awaish Kumar: We don’t… so…
75 00:06:48.280 ⇒ 00:06:58.100 Ashwini Sharma: Let’s look at the… can we look at the dashboard and then see what exactly is there in the original dashboard? And then maybe we can come to Omni and see what’s missing, or…
76 00:06:58.900 ⇒ 00:07:00.570 Ashwini Sharma: You know, if we have more questions.
77 00:07:00.570 ⇒ 00:07:06.339 Amber Lin: I can’t find the Fort Josh one, I think it’s a snapshot of the…
78 00:07:06.480 ⇒ 00:07:09.709 Amber Lin: It’s a query that we have. It might be on…
79 00:07:10.220 ⇒ 00:07:13.810 Ashwini Sharma: I mean, it should be on Tableau, right? Not in this one?
80 00:07:14.110 ⇒ 00:07:17.189 Awaish Kumar: It’s here as well. Can I go to the hub?
81 00:07:18.120 ⇒ 00:07:18.690 Amber Lin: Yeah…
82 00:07:18.690 ⇒ 00:07:25.260 Awaish Kumar: If you can go to… Exact… Executive, or maybe…
83 00:07:25.560 ⇒ 00:07:29.620 Amber Lin: Yeah, do you think it’s a query inside of these?
84 00:07:29.820 ⇒ 00:07:32.000 Awaish Kumar: What is that, Executive Financial Overview?
85 00:07:34.630 ⇒ 00:07:37.140 Amber Lin: This is not the one for him.
86 00:07:37.580 ⇒ 00:07:38.270 Awaish Kumar: Okay.
87 00:07:38.520 ⇒ 00:07:39.930 Amber Lin: What’s in here.
88 00:07:40.980 ⇒ 00:07:42.120 Awaish Kumar: Oh, like the…
89 00:07:43.810 ⇒ 00:07:45.270 Amber Lin: Yeah, I don’t know.
90 00:07:46.120 ⇒ 00:07:46.919 Awaish Kumar: You’ll be fine.
91 00:07:51.930 ⇒ 00:07:55.900 Awaish Kumar: It should be… There, where we are going to chat.
92 00:08:15.660 ⇒ 00:08:21.750 Awaish Kumar: So, let’s see… This is the… This is what we are… We haven’t.
93 00:08:22.400 ⇒ 00:08:25.730 Awaish Kumar: We have revenue for a product.
94 00:08:25.880 ⇒ 00:08:27.189 Awaish Kumar: And a product group.
95 00:08:27.510 ⇒ 00:08:32.480 Awaish Kumar: And then we have a way to identify new and recurring orders.
96 00:08:32.750 ⇒ 00:08:42.160 Awaish Kumar: Right? And… new… New customers, and order status, and things like that.
97 00:08:43.130 ⇒ 00:08:50.940 Awaish Kumar: So, order status will give us, like, if it’s a pending, abandoned, Or if you… Whatever the state is.
98 00:08:53.040 ⇒ 00:08:55.790 Awaish Kumar: That is current status, and then…
99 00:08:56.300 ⇒ 00:09:01.510 Awaish Kumar: We have all the… obviously, the fact transaction has all the orders, all the revenue.
100 00:09:02.110 ⇒ 00:09:06.249 Awaish Kumar: and the new order revenue, and the new customers. So I think that…
101 00:09:06.250 ⇒ 00:09:11.409 Ashwini Sharma: This was… Avish, wasn’t this the product sales summary by transaction report?
102 00:09:11.410 ⇒ 00:09:12.580 Awaish Kumar: No, this is not.
103 00:09:14.670 ⇒ 00:09:18.190 Awaish Kumar: It’s kind of similar, but it’s not… not exactly…
104 00:09:18.980 ⇒ 00:09:25.250 Awaish Kumar: built out of that. So this is… it does not have a spend information. It is purely just the revenue information.
105 00:09:26.000 ⇒ 00:09:28.289 Awaish Kumar: There’s no spend data here.
106 00:09:29.020 ⇒ 00:09:33.890 Amber Lin: Yeah, I thought this was just a transaction… facts transactions table.
107 00:09:34.020 ⇒ 00:09:34.990 Awaish Kumar: Transaction.
108 00:09:35.270 ⇒ 00:09:35.710 Amber Lin: Yeah.
109 00:09:35.710 ⇒ 00:09:49.399 Awaish Kumar: the fact transaction is joining to DIM Products just to get this product name, because they want to see the revenue byproduct, that’s all. Like, we effect orders, right? You can use that
110 00:09:49.500 ⇒ 00:09:52.649 Awaish Kumar: But only, Ashwini, what we need to do is kind of
111 00:09:52.780 ⇒ 00:09:57.899 Awaish Kumar: we have to figure out a way to join. Either we have to include
112 00:09:59.710 ⇒ 00:10:06.760 Awaish Kumar: Like, from fact orders, we have a fact order item, and then in that, we might have to come up with the…
113 00:10:08.950 ⇒ 00:10:11.359 Awaish Kumar: Revenue for each product line.
114 00:10:11.580 ⇒ 00:10:12.380 Awaish Kumar: Right?
115 00:10:12.600 ⇒ 00:10:17.149 Awaish Kumar: So we may be… in order item, we might have some…
116 00:10:17.450 ⇒ 00:10:20.969 Awaish Kumar: product ID, which joins to DIM product, and then…
117 00:10:21.150 ⇒ 00:10:23.569 Awaish Kumar: The revenue, client revenue, right?
118 00:10:23.790 ⇒ 00:10:28.240 Awaish Kumar: And basically, you can then, Amber, use that to create.
119 00:10:28.240 ⇒ 00:10:36.869 Amber Lin: Cool. Can you send… can you send me this link in… In… in Slack.
120 00:10:37.230 ⇒ 00:10:39.619 Awaish Kumar: It’s… yeah, it’s just an…
121 00:10:41.250 ⇒ 00:10:42.650 Awaish Kumar: I can send you the links.
122 00:10:42.650 ⇒ 00:10:43.660 Amber Lin: Yeah, cool.
123 00:10:44.040 ⇒ 00:10:48.280 Ashwini Sharma: Yeah, this is just an image, can you forward it here? Okay, it’s not just an image.
124 00:10:50.790 ⇒ 00:10:52.370 Ashwini Sharma: That’s the actual dashboard, right?
125 00:10:53.090 ⇒ 00:10:56.079 Awaish Kumar: Yeah, it’s a report coming from a dashboard.
126 00:11:03.270 ⇒ 00:11:06.530 Awaish Kumar: Okay, basically… That was it.
127 00:11:07.220 ⇒ 00:11:08.060 Amber Lin: Hold on.
128 00:11:09.860 ⇒ 00:11:15.519 Awaish Kumar: So, for… what we need for that is, we need, Fact order item table.
129 00:11:15.640 ⇒ 00:11:21.369 Awaish Kumar: Which can give us the… which is already there, but it might be missing product name.
130 00:11:21.550 ⇒ 00:11:23.069 Awaish Kumar: So we just have an opinion.
131 00:11:23.570 ⇒ 00:11:28.720 Awaish Kumar: Way to join… get the product name, a way to get the…
132 00:11:31.260 ⇒ 00:11:35.910 Awaish Kumar: In, like, the order for individual item, if possible, or an order
133 00:11:38.780 ⇒ 00:11:43.619 Awaish Kumar: Yeah, and that’s all. And that’s… that’s… that you can use to basically create.
134 00:11:44.920 ⇒ 00:11:45.600 Amber Lin: Yeah.
135 00:11:46.430 ⇒ 00:11:55.350 Amber Lin: Sounds good. Question on the 30-day, 60-day, year-to-date. Are those modeled, or are those calculated?
136 00:11:55.350 ⇒ 00:11:56.930 Awaish Kumar: be calculated in the Omni.
137 00:11:57.070 ⇒ 00:12:05.330 Amber Lin: Okay, cool. So, I think what I need is… mostly the product.
138 00:12:05.620 ⇒ 00:12:06.930 Amber Lin: And…
139 00:12:08.020 ⇒ 00:12:16.539 Amber Lin: How would I know if it’s a new versus old customer? Are we… did we backfill everything? Can I just rely on that?
140 00:12:17.700 ⇒ 00:12:24.089 Awaish Kumar: Yeah, so there is one thing. Right now, we only have access to staging data. We don’t really have the live…
141 00:12:24.090 ⇒ 00:12:24.430 Amber Lin: Okay.
142 00:12:24.430 ⇒ 00:12:25.860 Awaish Kumar: they don’t just in Basque.
143 00:12:25.990 ⇒ 00:12:29.770 Awaish Kumar: So I’m not sure how we are going to…
144 00:12:29.910 ⇒ 00:12:32.820 Awaish Kumar: handle that. Right now, we don’t have any info.
145 00:12:33.040 ⇒ 00:12:36.890 Awaish Kumar: I did ask… try to ask… Their engineering team about it.
146 00:12:36.890 ⇒ 00:12:37.360 Amber Lin: I’m not.
147 00:12:37.650 ⇒ 00:12:42.650 Awaish Kumar: That’s what I need to… Maybe they will ingest everything to AidenOS?
148 00:12:43.790 ⇒ 00:12:46.419 Awaish Kumar: All the data for all the customers, so we don’t have.
149 00:12:46.420 ⇒ 00:12:47.680 Amber Lin: Let’s see…
150 00:12:47.680 ⇒ 00:12:48.250 Awaish Kumar: Things?
