Meeting Title: Javy-Project-Internal-Review Date: 2024-10-03 Meeting participants: Nicolas Sucari, Uttam Kumaran, Brian Pei, Payas Parab
WEBVTT
1 00:05:25.900 ⇒ 00:05:26.530 Brian Pei: Yeah.
2 00:05:26.530 ⇒ 00:05:27.300 Uttam Kumaran: Oh!
3 00:05:28.620 ⇒ 00:05:29.430 Brian Pei: Hello!
4 00:05:30.630 ⇒ 00:05:33.811 Uttam Kumaran: I didn’t know it was just you alone, chilling in here. I was just late.
5 00:05:34.170 ⇒ 00:05:35.430 Brian Pei: I’m hanging out.
6 00:05:36.340 ⇒ 00:05:37.120 Nicolas Sucari: Hey! Brian.
7 00:05:37.840 ⇒ 00:05:38.770 Brian Pei: What’s up?
8 00:05:40.420 ⇒ 00:05:41.560 Nicolas Sucari: All good here.
9 00:05:43.350 ⇒ 00:05:45.179 Nicolas Sucari: Oh, we spare gas!
10 00:05:47.460 ⇒ 00:05:48.190 Brian Pei: What was that?
11 00:05:48.880 ⇒ 00:05:50.249 Nicolas Sucari: You’re still in Vegas.
12 00:05:50.930 ⇒ 00:05:53.989 Brian Pei: Yeah. I’m going back to New York on Sunday.
13 00:05:55.400 ⇒ 00:05:56.390 Uttam Kumaran: And homesick.
14 00:05:57.330 ⇒ 00:05:58.130 Brian Pei: Little bit
15 00:05:59.020 ⇒ 00:06:00.339 Brian Pei: little bit.
16 00:06:00.630 ⇒ 00:06:01.790 Brian Pei: It’s not that bad, though.
17 00:06:05.600 ⇒ 00:06:11.520 Uttam Kumaran: What’s what’s your like? What’s your like during the week schedule like in New York these days?
18 00:06:13.730 ⇒ 00:06:15.779 Brian Pei: It’s my I don’t. I don’t know. I’ll find out.
19 00:06:15.780 ⇒ 00:06:18.089 Uttam Kumaran: Like, what do you do like? What do you do after work?
20 00:06:18.170 ⇒ 00:06:20.690 Uttam Kumaran: Are you still golfing like heavy.
21 00:06:20.900 ⇒ 00:06:22.639 Brian Pei: I’m golfing heavy
22 00:06:22.870 ⇒ 00:06:24.440 Brian Pei: and
23 00:06:26.240 ⇒ 00:06:27.790 Brian Pei: drinking.
24 00:06:27.950 ⇒ 00:06:28.890 Brian Pei: I don’t know
25 00:06:29.320 ⇒ 00:06:31.279 Brian Pei: this is being recorded. I’m not gonna.
26 00:06:32.440 ⇒ 00:06:32.869 Uttam Kumaran: I don’t want.
27 00:06:32.870 ⇒ 00:06:35.199 Brian Pei: Stay home. And I watch movies.
28 00:06:38.980 ⇒ 00:06:39.680 Uttam Kumaran: Alright.
29 00:06:40.450 ⇒ 00:06:42.430 Uttam Kumaran: very very cool.
30 00:06:42.430 ⇒ 00:06:44.140 Brian Pei: Keep myself occupied.
31 00:06:44.140 ⇒ 00:06:47.329 Uttam Kumaran: Very cool. Yeah, this is how a conversation works.
32 00:06:47.470 ⇒ 00:06:48.140 Uttam Kumaran: Okay.
33 00:06:48.560 ⇒ 00:06:50.660 Brian Pei: Well, it’s it’s a different.
34 00:06:50.660 ⇒ 00:06:52.200 Uttam Kumaran: I’m just asking about how.
35 00:06:52.200 ⇒ 00:06:58.240 Brian Pei: Fireflies, fireflies is noting all of my oh, you want me to say sports betting. I go to the Casino.
36 00:06:59.760 ⇒ 00:07:00.620 Brian Pei: want to hear.
37 00:07:00.760 ⇒ 00:07:05.150 Uttam Kumaran: No, but I also tried to remove. I tried to get rid of fireflies, Nico. I don’t know why.