151 00:12:48.910 ⇒ 00:12:59.979 Amber Lin: I’m also looking at that there’s no, like, new is first order field, so how am I going to know if this is a new customer?
152 00:13:01.270 ⇒ 00:13:05.809 Awaish Kumar: Yeah, that’s, like, for example, we can build these fields that…
153 00:13:06.040 ⇒ 00:13:11.839 Awaish Kumar: in this model is first customer or his first order, but the thing is,
154 00:13:12.030 ⇒ 00:13:18.400 Awaish Kumar: What I’m trying to say is, right now, even if we make… we make these fields,
155 00:13:18.600 ⇒ 00:13:25.930 Awaish Kumar: It is only depend… dependent on the… on the data in the invoice. So, if a customer ordered
156 00:13:26.180 ⇒ 00:13:29.599 Awaish Kumar: In the Basque. And then he came in Eden West.
157 00:13:29.820 ⇒ 00:13:32.220 Awaish Kumar: and ordered here. Then there will be…
158 00:13:32.400 ⇒ 00:13:34.259 Awaish Kumar: No way to find out.
159 00:13:34.540 ⇒ 00:13:35.560 Awaish Kumar: Oh, okay.
160 00:13:36.270 ⇒ 00:13:38.360 Awaish Kumar: If we have two separate models.
161 00:13:38.360 ⇒ 00:13:39.580 Amber Lin: I see.
162 00:13:40.130 ⇒ 00:13:56.320 Awaish Kumar: And before unifying those two models, I won’t… I’m just trying to get answers from their team that if they move all the data from Bask to Eden OS, then we don’t have to unify between two platforms. We will have everything
163 00:13:57.460 ⇒ 00:14:00.059 Awaish Kumar: Enido noise, and we just… Oh, okay.
164 00:14:00.280 ⇒ 00:14:11.980 Amber Lin: So, for now, am I going to use BAS tables for new revenue? How… how are we going to go about this? Are we just going to wait for the Eden OS team?
165 00:14:12.950 ⇒ 00:14:17.169 Awaish Kumar: We are thinking about this system as its own.
166 00:14:18.190 ⇒ 00:14:22.799 Awaish Kumar: Right? So we don’t… we don’t have… we are not comparing it with PASC.
167 00:14:23.000 ⇒ 00:14:24.930 Awaish Kumar: So, what we are going to do is…
168 00:14:25.160 ⇒ 00:14:27.479 Awaish Kumar: Whatever is in there is our data.
169 00:14:27.660 ⇒ 00:14:28.489 Awaish Kumar: So if it doesn’t.
170 00:14:28.490 ⇒ 00:14:34.329 Amber Lin: So, Josh will have… we won’t have new customers for… for the Josh Report.
171 00:14:34.890 ⇒ 00:14:40.040 Awaish Kumar: So, we are not going to change his existing report. We are going to create a similar report.
172 00:14:40.410 ⇒ 00:14:45.689 Amber Lin: I know, that’s what I’m saying. So, like, the new report won’t be able to have new customers.
173 00:14:45.690 ⇒ 00:14:48.740 Awaish Kumar: Yeah, we will add this field, that’s what I’m trying to say, but…
174 00:14:49.140 ⇒ 00:14:59.340 Awaish Kumar: like, from the look, it will be the same, that you will find the similar column, you can add it in Omni, but in terms of meaning of that data.
175 00:14:59.500 ⇒ 00:15:05.850 Awaish Kumar: is a bit… off right now, because a lot of customers are in Basque, so…
176 00:15:05.850 ⇒ 00:15:09.249 Amber Lin: Cool, sounds good. Let’s make a…
177 00:15:09.350 ⇒ 00:15:13.739 Amber Lin: Ticket for this? Do you already… do you guys already have a ticket for that one?
178 00:15:15.070 ⇒ 00:15:19.530 Amber Lin: Where is the Eden OS team? Cool.
179 00:15:19.890 ⇒ 00:15:20.910 Amber Lin: Let’s…
180 00:15:21.220 ⇒ 00:15:29.399 Amber Lin: Cool, okay. I’m gonna create a ticket, and then I’ll assign the modeling to Srini, and then, once done, just assign it to me.
181 00:15:33.360 ⇒ 00:15:34.020 Awaish Kumar: So I…
182 00:15:34.020 ⇒ 00:15:36.749 Amber Lin: So, we said we want a new custom field?
183 00:15:37.670 ⇒ 00:15:42.160 Awaish Kumar: Yeah, new cus… like, we should have everything that supports this dashboard.
184 00:15:42.160 ⇒ 00:15:45.090 Amber Lin: New order.
185 00:15:45.090 ⇒ 00:15:47.470 Awaish Kumar: The habit I’ll have is first order.
186 00:15:49.250 ⇒ 00:15:52.870 Amber Lin: Oh, let me… let me share a screen so you guys can see.
187 00:15:53.170 ⇒ 00:15:55.660 Amber Lin: Case coverage order…
188 00:15:55.930 ⇒ 00:15:56.480 Awaish Kumar: God.
189 00:15:56.480 ⇒ 00:15:58.469 Amber Lin: And there’s products.
190 00:15:58.800 ⇒ 00:15:59.720 Awaish Kumar: That’s a new word.
191 00:15:59.720 ⇒ 00:16:05.380 Amber Lin: product ID, or what are we… what are you using as a key? Are we using variant ID?
192 00:16:05.750 ⇒ 00:16:06.420 Amber Lin: And then…
193 00:16:07.230 ⇒ 00:16:09.069 Awaish Kumar: You need a product ID name.
194 00:16:11.400 ⇒ 00:16:13.599 Amber Lin: Is it product ID or variant ID?
195 00:16:14.710 ⇒ 00:16:15.310 Awaish Kumar: It’s a…
196 00:16:16.540 ⇒ 00:16:19.560 Amber Lin: I don’t think we have product ID.
197 00:16:20.420 ⇒ 00:16:24.060 Awaish Kumar: That product ID is basically an artificial product ID, which I…
198 00:16:24.540 ⇒ 00:16:26.949 Awaish Kumar: created. It’s called Artificial Product ID.
199 00:16:27.160 ⇒ 00:16:29.880 Awaish Kumar: That joins Correct Transaction and DIM Products.
200 00:16:30.220 ⇒ 00:16:32.689 Awaish Kumar: But you’re, like, you don’t really…
201 00:16:32.820 ⇒ 00:16:39.690 Awaish Kumar: We just have to find out… we have to create dim products and join with fact order, or fact order item, and that’s.
202 00:16:39.690 ⇒ 00:16:40.470 Amber Lin: Yeah.
203 00:16:41.040 ⇒ 00:16:45.490 Awaish Kumar: And we will let you know what… what I… what colleagues you’ll be joining.
204 00:16:50.110 ⇒ 00:16:56.789 Amber Lin: Cool. So, I think with that… Order count, customer count…
205 00:16:57.340 ⇒ 00:16:59.849 Awaish Kumar: Yeah, obviously… That’s the CK.
206 00:17:00.590 ⇒ 00:17:05.789 Amber Lin: Okay, now let’s go. Revenue… Okay, I need an order status.
207 00:17:06.319 ⇒ 00:17:06.859 Awaish Kumar: Dear.
208 00:17:07.089 ⇒ 00:17:07.929 Amber Lin: Okay.
209 00:17:18.369 ⇒ 00:17:19.689 Amber Lin: Okay.
210 00:17:20.739 ⇒ 00:17:23.819 Amber Lin: That’s good, that’s this first one.
211 00:17:24.789 ⇒ 00:17:32.239 Amber Lin: I’m gonna say this is to… to do… Urgent today.
212 00:17:33.009 ⇒ 00:17:34.549 Amber Lin: Cool, okay.
213 00:17:35.059 ⇒ 00:17:40.719 Amber Lin: Next one, since we still have some time, let’s go through a few, few ones.
214 00:17:40.909 ⇒ 00:17:46.269 Amber Lin: I think the next one… well, I had a list of usage here.
215 00:17:46.529 ⇒ 00:17:50.759 Amber Lin: So, we can either… yeah, this was the… for Josh report.
216 00:17:50.949 ⇒ 00:17:51.989 Amber Lin: This one.
217 00:17:53.759 ⇒ 00:17:59.969 Amber Lin: This is… like, we can do this, or we can do the financial overview.
218 00:17:59.970 ⇒ 00:18:05.740 Awaish Kumar: We are already a product of us and LTV. We are already creating a product on the table for that.
219 00:18:05.740 ⇒ 00:18:11.919 Amber Lin: Okay, awesome, so let’s, let’s, products for us and LTV.
220 00:18:13.330 ⇒ 00:18:24.809 Amber Lin: Alright, the new tables we’re creating… Does it have all these… So it has product group…
221 00:18:25.370 ⇒ 00:18:27.849 Amber Lin: Ad spends from the old stuff, right?
222 00:18:28.260 ⇒ 00:18:30.529 Amber Lin: I’ll use the old attachment.
223 00:18:32.250 ⇒ 00:18:36.790 Awaish Kumar: Yeah, you can create a table for it. I think Aishwani knows what to do here.
224 00:18:38.320 ⇒ 00:18:46.610 Amber Lin: Okay, what model are you creating? Like, what are you changing? Because I know the current order summary table doesn’t have spend.
225 00:18:46.980 ⇒ 00:18:52.099 Awaish Kumar: This is not depend on order summary, it depends on product sales summary by transaction table.
226 00:18:52.100 ⇒ 00:18:53.700 Amber Lin: Okay, okay.
227 00:18:56.290 ⇒ 00:18:58.999 Amber Lin: And what are we rebuilding there?
228 00:19:00.780 ⇒ 00:19:03.769 Awaish Kumar: Yeah, we have a similar table, right?
229 00:19:04.060 ⇒ 00:19:07.320 Awaish Kumar: Maybe call it Eden West Product Sales Summary, or something like that.
230 00:19:07.320 ⇒ 00:19:07.940 Amber Lin: Huh.
231 00:19:09.490 ⇒ 00:19:10.330 Amber Lin: Okay.
232 00:19:12.270 ⇒ 00:19:16.749 Amber Lin: Not TVs, and… Do we have LTV?
233 00:19:18.880 ⇒ 00:19:22.009 Awaish Kumar: Yeah, LTV is just, like, total revenue, right?
234 00:19:23.140 ⇒ 00:19:24.180 Amber Lin: Yeah.
235 00:19:24.440 ⇒ 00:19:25.500 Amber Lin: Okay.
236 00:19:26.950 ⇒ 00:19:30.030 Amber Lin: Total revenue by customer, by product, though.
237 00:19:30.600 ⇒ 00:19:31.250 Amber Lin: So…
238 00:19:31.250 ⇒ 00:19:34.299 Awaish Kumar: Yeah, you have a product, and you have the revenue, you can…
239 00:19:34.590 ⇒ 00:19:37.470 Awaish Kumar: calculate these metrics on the… in the… in the Omni.
240 00:19:37.800 ⇒ 00:19:38.650 Amber Lin: Okay.
241 00:19:38.760 ⇒ 00:19:47.619 Amber Lin: And then… NCAP… Okay, great. I can, I can… so is this ready to go? I can start here.
242 00:19:48.730 ⇒ 00:19:52.739 Awaish Kumar: I don’t know if, actually, I’ll find… You’re on.
243 00:19:55.860 ⇒ 00:19:56.810 Awaish Kumar: Hi, Shuny.
244 00:19:59.650 ⇒ 00:20:04.439 Ashwini Sharma: Sorry, I was speaking on mute. No, it’s not yet ready. I’ll get it ready and then send a message to Amber.
245 00:20:04.940 ⇒ 00:20:09.119 Amber Lin: Cool, so that would be the… oh, sorry, which…
246 00:20:09.770 ⇒ 00:20:10.820 Ashwini Sharma: Rose, yeah.
247 00:20:11.340 ⇒ 00:20:15.579 Amber Lin: Row ass. Okay. Wait, what’s the… what’s the…
248 00:20:17.010 ⇒ 00:20:19.490 Amber Lin: Model name that you’re working on?
249 00:20:20.490 ⇒ 00:20:22.080 Amber Lin: Product sales summary.
250 00:20:22.080 ⇒ 00:20:24.240 Ashwini Sharma: Yeah, product sales summary by transaction.
251 00:20:24.470 ⇒ 00:20:29.330 Amber Lin: Okay, is this a… Is this a ticket anywhere?
252 00:20:30.210 ⇒ 00:20:36.070 Ashwini Sharma: We can create a new one, I think. Okay.
253 00:20:36.070 ⇒ 00:20:36.810 Amber Lin: That’s great.
254 00:20:36.810 ⇒ 00:20:37.320 Ashwini Sharma: Yeah.
255 00:20:37.940 ⇒ 00:20:43.679 Awaish Kumar: Yeah, actually, we need to call it something with Aiden OS, so we don’t break the existing…
256 00:20:45.590 ⇒ 00:20:49.530 Ashwini Sharma: Also, I’m going to change the name, Amber.
257 00:20:49.750 ⇒ 00:20:51.389 Ashwini Sharma: For this one, right.
258 00:20:53.150 ⇒ 00:20:56.320 Amber Lin: Okay, feel free to change whatever you want to.
259 00:20:56.630 ⇒ 00:21:01.320 Amber Lin: Cool.
260 00:21:01.630 ⇒ 00:21:03.150 Amber Lin: Yeah, let me know.
261 00:21:09.610 ⇒ 00:21:14.779 Amber Lin: Oh, are we… Doing these, what are these for?
262 00:21:15.230 ⇒ 00:21:22.470 Awaish Kumar: Yeah, these are also… like, for one of the dashboards, and I think,
263 00:21:22.630 ⇒ 00:21:25.380 Awaish Kumar: Ashwini has already started on it as well, but…
264 00:21:26.640 ⇒ 00:21:30.930 Amber Lin: Is it the lifecycle stuff, or, like, retention by product?
265 00:21:31.330 ⇒ 00:21:33.269 Awaish Kumar: It is for retention, like that.
266 00:21:39.700 ⇒ 00:21:42.080 Amber Lin: Cool. So…
267 00:21:47.830 ⇒ 00:21:49.040 Amber Lin: Marketing?
268 00:21:50.750 ⇒ 00:21:52.439 Amber Lin: It is the right one.
269 00:21:53.290 ⇒ 00:21:54.070 Amber Lin: Crazy.
270 00:21:54.920 ⇒ 00:21:55.650 Amber Lin: Nope.
271 00:21:59.700 ⇒ 00:22:06.489 Amber Lin: Okay, once… I think once we have the new cut as first order field, we can do this.
272 00:22:07.370 ⇒ 00:22:10.850 Amber Lin: Okay.
273 00:22:13.210 ⇒ 00:22:14.050 Amber Lin: This one.
274 00:22:17.820 ⇒ 00:22:18.580 Amber Lin: Yeah.
275 00:22:19.060 ⇒ 00:22:23.369 Amber Lin: order count, order revenue is the thing I’ll need.
276 00:22:23.750 ⇒ 00:22:29.599 Amber Lin: Probably also in fact orders, rather than fact order items, don’t know.
277 00:22:29.920 ⇒ 00:22:32.910 Amber Lin: And then…
278 00:22:36.340 ⇒ 00:22:39.309 Amber Lin: Is this what you’re working on, the reorder rate?
279 00:22:42.100 ⇒ 00:22:46.010 Awaish Kumar: Yeah, it is… Something… yeah, like…
280 00:22:49.060 ⇒ 00:22:51.480 Awaish Kumar: It should be something, like, to support this.
281 00:22:54.770 ⇒ 00:22:55.790 Amber Lin: Okay.
282 00:22:56.040 ⇒ 00:23:00.899 Amber Lin: So, what is… Do we know the exact specs we’re working on?
283 00:23:03.710 ⇒ 00:23:04.410 Awaish Kumar: Alright?
284 00:23:04.550 ⇒ 00:23:08.209 Amber Lin: Like, what are we… what exactly are we working on?
285 00:23:09.730 ⇒ 00:23:13.449 Awaish Kumar: So, yeah, we need to create this dashboard, and to do that.
286 00:23:13.640 ⇒ 00:23:18.900 Awaish Kumar: I don’t remember everything what we did before, so… We have this model.
287 00:23:19.040 ⇒ 00:23:26.450 Awaish Kumar: Which can help you come up with something similar, so we have cohort.
288 00:23:26.560 ⇒ 00:23:32.690 Awaish Kumar: Then it can be the cohort size, like, new users in that, like, month, for example.
289 00:23:33.220 ⇒ 00:23:38.510 Awaish Kumar: 24 is our cohort, then the size is this one. That means these are new customers.
290 00:23:38.670 ⇒ 00:23:43.730 Awaish Kumar: Then, what is the customer? So, total revenue divided by the code size?
291 00:23:43.870 ⇒ 00:23:46.319 Awaish Kumar: Right? And the first order product is…
292 00:23:46.680 ⇒ 00:23:49.070 Awaish Kumar: Is what, like, in that month?
293 00:23:49.380 ⇒ 00:23:50.929 Awaish Kumar: For all the new orders.
294 00:23:51.120 ⇒ 00:23:54.620 Awaish Kumar: What was the… The first order that was purchased.
295 00:23:54.790 ⇒ 00:23:55.859 Awaish Kumar: By any customer.
296 00:23:57.070 ⇒ 00:24:01.909 Amber Lin: Great, so is this, this is this one?
297 00:24:03.680 ⇒ 00:24:04.560 Awaish Kumar: I think so.
298 00:24:04.960 ⇒ 00:24:09.969 Amber Lin: Okay, so let’s say this one, we need cohort…
299 00:24:14.350 ⇒ 00:24:15.160 Amber Lin: Oh.
300 00:24:15.330 ⇒ 00:24:18.609 Amber Lin: Oversize fresh products.
301 00:24:19.570 ⇒ 00:24:22.400 Awaish Kumar: Yeah, we need all the things that are in the model, right?
302 00:24:22.760 ⇒ 00:24:26.659 Awaish Kumar: You can look at the model and copy-paste the fields.
303 00:24:27.910 ⇒ 00:24:28.500 Amber Lin: Boom.
304 00:24:28.890 ⇒ 00:24:32.559 Awaish Kumar: Because from here, like, you will miss something, and then we…
305 00:24:32.710 ⇒ 00:24:35.080 Awaish Kumar: I have to re-run it. Recreate it.
306 00:24:35.760 ⇒ 00:24:36.260 Amber Lin: Okay.