38 00:07:06.350 ⇒ 00:07:09.340 Nicolas Sucari: No, but this one is from Payas, so I.
39 00:07:09.340 ⇒ 00:07:12.199 Uttam Kumaran: See if you can remove it. See if you can just get get rid of it.
40 00:07:13.630 ⇒ 00:07:14.580 Nicolas Sucari: Yeah, I can
41 00:07:15.090 ⇒ 00:07:15.640 Nicolas Sucari: remove.
42 00:07:15.640 ⇒ 00:07:29.010 Uttam Kumaran: Yeah, just just ditch it. Cause I just don’t. I don’t know. Like, I don’t know. I try. I emailed them being like, don’t allow anything on our domain because it’s just like it. I don’t want stuff going to external companies, and we already have our own internal recorder.
43 00:07:29.900 ⇒ 00:07:31.040 Nicolas Sucari: Yeah, okay.
44 00:07:31.040 ⇒ 00:07:35.379 Uttam Kumaran: So I’m happy to share our notes like I’m happy to send the transcript over to him after.
45 00:07:36.120 ⇒ 00:07:36.700 Nicolas Sucari: Okay.
46 00:07:39.290 ⇒ 00:07:45.469 Nicolas Sucari: I think when we when you invite someone to the meeting that has
47 00:07:45.790 ⇒ 00:07:47.960 Nicolas Sucari: fireflies notetaker
48 00:07:48.536 ⇒ 00:07:52.429 Nicolas Sucari: like, automatically they join with the notetaker.
49 00:07:52.840 ⇒ 00:07:53.289 Uttam Kumaran: Yeah.
50 00:08:03.410 ⇒ 00:08:07.010 Nicolas Sucari: Are you going to the formula? One there in Austin?
51 00:08:07.230 ⇒ 00:08:08.240 Nicolas Sucari: What time.
52 00:08:08.240 ⇒ 00:08:11.879 Uttam Kumaran: I have some friends that are visiting me to go. I’m not going, though.
53 00:08:11.880 ⇒ 00:08:12.600 Nicolas Sucari: Nice
54 00:08:14.740 ⇒ 00:08:16.380 Nicolas Sucari: pretty interesting. Event.
55 00:08:17.000 ⇒ 00:08:19.090 Uttam Kumaran: Yeah, it’ll be packed here.
56 00:08:19.400 ⇒ 00:08:19.949 Uttam Kumaran: How much.
57 00:08:19.950 ⇒ 00:08:20.790 Brian Pei: Tickets.
58 00:08:21.830 ⇒ 00:08:26.860 Uttam Kumaran: Tickets are a lot dude like I don’t know. Probably like close to 800 bucks. Maybe.
59 00:08:27.140 ⇒ 00:08:27.870 Nicolas Sucari: Yeah.
60 00:08:27.870 ⇒ 00:08:28.390 Brian Pei: Brother.
61 00:08:28.390 ⇒ 00:08:30.130 Nicolas Sucari: Or the 3 days. Yeah, maybe.
62 00:08:30.710 ⇒ 00:08:31.640 Uttam Kumaran: Yeah.
63 00:08:31.640 ⇒ 00:08:33.390 Brian Pei: Not worth
64 00:08:35.159 ⇒ 00:08:36.940 Brian Pei: really like fast cars.
65 00:08:37.220 ⇒ 00:08:38.740 Brian Pei: I like slow
66 00:08:39.539 ⇒ 00:08:40.870 Brian Pei: convertibles.
67 00:08:43.789 ⇒ 00:08:45.693 Uttam Kumaran: Who said, nobody ever
68 00:08:47.330 ⇒ 00:08:51.399 Uttam Kumaran: nobody’s. I like fast convertibles and fast Suvs.
69 00:08:53.390 ⇒ 00:09:00.419 Brian Pei: At what point in our working lives will we have to go from 0 to 90 in like 2 seconds? Ever in our lives.
70 00:09:01.310 ⇒ 00:09:02.710 Uttam Kumaran: Whenever you want to.
71 00:09:04.150 ⇒ 00:09:04.530 Brian Pei: No man.
72 00:09:04.530 ⇒ 00:09:09.989 Uttam Kumaran: It’s not about. It’s not about when do you have to? It’s about having the ability to right. It’s like, it’s like free speech.
73 00:09:10.600 ⇒ 00:09:17.430 Uttam Kumaran: You can’t just be like, yeah, it’s like, I want the right to do it. Is it illegal to go that to go 0 to 90,
74 00:09:17.470 ⇒ 00:09:20.490 Uttam Kumaran: maybe. Like, yeah, maybe a little bit. But
75 00:09:22.500 ⇒ 00:09:31.510 Uttam Kumaran: I mean, I don’t know. Dude. I think it’s fun that fast cars are fun. They are dangerous, though. And do people here in Texas, like the driving, is very dangerous. Everybody drives super fast.
76 00:09:33.030 ⇒ 00:09:36.870 Brian Pei: I double, lock my seatbelt, I buy another seatbelt on Amazon.
77 00:09:37.200 ⇒ 00:09:40.519 Brian Pei: I double strap in. That’s how safe I am on the road.
78 00:09:42.580 ⇒ 00:09:43.620 Uttam Kumaran: You’re a loser.
79 00:09:43.620 ⇒ 00:09:45.860 Nicolas Sucari: Yeah, I am. I made that up.
80 00:09:51.130 ⇒ 00:09:52.440 Brian Pei: Gotta be safe.
81 00:09:53.510 ⇒ 00:09:54.490 Nicolas Sucari: Hey! Payaz.
82 00:09:55.430 ⇒ 00:09:56.555 Payas Parab: Hey, guys, how’s it going.
83 00:09:56.910 ⇒ 00:09:57.580 Uttam Kumaran: Hey!
84 00:09:57.580 ⇒ 00:09:58.440 Brian Pei: What’s up?
85 00:09:58.990 ⇒ 00:09:59.569 Brian Pei: We’re just.
86 00:09:59.570 ⇒ 00:10:00.410 Payas Parab: Alright! How are you.
87 00:10:00.410 ⇒ 00:10:00.760 Brian Pei: Island.
88 00:10:00.760 ⇒ 00:10:01.880 Payas Parab: Sorry I’m late.
89 00:10:02.890 ⇒ 00:10:04.426 Brian Pei: No, you’re good. We
90 00:10:05.090 ⇒ 00:10:08.120 Brian Pei: Aman’s not here yet, so we’re kind of just shooting the shit.
91 00:10:10.420 ⇒ 00:10:12.880 Uttam Kumaran: I think it’s just us on this. I don’t think I’m on this one.
92 00:10:12.880 ⇒ 00:10:13.450 Nicolas Sucari: Yeah.
93 00:10:13.770 ⇒ 00:10:15.079 Brian Pei: Oh no!
94 00:10:15.080 ⇒ 00:10:16.520 Uttam Kumaran: This is just our internal one.
95 00:10:16.700 ⇒ 00:10:18.849 Brian Pei: Oh, okay, never mind. Then
96 00:10:19.310 ⇒ 00:10:21.160 Brian Pei: I’ll go back on on Cam.
97 00:10:23.060 ⇒ 00:10:25.270 Brian Pei: Okay, wait. This is much better, because I was
98 00:10:26.780 ⇒ 00:10:29.909 Brian Pei: actually never mind. I’ll talk about that when we start.
99 00:10:32.390 ⇒ 00:10:33.240 Nicolas Sucari: Okay.
100 00:10:37.170 ⇒ 00:10:39.040 Brian Pei: I mean, I guess we can. Well.
101 00:10:39.040 ⇒ 00:10:40.192 Uttam Kumaran: Yeah, go for it.
102 00:10:41.020 ⇒ 00:10:42.914 Brian Pei: Oh, wait! Pie has just left.
103 00:10:51.040 ⇒ 00:10:52.960 Nicolas Sucari: We can’t. I don’t think we can hear you.
104 00:10:53.540 ⇒ 00:10:54.369 Nicolas Sucari: But yes.
105 00:10:54.550 ⇒ 00:10:55.480 Nicolas Sucari: oh, yeah.
106 00:10:58.080 ⇒ 00:10:59.049 Payas Parab: Can you hear me now?
107 00:10:59.460 ⇒ 00:11:00.190 Payas Parab: Yep.