307 00:24:36.260 ⇒ 00:24:38.230 Ashwini Sharma: Yeah, meh, right.
308 00:24:38.440 ⇒ 00:24:43.490 Ashwini Sharma: You know, I think, Amber, if you can add what exactly is needed?
309 00:24:43.660 ⇒ 00:24:49.329 Ashwini Sharma: For the report, like, for example, if you go back to the ticket in linear, I think all it says is.
310 00:24:49.690 ⇒ 00:24:51.999 Ashwini Sharma: create this thing from Eden OS, right?
311 00:24:52.110 ⇒ 00:24:58.800 Ashwini Sharma: And this is highly misleading, because sometimes it may not not be possible.
312 00:25:00.120 ⇒ 00:25:00.790 Ashwini Sharma: So…
313 00:25:00.790 ⇒ 00:25:03.760 Amber Lin: Yeah, I didn’t create this ticket, so I don’t know.
314 00:25:03.760 ⇒ 00:25:04.210 Ashwini Sharma: Yeah.
315 00:25:04.210 ⇒ 00:25:04.730 Amber Lin: Where it came.
316 00:25:04.730 ⇒ 00:25:14.680 Ashwini Sharma: That’s okay. What I need is, like, what do we need out of this model, right? That is… that will help me decide what to put into the model and how to put it.
317 00:25:14.680 ⇒ 00:25:18.459 Amber Lin: Let’s see, so we’re not trying to recreate the BASC models.
318 00:25:20.150 ⇒ 00:25:26.250 Awaish Kumar: Yeah, but my question is, again, what she’s looking at is the dashboard generated out of that model, actually.
319 00:25:26.450 ⇒ 00:25:37.080 Awaish Kumar: And she’s going to look at that dashboard and only fill out everything that is in that model. That’s what I’m trying to say. These are not new requirements coming from the client, or…
320 00:25:37.110 ⇒ 00:25:47.169 Awaish Kumar: or we are not looking for a new chart. If I look at that dashboard, and if I start copy-pasting each field, you end up with all the fields that are in that model.
321 00:25:48.910 ⇒ 00:25:57.189 Amber Lin: Yeah, if we can replicate the model, that would be great, and then just tell me what we cannot replicate, and then we’ll have to work around that.
322 00:25:58.990 ⇒ 00:26:05.689 Awaish Kumar: because she don’t know what is in Eden OS. We know that, like, we have been modeling this, and we know
323 00:26:05.960 ⇒ 00:26:19.630 Awaish Kumar: Like, it has to come from us, in that sense. That, if I am working on products with somebody, as I know, membership land field is not there. It will be part of my PR description that
324 00:26:20.160 ⇒ 00:26:25.189 Awaish Kumar: this table does not have these fields, we can’t bring that in. And then Ember will…
325 00:26:25.540 ⇒ 00:26:29.359 Awaish Kumar: Come up, like, create the dashboard without those fields.
326 00:26:32.470 ⇒ 00:26:39.710 Awaish Kumar: the other way around that you are suggesting is for new requirements, if… if Amber comes with a new chart, or…
327 00:26:39.990 ⇒ 00:26:45.359 Awaish Kumar: Or, or comes up with… A dashboard, which is not here.
328 00:26:45.740 ⇒ 00:26:52.870 Awaish Kumar: That makes sense, but if she only… she’s also looking at the same dashboard that I looked at, and… and then…
329 00:26:53.120 ⇒ 00:26:56.719 Awaish Kumar: come up with the same models that I… then we don’t have to re…
330 00:26:57.050 ⇒ 00:27:00.090 Awaish Kumar: Don’t have to loop over those things again and again.
331 00:27:02.790 ⇒ 00:27:05.870 Amber Lin: Yeah, here, I can show you…
332 00:27:06.050 ⇒ 00:27:15.270 Amber Lin: For example, this dat… this dashboard, this one that we’re looking at right now, here is… all the…
333 00:27:15.520 ⇒ 00:27:17.570 Amber Lin: These are all the queries.
334 00:27:17.720 ⇒ 00:27:18.940 Amber Lin: they use.
335 00:27:19.130 ⇒ 00:27:24.320 Amber Lin: This is what topics, they used, and what the base tables are.
336 00:27:24.430 ⇒ 00:27:27.659 Amber Lin: So, down here, I have a summary of
337 00:27:27.880 ⇒ 00:27:32.570 Amber Lin: all the base, like, tables it uses, so…
338 00:27:33.210 ⇒ 00:27:38.120 Amber Lin: This uses rev… cohort Revenue Retention Summary.
339 00:27:38.310 ⇒ 00:27:41.070 Amber Lin: This is cohort subsequent order summary.
340 00:27:41.670 ⇒ 00:27:44.099 Amber Lin: Product sales summary by transaction.
341 00:27:44.410 ⇒ 00:27:48.360 Amber Lin: revenue retention, I think that’s the same thing.
342 00:27:48.850 ⇒ 00:27:55.380 Amber Lin: And then return on ad spend. So, I think 1, 2, 3, 4. Do we have these?
343 00:27:56.940 ⇒ 00:28:05.749 Awaish Kumar: So, yeah, I… I… we can split this between me and Ashuni. He’s already working on product sales summary by transaction. I can take on, maybe…
344 00:28:06.030 ⇒ 00:28:09.309 Awaish Kumar: But some of the revenue retention summary, for example.
345 00:28:09.630 ⇒ 00:28:10.480 Amber Lin: Okay.
346 00:28:10.850 ⇒ 00:28:12.180 Amber Lin: Okay, okay, so…
347 00:28:12.180 ⇒ 00:28:13.640 Awaish Kumar: That’s good.
348 00:28:13.640 ⇒ 00:28:18.859 Amber Lin: So, I can… But let’s…
349 00:28:22.830 ⇒ 00:28:27.550 Amber Lin: Between these, what is more important? Should we do this one first?
350 00:28:28.520 ⇒ 00:28:31.040 Amber Lin: Financial overview.
351 00:28:32.890 ⇒ 00:28:36.290 Amber Lin: Oh, well, they also use cohort stuff.
352 00:28:37.030 ⇒ 00:28:48.129 Amber Lin: Cool, okay, I’m gonna create a ticket, I’m gonna put down the models here needed as sub-tickets, sub-issues, and then let’s go from there.
353 00:28:48.850 ⇒ 00:28:55.400 Amber Lin: let’s first do the For Josh report. So, I know, Ashini, you’re doing the… .
354 00:28:55.720 ⇒ 00:28:57.870 Awaish Kumar: This one.
355 00:28:58.010 ⇒ 00:29:05.249 Awaish Kumar: So that will, support, the product ROS and TV dashboard.
356 00:29:05.990 ⇒ 00:29:06.720 Amber Lin: Huh.
357 00:29:07.280 ⇒ 00:29:10.959 Awaish Kumar: This one… The next in line, yeah, after that.
358 00:29:10.960 ⇒ 00:29:11.650 Amber Lin: Okay.
359 00:29:17.320 ⇒ 00:29:21.649 Amber Lin: Also… this one is the first one?
360 00:29:22.160 ⇒ 00:29:24.260 Awaish Kumar: Yeah, he’s working on this thing right now.
361 00:29:24.260 ⇒ 00:29:28.280 Amber Lin: Okay, okay, so I’m gonna say… urgent…
362 00:29:34.680 ⇒ 00:29:37.749 Amber Lin: And then these two, I would say, go after that, right?
363 00:29:39.030 ⇒ 00:29:44.300 Amber Lin: Let’s… let’s put this… Okay.
364 00:29:44.450 ⇒ 00:29:58.990 Amber Lin: Let me know how those goes. I’m gonna create tickets, I’ll send it to you guys to triage. I’m gonna work through the top 10, dashboards to tell you what is needed, and,
365 00:29:59.720 ⇒ 00:30:01.180 Amber Lin: I think we’ll go from there.
366 00:30:01.810 ⇒ 00:30:02.460 Awaish Kumar: Okay.
367 00:30:02.840 ⇒ 00:30:03.340 Amber Lin: Yeah.
368 00:30:04.020 ⇒ 00:30:09.899 Amber Lin: Sounds good. Yeah, let me know when things are done so I can start, creating a test.
369 00:30:09.900 ⇒ 00:30:14.940 Awaish Kumar: from If you would like, we can do kind of a working session together on it.
370 00:30:15.140 ⇒ 00:30:22.080 Amber Lin: Yeah, yeah, yeah. I have an interview… I mean, I’m free for the next 30, and I have an interview
371 00:30:22.590 ⇒ 00:30:26.110 Amber Lin: And then I should be… This is Nick?
372 00:30:29.540 ⇒ 00:30:34.279 Amber Lin: Yeah, when… maybe… will the models be ready in, like, an hour or something?
373 00:30:34.770 ⇒ 00:30:37.560 Awaish Kumar: No, no, I mean, I and Ashwini can pair, but I…
374 00:30:37.560 ⇒ 00:30:40.710 Amber Lin: Oh, oh, sorry, sorry, sorry, I thought you meant me.
375 00:30:40.860 ⇒ 00:30:41.470 Amber Lin: You need…
376 00:30:41.470 ⇒ 00:30:42.340 Awaish Kumar: This woman…
377 00:30:43.770 ⇒ 00:30:46.189 Amber Lin: No, I don’t need it. You can have it.
378 00:30:47.140 ⇒ 00:30:48.480 Amber Lin: Alrighty. Thanks, guys.