108 00:11:00.390 ⇒ 00:11:01.310 Brian Pei: Oh, yep.
109 00:11:03.618 ⇒ 00:11:07.889 Brian Pei: yeah, I didn’t know this was internal, so I guess the 1st
110 00:11:07.930 ⇒ 00:11:10.091 Brian Pei: thing that I’ll throw to you is
111 00:11:11.060 ⇒ 00:11:20.399 Brian Pei: If if anyone. I didn’t do a good job sending it to like the whole channel. But all the threads that pious had I tried to respond to all of them.
112 00:11:22.620 ⇒ 00:11:27.262 Brian Pei: Oh, before I talk about Amazon, I can throw it to you on
113 00:11:28.450 ⇒ 00:11:30.330 Brian Pei: like all of the
114 00:11:32.065 ⇒ 00:11:33.240 Brian Pei: whatever
115 00:11:34.008 ⇒ 00:11:38.150 Brian Pei: pops out at you from updates that we both sent to each other.
116 00:11:38.210 ⇒ 00:11:39.390 Brian Pei: and
117 00:11:39.610 ⇒ 00:11:41.489 Brian Pei: anything else that we need.
118 00:11:42.430 ⇒ 00:11:48.189 Payas Parab: I think I think it’s just. There’s only one. Basically, I think you answered everything. And then like solve for basically, most of the stuff.
119 00:11:48.530 ⇒ 00:12:12.009 Payas Parab: I think it’s just the we just gotta check with them on on the negative inventory. So that’s an item that we need to go over with him. We might just want to ping him in that other chat, so we don’t hold it up if there’s something wrong with that, and he kind of sees some progress along the way you can send that, or I’m happy to send that. That’s the only one. Besides that, I think we’re we’re we’re in a good place around. Everything except, you know. I think I mentioned the shipping thing. There’s 1 analysis we had done which was like
120 00:12:12.010 ⇒ 00:12:25.119 Payas Parab: shipping cost like how much it was, how much the weight impacts the shipping, because sometimes Justin goes and negotiates with their supply, like their shipping providers for better rates. And so
121 00:12:25.190 ⇒ 00:12:35.750 Payas Parab: it’s something that he does use, I believe, from time to time. So we wanna make sure we’re able to capture that. But, like you said. It’s like a manual data entry, right? If someone didn’t put in the weight like there’s nothing we can do about that.
122 00:12:36.364 ⇒ 00:12:39.810 Payas Parab: But I think like you said the actual shipping cost
123 00:12:39.820 ⇒ 00:12:44.719 Payas Parab: is captured in another table. So as long as we know where that is, then I think they’ll be they’ll be okay with that.
124 00:12:45.090 ⇒ 00:12:49.710 Brian Pei: Okay, cool if you don’t mind. If you could send the
125 00:12:49.820 ⇒ 00:12:53.401 Brian Pei: negative inventory question because I’m gonna send something about Amazon.
126 00:12:53.760 ⇒ 00:13:05.670 Payas Parab: Perfect. Yeah, I can. I can send that to him. I’m also gonna send him about. The like is renewal is subscription, like we discussed, and just make sure we get that logic right? So I will bundle that and send that by end of day. Today.
127 00:13:05.870 ⇒ 00:13:06.850 Payas Parab: Cool.
128 00:13:07.320 ⇒ 00:13:11.234 Brian Pei: Do the same with Amazon, which I’ll share really quick.
129 00:13:12.746 ⇒ 00:13:17.620 Brian Pei: let’s see, was there anything else I’m missing? Okay. So Amazon.
130 00:13:18.694 ⇒ 00:13:19.750 Brian Pei: as
131 00:13:20.100 ⇒ 00:13:23.909 Brian Pei: we all know, is very different from shopify. So it took me a little bit longer
132 00:13:24.450 ⇒ 00:13:29.250 Brian Pei: to get a version of order. There are just more tables to be joined. But
133 00:13:29.757 ⇒ 00:13:35.910 Brian Pei: I’ll quickly go over this, because I’ll probably have to do it again with them on next week. But I do have a
134 00:13:36.390 ⇒ 00:13:39.655 Brian Pei: preliminary version of fact. Amazon order.
135 00:13:40.500 ⇒ 00:13:42.980 Brian Pei: what I’ll have to do after this is that
136 00:13:43.330 ⇒ 00:13:50.940 Brian Pei: there’s a lot. There’s a mismatch of columns between Shopify and Amazon, and we would like to make a nice all orders table, obviously.
137 00:13:50.970 ⇒ 00:13:55.269 Brian Pei: So. Next on my list is getting it to fit together. But I wanted to
138 00:13:55.530 ⇒ 00:13:57.339 Brian Pei: get all the Amazon stuff
139 00:13:57.500 ⇒ 00:13:59.590 Brian Pei: in one place first, st before I
140 00:14:00.150 ⇒ 00:14:02.140 Brian Pei: I don’t know. Change column names, and
141 00:14:02.480 ⇒ 00:14:04.310 Brian Pei: whatever all that stuff but
142 00:14:05.730 ⇒ 00:14:09.850 Brian Pei: What I have is the Amazon order. Id looks different, but it’s fine.
143 00:14:10.389 ⇒ 00:14:16.499 Brian Pei: The seller order Id. I might get rid of, because there’s no
144 00:14:17.209 ⇒ 00:14:20.989 Brian Pei: I think the this the seller is
145 00:14:22.080 ⇒ 00:14:24.860 Brian Pei: some entity in Javi, and
146 00:14:25.415 ⇒ 00:14:29.210 Brian Pei: I don’t know if we report on that in in shopify
147 00:14:29.290 ⇒ 00:14:32.120 Brian Pei: it just says shopify. So
148 00:14:32.545 ⇒ 00:14:37.959 Brian Pei: maybe I’ll do a little bit more digging. I need to find out what these actually join to. But this kind of just
149 00:14:38.110 ⇒ 00:14:39.830 Brian Pei: came in. I try to put all the
150 00:14:40.150 ⇒ 00:14:41.650 Brian Pei: ids on the left
151 00:14:42.395 ⇒ 00:14:44.775 Brian Pei: the buyer email, like
152 00:14:45.750 ⇒ 00:14:49.416 Brian Pei: Aman said in the beginning, is hashed
153 00:14:50.540 ⇒ 00:14:55.508 Brian Pei: and oh, wait! This is all amazon.com. Oh, so it’s fully hashed. But
154 00:14:55.850 ⇒ 00:14:58.900 Brian Pei: for a recurring customer it’s the same hash.
155 00:14:58.980 ⇒ 00:15:01.769 Brian Pei: So I am able to get the order number
156 00:15:01.810 ⇒ 00:15:04.949 Brian Pei: based on because I don’t have a customer id in Amazon.
157 00:15:04.990 ⇒ 00:15:11.259 Brian Pei: I can do it on the buyer email. So whoever this is, this was their 1st order, and this was their second order
158 00:15:11.450 ⇒ 00:15:14.229 Brian Pei: based on this this kind of like, hash.
159 00:15:14.994 ⇒ 00:15:19.869 Brian Pei: Let me make sure. That’s right to July August. Yeah. Okay, so it’s kind of working.
160 00:15:21.260 ⇒ 00:15:23.889 Brian Pei: these are the same created and updated
161 00:15:23.960 ⇒ 00:15:29.330 Brian Pei: status and fulfillment are the the same as in shopify shares, columns. With this.
162 00:15:31.340 ⇒ 00:15:34.820 Brian Pei: there was some extra shipping information.
163 00:15:35.140 ⇒ 00:15:38.379 Brian Pei: Actually, no, that’s not even true. This is like the the Amazon
164 00:15:38.450 ⇒ 00:15:39.580 Brian Pei: shipping
165 00:15:39.650 ⇒ 00:15:40.710 Brian Pei: skew
166 00:15:40.780 ⇒ 00:15:48.640 Brian Pei: expedited second day, etc. Standard. That shopify also has. It’s just not named this way, so
167 00:15:48.870 ⇒ 00:15:50.179 Brian Pei: it would be
168 00:15:50.720 ⇒ 00:15:54.470 Brian Pei: if it was all consolidated into orders tough to group by.
169 00:15:54.590 ⇒ 00:15:59.329 Brian Pei: And that’s the case with a lot of stuff, obviously, with
170 00:15:59.580 ⇒ 00:16:04.712 Brian Pei: order skews or product skews, they’re gonna be named differently between systems.