379 00:30:49.120 ⇒ 00:30:50.180 Ashwini Sharma: Yeah, thanks, Elba.
380 00:30:54.010 ⇒ 00:30:54.900 Awaish Kumar: Okay.
381 00:30:56.340 ⇒ 00:30:57.620 Ashwini Sharma: Let me share my screen, yeah.
382 00:30:59.990 ⇒ 00:31:04.820 Awaish Kumar: Okay, okay, let’s… Let’s…
383 00:31:05.260 ⇒ 00:31:19.589 Awaish Kumar: like, you know, Aishwani, when I worked on this, the most important tables are the base tables. If once… once we have those 3-4 tables in a good form, everything else can use… we can just use AI to generate everything.
384 00:31:21.410 ⇒ 00:31:27.609 Ashwini Sharma: Right, so you’ve already created, right, those base tables, like the dimensions and facts for orders and…
385 00:31:28.100 ⇒ 00:31:31.769 Awaish Kumar: thing, I, like, when I worked on this.
386 00:31:31.980 ⇒ 00:31:43.359 Awaish Kumar: we… everything was not there, right? So they started… they added new fields and things, that’s why they are sending me this information that I was sharing with you on the fly.
387 00:31:43.480 ⇒ 00:31:53.030 Awaish Kumar: So, I started modeling this, like, 2 weeks ago, I think, maybe more than that, and didn’t have all the things. But now they have started adding flu.
388 00:31:53.140 ⇒ 00:31:59.639 Awaish Kumar: more things in there. Like, the discount is coming in, it’s not there in the system, for example.
389 00:32:00.480 ⇒ 00:32:01.370 Awaish Kumar: Okay.
390 00:32:02.070 ⇒ 00:32:09.609 Awaish Kumar: So, and that is… that is still not in the system itself. Today, in the engineering call, they mentioned that
391 00:32:10.020 ⇒ 00:32:14.090 Awaish Kumar: Now they have it, so we are maybe going to receive an update on that.
392 00:32:14.580 ⇒ 00:32:19.299 Awaish Kumar: But my point is, if we go to the fact order.
393 00:32:20.560 ⇒ 00:32:23.250 Ashwini Sharma: Okay, let me go to fact order.
394 00:32:24.120 ⇒ 00:32:26.880 Awaish Kumar: What I’m trying to do is,
395 00:32:27.430 ⇒ 00:32:32.040 Awaish Kumar: I’m… why I’m keep showing you a few previous things is because
396 00:32:32.590 ⇒ 00:32:35.950 Awaish Kumar: It just makes… like, we made some compromises.
397 00:32:36.080 ⇒ 00:32:39.270 Awaish Kumar: In our previous modeling, because we were…
398 00:32:39.630 ⇒ 00:32:44.620 Awaish Kumar: restricted by the system, so Basque gives you only the order.
399 00:32:45.110 ⇒ 00:32:47.159 Awaish Kumar: It does not give you order item.
400 00:32:47.860 ⇒ 00:32:48.350 Awaish Kumar: So…
401 00:32:48.350 ⇒ 00:32:49.010 Ashwini Sharma: Okay.
402 00:32:49.200 ⇒ 00:33:03.909 Awaish Kumar: So, like, if an order is on Bask, is placed, and if there are multiple products sold, we don’t know in the Basque system that if two different products were sold, what. In new system, we might have that information.
403 00:33:04.290 ⇒ 00:33:10.519 Awaish Kumar: So, previously, every… everything that was sold can maybe just… revenue just tied to one product.
404 00:33:10.740 ⇒ 00:33:12.919 Awaish Kumar: But now we have order item.
405 00:33:13.850 ⇒ 00:33:16.020 Awaish Kumar: Fat, it is all item as well.
406 00:33:16.180 ⇒ 00:33:23.290 Awaish Kumar: That means, we can, for each individual item, we can maybe find the product.
407 00:33:23.830 ⇒ 00:33:27.709 Awaish Kumar: And I’m not sure, because you worked on that order total thing.
408 00:33:27.920 ⇒ 00:33:30.040 Awaish Kumar: So, I just want to know if…
409 00:33:30.230 ⇒ 00:33:32.550 Awaish Kumar: If it was possible for you to…
410 00:33:32.730 ⇒ 00:33:37.079 Awaish Kumar: Bring the line revenue for this auto item, or not?
411 00:33:38.570 ⇒ 00:33:44.419 Ashwini Sharma: Yeah, there should be pos… so this is, order IDs here, right? Pharmacy item ID, this is the product ID, right? We’re talking about.
412 00:33:46.840 ⇒ 00:33:47.749 Awaish Kumar: So, we have this…
413 00:33:47.750 ⇒ 00:33:48.290 Ashwini Sharma: See, a little…
414 00:33:48.290 ⇒ 00:33:54.840 Awaish Kumar: Okay, not pharmacy, but we have this, in the order item, we have treatment dose ID, and then I…
415 00:33:55.170 ⇒ 00:33:58.189 Awaish Kumar: Showed you how it goes… how it joins with the.
416 00:33:58.190 ⇒ 00:33:58.910 Ashwini Sharma: Right.
417 00:33:58.910 ⇒ 00:34:01.570 Awaish Kumar: voice, right? Yesterday’s end.
418 00:34:01.570 ⇒ 00:34:05.819 Ashwini Sharma: dose. Treatment dose. Okay, treatment dose is here.
419 00:34:06.380 ⇒ 00:34:10.070 Ashwini Sharma: Treatment dose… Alright, shipment does…
420 00:34:10.070 ⇒ 00:34:18.019 Awaish Kumar: I sent you a message about how it is joining. Oh yeah, treatment doors… Brands with invoice ID.
421 00:34:18.380 ⇒ 00:34:20.370 Ashwini Sharma: No, this is not the one. Which one is it?
422 00:34:20.909 ⇒ 00:34:23.040 Awaish Kumar: It’s a, it’s a simple text message.
423 00:34:23.230 ⇒ 00:34:23.840 Awaish Kumar: This one.
424 00:34:23.840 ⇒ 00:34:24.370 Ashwini Sharma: What is?
425 00:34:24.770 ⇒ 00:34:26.319 Ashwini Sharma: It was the image, yeah.
426 00:34:26.320 ⇒ 00:34:28.250 Awaish Kumar: There’s… there’s another one after that.
427 00:34:30.409 ⇒ 00:34:36.479 Awaish Kumar: Below that, there is a message which says Treatment Doors, and you can join Treatment Doors to invoice ID.
428 00:34:36.719 ⇒ 00:34:40.250 Awaish Kumar: Scroll down, it is there. Invoice ID, you can search for it.
429 00:34:42.489 ⇒ 00:34:43.379 Ashwini Sharma: This one?
430 00:34:43.679 ⇒ 00:34:45.009 Awaish Kumar: Yeah, the other one.
431 00:34:45.379 ⇒ 00:34:46.569 Awaish Kumar: The second one.
432 00:34:46.579 ⇒ 00:34:47.759 Ashwini Sharma: Yeah, this one.
433 00:34:48.599 ⇒ 00:34:53.299 Awaish Kumar: You see, from order or item, you can go to treatment dose, and you can go to invoice ID.
434 00:34:53.300 ⇒ 00:34:54.740 Ashwini Sharma: Invoice ID, okay.
435 00:34:55.550 ⇒ 00:34:56.290 Awaish Kumar: Okay.
436 00:34:56.929 ⇒ 00:34:58.259 Ashwini Sharma: The order, order item.
437 00:34:58.630 ⇒ 00:35:02.170 Ashwini Sharma: Treatment dose, treatment dose 2, invoice, invoice ID, okay.
438 00:35:02.490 ⇒ 00:35:03.970 Awaish Kumar: Yeah, and we can go to invites.
439 00:35:03.970 ⇒ 00:35:07.359 Ashwini Sharma: Invoice… invoice here?
440 00:35:07.830 ⇒ 00:35:10.239 Awaish Kumar: And then we can bring in price from here.
441 00:35:10.540 ⇒ 00:35:11.270 Awaish Kumar: unfair.
442 00:35:12.610 ⇒ 00:35:13.200 Awaish Kumar: Yeah.
443 00:35:13.200 ⇒ 00:35:14.590 Ashwini Sharma: Amount refunded.
444 00:35:15.720 ⇒ 00:35:19.470 Ashwini Sharma: This is what, invoice one ID, right? Invoice ID is here, okay.
445 00:35:19.780 ⇒ 00:35:20.370 Awaish Kumar: Oh, yeah.
446 00:35:21.490 ⇒ 00:35:23.950 Ashwini Sharma: Is that the correct sequence to go?
447 00:35:24.570 ⇒ 00:35:30.130 Awaish Kumar: Yes, that’s what I get from Eden West team. That’s what they’re sending me.
448 00:35:30.380 ⇒ 00:35:35.960 Awaish Kumar: I don’t know, I can’t… I can address it to… to the… like, there’s no channel.
449 00:35:36.160 ⇒ 00:35:50.929 Awaish Kumar: For those people, because the… yeah, there’s a lot of complication with this project. So, Eden have hired a new engineers, they have a channel with us, but they don’t know much about the system itself, because system is built by surf.
450 00:35:51.170 ⇒ 00:35:57.970 Awaish Kumar: Surf was hired by Brainforge, and he’s no longer supporting that project, because his contract ended.