171 00:16:05.260 ⇒ 00:16:08.060 Brian Pei: we can have the conversation of whether we want
172 00:16:08.190 ⇒ 00:16:09.270 Brian Pei: to
173 00:16:09.739 ⇒ 00:16:27.090 Brian Pei: do a case statement on the string to get like like if second day and shopify is second underscore day, or whatever like to change it all. So it all matches if you group by all orders. But I think we want to get this running in Dbt first, st before we do any of the like more.
174 00:16:28.060 ⇒ 00:16:37.989 Brian Pei: It’s not even more challenging. Just the the we need insight on whether or not to do it yet if they want to see stuff like that. But anyway, I digress
175 00:16:38.040 ⇒ 00:16:42.529 Brian Pei: at the very least. The total amount is fine. Total
176 00:16:42.760 ⇒ 00:16:44.490 Brian Pei: item, price amount.
177 00:16:44.510 ⇒ 00:16:48.790 Brian Pei: great shipping amount, great shipping taxes.
178 00:16:49.250 ⇒ 00:16:51.099 Brian Pei: shipping, discounts
179 00:16:51.490 ⇒ 00:16:56.949 Brian Pei: shipping, discount tax which I don’t think is in shopify. I need to double check.
180 00:16:57.140 ⇒ 00:17:01.030 Brian Pei: and then promotion, discount, promotion, discount, tax, I think, in shopify
181 00:17:01.180 ⇒ 00:17:05.380 Brian Pei: discounts are just aggregated with the tax applied.
182 00:17:05.510 ⇒ 00:17:26.729 Brian Pei: and in Amazon it’s split out between what the customer sees, and then any sales tax related to the discount. So again. When I combine them together, I’ll have to do that arithmetic myself, and we can validate once I do that, but for now. All the metric fields. I’m not trying not to do any arithmetic until
183 00:17:27.579 ⇒ 00:17:30.949 Brian Pei: downstream, so I kind of just have all the columns that I saw
184 00:17:30.960 ⇒ 00:17:32.359 Brian Pei: in one place here.
185 00:17:33.444 ⇒ 00:17:39.989 Brian Pei: Obviously, this is Amazon only was it a prime order or not? It’s not going to be in shopify.
186 00:17:40.920 ⇒ 00:17:41.620 Brian Pei: But
187 00:17:41.670 ⇒ 00:17:45.782 Brian Pei: the good news is, I do get shipping information.
188 00:17:46.400 ⇒ 00:17:49.590 Brian Pei: so I do get like this city
189 00:17:49.740 ⇒ 00:17:50.750 Brian Pei: which
190 00:17:51.110 ⇒ 00:17:59.460 Brian Pei: we’ve seen this before. It’s like, sometimes it’s all caps and sometimes it’s not. And so I’ll have to do a bit of cleaning if I want to combine this with the shopify cities.
191 00:18:01.070 ⇒ 00:18:02.740 Brian Pei: address, state, or region.
192 00:18:03.020 ⇒ 00:18:05.640 Brian Pei: It’s a state code unless it’s in Canada
193 00:18:06.966 ⇒ 00:18:09.709 Brian Pei: postal code postal codes.
194 00:18:09.850 ⇒ 00:18:12.689 Brian Pei: I’ll have to clean this up the same way. I clean
195 00:18:12.740 ⇒ 00:18:15.249 Brian Pei: quote unquote cleaned up shopify. But
196 00:18:16.390 ⇒ 00:18:19.819 Brian Pei: if it’s in Canada. Obviously, it’s not the 5 digits, but that’s fine.
197 00:18:20.060 ⇒ 00:18:22.809 Brian Pei: and the and the country code.
198 00:18:24.060 ⇒ 00:18:27.899 Brian Pei: there’s a couple less columns in Amazon that I can find.
199 00:18:29.038 ⇒ 00:18:33.891 Brian Pei: Then shopify shopify has more columns.
200 00:18:34.840 ⇒ 00:18:39.689 Brian Pei: so like, I still need to find out, like the actual discount code that they used
201 00:18:40.040 ⇒ 00:18:48.110 Brian Pei: refunds I couldn’t find yet. This is why it’s better that I’m saying this out loud now, because hopefully, by the time I show this to Aman I’ll find refunds.