451 00:35:58.150 ⇒ 00:35:59.050 Awaish Kumar: So…
452 00:35:59.360 ⇒ 00:36:05.829 Awaish Kumar: But this information, this self-stream is still feeding me some of this information. I try to ping them, and…
453 00:36:06.030 ⇒ 00:36:08.579 Awaish Kumar: And get some replies from time to time.
454 00:36:10.890 ⇒ 00:36:16.259 Ashwini Sharma: It’s a one-to-one mapping, right? Order, order item, order item, and treatment door.
455 00:36:16.260 ⇒ 00:36:16.940 Awaish Kumar: survival.
456 00:36:16.940 ⇒ 00:36:18.770 Ashwini Sharma: Is, one-to-one?
457 00:36:18.770 ⇒ 00:36:29.010 Awaish Kumar: Oh, there are… Order item and treatment dose should be 101, because In one order, One item, like, one…
458 00:36:29.680 ⇒ 00:36:35.160 Awaish Kumar: One order, an individual can only get one dose. He cannot get more than one dose.
459 00:36:35.300 ⇒ 00:36:36.529 Awaish Kumar: In a single order.
460 00:36:38.900 ⇒ 00:36:56.700 Awaish Kumar: Like, if you… if you apply for any treatment in Eden, and then you, for example, want to… in your order, there’s an order item for, for example, semaglatitude, then you cannot order, like, 2 months of semaglatitude. If your… your dose is for one month, you will only get one month.
461 00:36:58.370 ⇒ 00:37:00.189 Awaish Kumar: So, it should be one-on-one better.
462 00:37:01.100 ⇒ 00:37:03.850 Ashwini Sharma: what is treatment dose like? Treatment dose is, basically.
463 00:37:03.850 ⇒ 00:37:05.150 Awaish Kumar: Billing period.
464 00:37:06.180 ⇒ 00:37:09.879 Awaish Kumar: Yeah, treatment doses, exactly what I just told you about.
465 00:37:10.750 ⇒ 00:37:14.400 Awaish Kumar: The actual, like, the product dose he’s getting.
466 00:37:15.320 ⇒ 00:37:20.209 Awaish Kumar: So how much days this will last? Like, if it’s a 28 days tours over a…
467 00:37:21.310 ⇒ 00:37:24.050 Awaish Kumar: What, 3-month dose, or whatever it is.
468 00:37:24.280 ⇒ 00:37:26.400 Awaish Kumar: And what escape of the…
469 00:37:26.650 ⇒ 00:37:36.989 Awaish Kumar: dose plan, what step is at, like, if it’s your first time buying that dose, or if your third time buying that dose, right? And things like that.
470 00:37:37.500 ⇒ 00:37:44.780 Ashwini Sharma: So if we can create… okay, so basically create one table, right, which is at the order line… order line item level.
471 00:37:45.390 ⇒ 00:37:46.010 Awaish Kumar: We only have…
472 00:37:46.720 ⇒ 00:37:49.070 Ashwini Sharma: Fact order line item?
473 00:37:49.430 ⇒ 00:37:53.869 Awaish Kumar: We have other items, then we can include these things in order.
474 00:37:54.360 ⇒ 00:38:00.410 Ashwini Sharma: Right, right, yeah, that’s what I’m saying. I created a new table, which is at the grain of order item level, but it includes the…
475 00:38:00.880 ⇒ 00:38:02.260 Ashwini Sharma: the amount.
476 00:38:03.190 ⇒ 00:38:03.710 Awaish Kumar: California.
477 00:38:03.710 ⇒ 00:38:05.310 Ashwini Sharma: via this route.
478 00:38:08.220 ⇒ 00:38:09.010 Ashwini Sharma: Right?
479 00:38:09.560 ⇒ 00:38:16.010 Awaish Kumar: We already have order item table, we just have to bring that in. Maybe add a few weeks or fields, yeah.
480 00:38:16.450 ⇒ 00:38:25.459 Ashwini Sharma: Okay, and okay, let’s take a step back. That is regarding the amount, right? This is for the amount calculation, for the revenue calculation, right?
481 00:38:25.460 ⇒ 00:38:26.040 Awaish Kumar: be?
482 00:38:26.240 ⇒ 00:38:36.180 Awaish Kumar: ID, item ID, order item, we go to the treatment doors, and we bring in the amount. Second thing we need to bring in is product name itself.
483 00:38:37.270 ⇒ 00:38:41.910 Ashwini Sharma: Product name, yeah, product name. Product name is the pharmacy, this thing.
484 00:38:41.910 ⇒ 00:38:51.480 Awaish Kumar: No, pharmacy is the… that is… And that might be just… Sending that… item, but…
485 00:38:52.890 ⇒ 00:38:55.119 Awaish Kumar: This does not have a product name here.
486 00:38:55.570 ⇒ 00:38:56.209 Awaish Kumar: I don’t think…
487 00:38:58.230 ⇒ 00:39:00.019 Ashwini Sharma: Where is the product name, then?
488 00:39:00.690 ⇒ 00:39:06.030 Awaish Kumar: Maybe we have to go from other eye treatment doors, or somewhere.
489 00:39:06.400 ⇒ 00:39:07.980 Awaish Kumar: Oh, cool.
490 00:39:10.120 ⇒ 00:39:18.749 Ashwini Sharma: treatment does… Treatment dose, okay? Treatment dose has a consultation ID, that is created date ID,
491 00:39:19.280 ⇒ 00:39:25.230 Ashwini Sharma: Invoice ID, sequence number, treatment ID. Treatment ID cannot be the product name.
492 00:39:25.600 ⇒ 00:39:26.600 Awaish Kumar: Those medications.
493 00:39:28.990 ⇒ 00:39:33.260 Awaish Kumar: it has 3.1’s ID, it has quantity, Schedule.
494 00:39:37.790 ⇒ 00:39:41.520 Awaish Kumar: And there is offering, I think. It is in some kind of offering table.
495 00:39:42.900 ⇒ 00:39:43.900 Ashwini Sharma: Aww.
496 00:39:44.760 ⇒ 00:39:46.370 Awaish Kumar: There should be something called…
497 00:39:46.910 ⇒ 00:39:47.780 Ashwini Sharma: offering.
498 00:39:52.940 ⇒ 00:39:58.959 Ashwini Sharma: What is the, hold on a second, what is the…
499 00:39:59.690 ⇒ 00:40:02.610 Ashwini Sharma: Is these tables available in broad?
500 00:40:03.640 ⇒ 00:40:05.959 Ashwini Sharma: These, these, rotables?
501 00:40:06.800 ⇒ 00:40:07.640 Awaish Kumar: Right, right?
502 00:40:09.970 ⇒ 00:40:11.850 Ashwini Sharma: Is this there, right, in Broad?
503 00:40:12.610 ⇒ 00:40:15.130 Awaish Kumar: Broadwood, like.
504 00:40:15.130 ⇒ 00:40:16.690 Ashwini Sharma: Dbt Broadmart.
505 00:40:17.790 ⇒ 00:40:20.000 Awaish Kumar: These will be in raw, like…
506 00:40:20.780 ⇒ 00:40:22.850 Awaish Kumar: The raw, like, if you look at a source…
507 00:40:22.850 ⇒ 00:40:25.640 Ashwini Sharma: Yeah, yeah, DBT raw, sorry, DBT raw, yeah.
508 00:40:26.180 ⇒ 00:40:34.170 Awaish Kumar: If you look at source.vimil, where it is bringing it from, you can… like… In source.vml file, search for
509 00:40:34.300 ⇒ 00:40:37.249 Awaish Kumar: Roid invoice, and the dataset name is this one.
510 00:40:38.930 ⇒ 00:40:43.630 Ashwini Sharma: Okay, in the previous BASH model, where is the product name located?
511 00:40:44.900 ⇒ 00:40:49.560 Awaish Kumar: Basque model, the product name is inside the… Order completed itself.
512 00:40:52.680 ⇒ 00:40:54.150 Awaish Kumar: Yeah, in this order.
513 00:40:54.150 ⇒ 00:40:54.990 Ashwini Sharma: Believe it or not.
514 00:40:55.920 ⇒ 00:40:57.640 Awaish Kumar: You will see the bottom.
515 00:41:02.550 ⇒ 00:41:04.380 Ashwini Sharma: Product name is the rocket.
516 00:41:09.820 ⇒ 00:41:10.495 Ashwini Sharma: And…
517 00:41:36.510 ⇒ 00:41:40.719 Ashwini Sharma: not write an OS. Sources Eden OS sources.
518 00:42:14.110 ⇒ 00:42:15.760 Ashwini Sharma: Let’s see if it does that.
519 00:42:35.690 ⇒ 00:42:42.580 Ashwini Sharma: While it is doing it, how… what about the new customer, old customer? There are certain things, right?
520 00:42:43.900 ⇒ 00:42:45.390 Ashwini Sharma: I’m just…
521 00:42:45.580 ⇒ 00:42:46.190 Awaish Kumar: Correct.
522 00:42:47.450 ⇒ 00:42:51.279 Ashwini Sharma: There were this, new customer, returning customer.
523 00:42:51.280 ⇒ 00:42:57.129 Awaish Kumar: Yeah, new customer is just… we figure out from the order itself. If that order is…
524 00:42:57.590 ⇒ 00:43:05.230 Awaish Kumar: like, if you partition by customer ID, right, and order by…
525 00:43:05.690 ⇒ 00:43:13.140 Awaish Kumar: the time… the timestamp, and only the first order is… is the first order for that customer, right? And all others are…
526 00:43:14.260 ⇒ 00:43:16.120 Awaish Kumar: Or, or after that.
527 00:43:16.800 ⇒ 00:43:21.060 Ashwini Sharma: No, but how do you come to a new, new call?
528 00:43:22.240 ⇒ 00:43:22.560 Awaish Kumar: So…
529 00:43:22.560 ⇒ 00:43:24.050 Ashwini Sharma: Oh, God.
530 00:43:24.050 ⇒ 00:43:29.100 Awaish Kumar: So, if you’re written by… Customer ID. You get all the orders for their customer, right?
531 00:43:29.310 ⇒ 00:43:29.900 Ashwini Sharma: Yeah.
532 00:43:30.530 ⇒ 00:43:40.440 Awaish Kumar: And then you say, okay, if you order it by time, then you will, in ascending order, you will… the first one is the first order from this customer.
533 00:43:40.560 ⇒ 00:43:45.120 Awaish Kumar: then your isFirstOrder flag will be true, for that.
534 00:43:45.520 ⇒ 00:43:49.020 Awaish Kumar: If it is… If… if it is one, right?
535 00:43:49.190 ⇒ 00:43:53.330 Awaish Kumar: otherwise false, so that’s… We just, like, used that.
536 00:43:53.750 ⇒ 00:43:57.499 Ashwini Sharma: Oh, you mean the row count, row count, right? Okay, got it, yeah.
537 00:43:57.500 ⇒ 00:44:04.280 Awaish Kumar: Not a… it’s not a raw count, it’s a… Yeah, row number, actually.
538 00:44:04.280 ⇒ 00:44:09.669 Ashwini Sharma: It should be row count, because only one order should be there for that customer, to be a new customer.
539 00:44:10.520 ⇒ 00:44:13.840 Awaish Kumar: Yeah, yeah, it is… yeah, you are right, it’s… it’s a…
540 00:44:14.210 ⇒ 00:44:16.960 Awaish Kumar: row number function, not a row count, I think.
541 00:44:18.720 ⇒ 00:44:19.295 Ashwini Sharma: Hmm…
542 00:44:19.870 ⇒ 00:44:21.910 Awaish Kumar: The function name is Rhod, right?
543 00:44:22.200 ⇒ 00:44:28.529 Ashwini Sharma: No, row number is going to return you in sequential order, right? If there are multiple rows, it will return one.
544 00:44:28.530 ⇒ 00:44:28.890 Awaish Kumar: True.
545 00:44:28.890 ⇒ 00:44:30.209 Ashwini Sharma: 3 like that, right?
546 00:44:30.430 ⇒ 00:44:42.550 Awaish Kumar: But you… if you rank it for each customer, if you rank it by timestamp, and then you say, if my… the… where the rank is 1 is my first order, right? You can figure that out that way as well.
547 00:44:43.020 ⇒ 00:44:47.429 Ashwini Sharma: Yeah, that is the first order. What I’m asking is new customer, right?
548 00:44:48.090 ⇒ 00:44:56.200 Awaish Kumar: So, that is the new customer, that the time it made a first order, at that moment, it was a new customer. For example.
549 00:44:56.530 ⇒ 00:45:03.820 Awaish Kumar: if Ashwini… Or, like, in our system, we want to identify new customer at each level.
550 00:45:03.980 ⇒ 00:45:07.940 Awaish Kumar: So, for example, if you came in January 2025,
551 00:45:08.050 ⇒ 00:45:10.739 Awaish Kumar: And if I’m… if I go back to that month.
552 00:45:10.880 ⇒ 00:45:14.519 Awaish Kumar: For me, you are a new customer in that specific time period.
553 00:45:17.130 ⇒ 00:45:19.929 Ashwini Sharma: Okay, okay, that is what you’re saying. Okay, got it, yeah.
554 00:45:20.110 ⇒ 00:45:21.789 Awaish Kumar: So, similarly… What a diff?
555 00:45:21.790 ⇒ 00:45:23.740 Ashwini Sharma: Yeah, it’s for a date, right? For a single date.
556 00:45:24.220 ⇒ 00:45:29.470 Awaish Kumar: Yeah, but now, for future ones, it also works, but if, for example, today’s…
557 00:45:29.610 ⇒ 00:45:41.040 Awaish Kumar: 31st of March, somebody comes in, gives an order, my model will work. There is only one order, and it will be marked as error number is 1 for that. So he’s a new customer only.
558 00:45:45.600 ⇒ 00:45:49.330 Awaish Kumar: So, it is by date, right? But today, he’s a new customer.
559 00:45:49.630 ⇒ 00:45:53.630 Awaish Kumar: If I look for today, We, we might have only got…
560 00:45:53.630 ⇒ 00:46:00.069 Ashwini Sharma: This was the one, right? Product Rose LTV? No, it was, it was a different one.
561 00:46:00.310 ⇒ 00:46:02.340 Awaish Kumar: So, for the… For the Josh?
562 00:46:02.680 ⇒ 00:46:04.379 Ashwini Sharma: Pro-Pro sales summary.
563 00:46:05.070 ⇒ 00:46:07.020 Awaish Kumar: Yeah, this one is for product sales summary.
564 00:46:07.550 ⇒ 00:46:10.380 Ashwini Sharma: Product gross. This is for sale summit? Okay.
565 00:46:10.620 ⇒ 00:46:11.190 Awaish Kumar: Damn.
566 00:46:11.470 ⇒ 00:46:16.690 Ashwini Sharma: Hold on a second, so what we need is the total ad spend? No, this is ad spend, or is it.
567 00:46:16.690 ⇒ 00:46:20.030 Awaish Kumar: Ad spend, actually, some marketing ad spend.
568 00:46:21.590 ⇒ 00:46:27.160 Ashwini Sharma: Okay, and how are we getting this ad spend? Is there any model that returns us ad spend?
569 00:46:27.630 ⇒ 00:46:32.680 Awaish Kumar: Yes, like, you worked on a product sale summary, I thought you already figured that out.
570 00:46:32.910 ⇒ 00:46:35.700 Ashwini Sharma: No, that was the orders, the PR was for orders right here.
571 00:46:35.700 ⇒ 00:46:40.750 Awaish Kumar: Yeah, an order summary and product size summary. PR was for two models, but I can show you…
572 00:46:40.750 ⇒ 00:46:42.220 Ashwini Sharma: Let me let Wayne go through it.
573 00:46:42.220 ⇒ 00:46:42.790 Awaish Kumar: Bye-bye.
574 00:46:43.180 ⇒ 00:46:44.350 Awaish Kumar: to go to marketing.
575 00:46:44.910 ⇒ 00:46:47.150 Awaish Kumar: Marketing… Did you go to marketing?
576 00:46:47.410 ⇒ 00:46:48.569 Awaish Kumar: Under March.
577 00:46:49.210 ⇒ 00:46:50.679 Ashwini Sharma: Under mods, okay?
578 00:46:53.330 ⇒ 00:46:55.310 Awaish Kumar: March?
579 00:46:55.950 ⇒ 00:46:58.120 Awaish Kumar: Not Eden OS. Marketing.
580 00:47:02.340 ⇒ 00:47:09.729 Awaish Kumar: So… Okay, so there is a channel spend summary, so you can get it from…
581 00:47:09.870 ⇒ 00:47:15.200 Awaish Kumar: Here, but it might not be wise, because it gives you by… only by…
582 00:47:16.100 ⇒ 00:47:25.329 Awaish Kumar: Yeah, it gives you by channel, but we don’t just need by channel, we also need by product, so we have to maybe go one step back from here to…
583 00:47:25.600 ⇒ 00:47:27.020 Awaish Kumar: You can go to the…
584 00:47:27.400 ⇒ 00:47:29.779 Ashwini Sharma: This one is better. We can utilize this as a…
585 00:47:30.230 ⇒ 00:47:30.869 Awaish Kumar: What’s a clue.
586 00:47:31.030 ⇒ 00:47:33.710 Awaish Kumar: Oh, you can… there is a product name, then you can use it.
587 00:47:35.400 ⇒ 00:47:37.660 Awaish Kumar: There is a product name, a standardized product name.
588 00:47:37.660 ⇒ 00:47:38.620 Ashwini Sharma: Yes, fair enough.
589 00:47:38.910 ⇒ 00:47:39.670 Awaish Kumar: Yeah.
590 00:47:42.840 ⇒ 00:47:45.290 Awaish Kumar: Yeah, so this, yeah, we can use it.
591 00:47:45.490 ⇒ 00:47:54.029 Awaish Kumar: Also, if… but if you… if it isn’t… if it doesn’t support what you are doing, then you can go back to these tables that are being used here.
592 00:47:54.910 ⇒ 00:47:57.880 Awaish Kumar: Like, into offline channel spend, give you this…
593 00:47:57.880 ⇒ 00:47:58.450 Ashwini Sharma: this.
594 00:47:58.800 ⇒ 00:47:59.130 Awaish Kumar: data?
595 00:47:59.130 ⇒ 00:48:01.580 Ashwini Sharma: Sprint summary, right? This one, for each product.
596 00:48:01.970 ⇒ 00:48:10.529 Ashwini Sharma: And then you have the new customer count, this is just the count of new customers. This is new customer revenue, for the new customer revenue generated by new customers.
597 00:48:10.720 ⇒ 00:48:15.589 Ashwini Sharma: New refund, total refund, new orders, okay? This is, again, aggregation of
598 00:48:15.810 ⇒ 00:48:18.590 Ashwini Sharma: Refund amount for the new customers, okay?
599 00:48:18.590 ⇒ 00:48:23.969 Awaish Kumar: Figure that out from also from here, how he’s doing. If you click on edit.
600 00:48:24.090 ⇒ 00:48:25.999 Awaish Kumar: It will get you to the worksheet.
601 00:48:26.130 ⇒ 00:48:28.849 Awaish Kumar: And you can see what exactly is being used.
602 00:48:30.470 ⇒ 00:48:32.940 Awaish Kumar: In the edit on top, not here.
603 00:48:33.540 ⇒ 00:48:35.959 Awaish Kumar: On top bar, on the left side.
604 00:48:36.540 ⇒ 00:48:37.970 Ashwini Sharma: Oh, okay, okay, okay.
605 00:48:38.130 ⇒ 00:48:40.749 Awaish Kumar: You can go in to that.
606 00:48:41.440 ⇒ 00:48:44.279 Awaish Kumar: And there… it will open a worksheet.
607 00:48:44.390 ⇒ 00:48:48.159 Awaish Kumar: And you go into Workshade, and you can see what exact field is being used, or…
608 00:48:59.040 ⇒ 00:49:02.190 Awaish Kumar: So, you have to find out your worksheet.
609 00:49:02.510 ⇒ 00:49:08.109 Awaish Kumar: And then you can… look at the fields. So this is the full dashboard.
610 00:49:09.190 ⇒ 00:49:09.830 Awaish Kumar: Australia.
611 00:49:09.830 ⇒ 00:49:12.009 Ashwini Sharma: How do I look into the query? Where is the…
612 00:49:12.460 ⇒ 00:49:17.340 Awaish Kumar: You have to look the… exact… from the un…
613 00:49:17.780 ⇒ 00:49:20.449 Awaish Kumar: Ashwini, at the bottom, there are different worksheets.
614 00:49:21.420 ⇒ 00:49:22.150 Ashwini Sharma: Okay.
615 00:49:22.340 ⇒ 00:49:25.059 Awaish Kumar: You have to find what chart you are looking for.
616 00:49:25.060 ⇒ 00:49:28.980 Ashwini Sharma: Total refund orders. New customer…
617 00:49:28.980 ⇒ 00:49:32.640 Awaish Kumar: All of the marketing matrix new orders is your chart.
618 00:49:34.250 ⇒ 00:49:36.890 Awaish Kumar: So you just scroll to the right, you figure out
619 00:49:37.020 ⇒ 00:49:45.749 Awaish Kumar: which one is your chart that is giving you a table, like this? You can click on those, and you can see if it is giving you the exact…
620 00:49:46.540 ⇒ 00:49:47.570 Awaish Kumar: Same thing.
621 00:49:47.810 ⇒ 00:49:48.830 Awaish Kumar: Yeah.
622 00:49:48.830 ⇒ 00:49:50.420 Ashwini Sharma: A box here, yeah?
623 00:49:52.440 ⇒ 00:49:57.340 Awaish Kumar: Yeah, on the left-hand side, you see the columns that are being used, and all of that.
624 00:49:59.100 ⇒ 00:50:03.150 Ashwini Sharma: This is already a calculated column, this one, okay? All right.
625 00:50:03.440 ⇒ 00:50:06.770 Ashwini Sharma: How do we… this is what clues.
626 00:50:12.850 ⇒ 00:50:16.530 Ashwini Sharma: Okay, let’s, let’s sync up after some more time, and then,
627 00:50:17.420 ⇒ 00:50:19.620 Ashwini Sharma: I’ll kind of work on this.
628 00:50:21.030 ⇒ 00:50:22.650 Awaish Kumar: Taking care of order items.
629 00:50:24.020 ⇒ 00:50:29.750 Ashwini Sharma: order? Yeah, yeah, I’ll use the order item level, and then aggregate it at.
630 00:50:30.270 ⇒ 00:50:30.920 Awaish Kumar: Yeah, product.
631 00:50:30.920 ⇒ 00:50:34.239 Ashwini Sharma: Basically, I’ll just create something at the order item level.
632 00:50:34.650 ⇒ 00:50:38.140 Ashwini Sharma: Right, and then we can use that to aggregate.
633 00:50:38.320 ⇒ 00:50:39.220 Awaish Kumar: This is…
634 00:50:39.220 ⇒ 00:50:40.950 Ashwini Sharma: Create this kind of table.
635 00:50:41.300 ⇒ 00:50:46.060 Awaish Kumar: This table can be created from order item. That’s why I’m telling you, if you…
636 00:50:46.180 ⇒ 00:50:49.849 Awaish Kumar: Work on either item, and just figure out how to get the product name in there.
637 00:50:50.040 ⇒ 00:50:55.759 Awaish Kumar: And then… Then, yeah, this can be built totally on top of that.
638 00:50:56.050 ⇒ 00:51:00.799 Ashwini Sharma: Yeah, product name, product revenue, as well as an indicator whether it’s a new customer.
639 00:51:01.610 ⇒ 00:51:06.619 Ashwini Sharma: For each order, right? So, okay, so there is a link to the customer also.
640 00:51:08.000 ⇒ 00:51:11.790 Ashwini Sharma: Eden OS, so let’s look at order.
641 00:51:12.330 ⇒ 00:51:16.660 Ashwini Sharma: Order item, does… Order.
642 00:51:17.750 ⇒ 00:51:20.769 Ashwini Sharma: Does order have a customer ID associated with it?
643 00:52:09.680 ⇒ 00:52:10.820 Awaish Kumar: Yeah, so…
644 00:52:11.000 ⇒ 00:52:18.029 Awaish Kumar: We don’t have to go back to customer, there is also a raw patient table. We just have to…
645 00:52:18.500 ⇒ 00:52:20.480 Awaish Kumar: We can bring the data from there.
646 00:52:21.440 ⇒ 00:52:22.489 Ashwini Sharma: On the patient table.
647 00:52:23.480 ⇒ 00:52:26.209 Awaish Kumar: Yeah, yeah, because whenever somebody, somebody…
648 00:52:26.420 ⇒ 00:52:33.700 Awaish Kumar: In Eden OS system, if someone buys something from Eden, then it becomes a patient. So there is the Eden OS patient table.
649 00:52:33.940 ⇒ 00:52:38.870 Awaish Kumar: Yeah, we have to… We can join it with this table, and…
650 00:52:47.110 ⇒ 00:52:49.990 Awaish Kumar: Okay, so if, if you find out…
651 00:52:50.100 ⇒ 00:52:52.909 Awaish Kumar: How to join it with the customer ID, and then a product.
652 00:52:54.510 ⇒ 00:53:01.700 Awaish Kumar: Let me know if… And we can maybe meet up, maybe after an hour or something.
653 00:53:02.070 ⇒ 00:53:07.869 Ashwini Sharma: Yeah, here it is. Treatment, treatment ID. Treatment ID has a patient ID associated with it. I think you can use this one to link.
654 00:53:08.390 ⇒ 00:53:16.730 Awaish Kumar: So, basically, you can… If you are in order, given the user ID, you can use treatment order table.
655 00:53:16.980 ⇒ 00:53:19.190 Awaish Kumar: to connect it with the treatment ID.
656 00:53:19.320 ⇒ 00:53:22.869 Awaish Kumar: And then, from the treatment ID, you can get the patient ID.
657 00:53:23.210 ⇒ 00:53:23.980 Awaish Kumar: Yeah.
658 00:53:24.980 ⇒ 00:53:26.520 Awaish Kumar: There’s, there’s some mapping with…
659 00:53:30.800 ⇒ 00:53:36.129 Ashwini Sharma: Basically, order line… order, order, order item. Order as a treatment?
660 00:53:36.320 ⇒ 00:53:37.070 Ashwini Sharma: Nope.
661 00:53:37.290 ⇒ 00:53:39.369 Ashwini Sharma: It’s the order line which has treatment.
662 00:53:40.920 ⇒ 00:53:41.479 Awaish Kumar: No, no.
663 00:53:41.480 ⇒ 00:53:41.930 Ashwini Sharma: You know, it’.
664 00:53:42.320 ⇒ 00:53:49.529 Awaish Kumar: Treatment is not there. Only way to go with… from order to treatment is using treatment order. It’s a mapping table.
665 00:53:49.530 ⇒ 00:53:52.699 Ashwini Sharma: Treatment. Okay, treatment order, yeah.
666 00:53:52.970 ⇒ 00:54:03.519 Ashwini Sharma: Alright, so treatment ID, and then… okay. Oh, we have the order ID. Order ID, you get the treatment ID, and then from treatment ID, from the treatment, you get the patient ID.
667 00:54:05.980 ⇒ 00:54:07.980 Ashwini Sharma: Patient ID, yeah, alright, cool.
668 00:54:08.760 ⇒ 00:54:11.070 Awaish Kumar: Okay, yeah, see you, can…
669 00:54:11.150 ⇒ 00:54:13.550 Ashwini Sharma: Alright, yeah, I’ll ping you again, yeah.
670 00:54:15.050 ⇒ 00:54:15.680 Awaish Kumar: Thanks.