202 00:18:48.230 ⇒ 00:18:51.160 Brian Pei: so I need to find refunds and add that here.
203 00:18:51.270 ⇒ 00:19:03.629 Brian Pei: So that’s why I said preliminary. There’s a couple more columns I need to find and add, but for the most part. You can still take a look at Amazon order now and do some preliminary analysis if you would like.
204 00:19:05.190 ⇒ 00:19:12.070 Brian Pei: But yeah, I spent most of my time doing this, and then adjusting the tables we presented.
205 00:19:12.733 ⇒ 00:19:18.269 Brian Pei: Tuesday. For Aman’s questions and for Pius’s additions.
206 00:19:18.950 ⇒ 00:19:24.389 Payas Parab: Question on this Amazon cause. The fulfillment is ultimately done by shopify. Right? So is there a
207 00:19:24.600 ⇒ 00:19:30.689 Payas Parab: a binding key towards I I believe the orders are fulfilled by shopify? Or do they, using fulfilled by Amazon.
208 00:19:32.560 ⇒ 00:19:34.109 Brian Pei: I thought they were fulfilled by Amazon. This.
209 00:19:34.110 ⇒ 00:19:36.100 Payas Parab: They are fulfilled by Amazon. Okay.
210 00:19:37.850 ⇒ 00:19:42.960 Brian Pei: that would be my guess. I didn’t know. I mean, we can ask as well, because the the Amazon
211 00:19:43.020 ⇒ 00:19:45.710 Brian Pei: tables have their own fulfillment.
212 00:19:45.710 ⇒ 00:19:47.000 Payas Parab: Okay, okay, perfect.
213 00:19:47.413 ⇒ 00:19:51.546 Brian Pei: So I think it’s fulfilled by Amazon. I think. Amazon.
214 00:19:52.520 ⇒ 00:20:00.389 Brian Pei: yeah, I guess, especially if it’s like a pro. If it’s Amazon prime specific, and they have their own engine. I don’t know why it would talk to shopify, but I.
215 00:20:00.390 ⇒ 00:20:03.109 Payas Parab: Yeah, yeah, you’re right, yeah.
216 00:20:04.630 ⇒ 00:20:09.709 Brian Pei: yeah, which is why, it’s important for me to spend the time
217 00:20:10.030 ⇒ 00:20:11.940 Brian Pei: to get
218 00:20:12.000 ⇒ 00:20:17.720 Brian Pei: the Amazon columns to match with shopify, so we can
219 00:20:17.860 ⇒ 00:20:26.569 Brian Pei: have a a universal orders table which will be what I’ll do for the rest of the week, so that hopefully, next time we meet with them on, and obviously.
220 00:20:26.660 ⇒ 00:20:33.110 Brian Pei: iteratively, I’ll I’ll sell or sell. I’ll send my progress over to you so we can take a look at it.
221 00:20:34.195 ⇒ 00:20:35.050 Brian Pei: Before
222 00:20:35.180 ⇒ 00:20:40.854 Brian Pei: hopefully, we get some sort of universal order dimension table that we can share.
223 00:20:41.330 ⇒ 00:20:44.679 Brian Pei: pending. You know your validation and analysis and all that stuff.
224 00:20:45.995 ⇒ 00:20:46.980 Brian Pei: But
225 00:20:47.030 ⇒ 00:20:49.865 Brian Pei: yeah, I’ve spent most of my time doing that.
226 00:20:50.520 ⇒ 00:20:52.680 Brian Pei: at the same time before
227 00:20:52.710 ⇒ 00:20:55.140 Brian Pei: the next client meeting.
228 00:20:55.968 ⇒ 00:21:02.330 Brian Pei: I should also have line item dimensions for shopify and Amazon.
229 00:21:03.080 ⇒ 00:21:05.750 Brian Pei: I think that’s my priority.
230 00:21:07.300 ⇒ 00:21:11.600 Brian Pei: so that’s that’s my update. I can throw it to whoever else.
231 00:21:13.040 ⇒ 00:21:15.520 Nicolas Sucari: Cool. I think if we
232 00:21:15.810 ⇒ 00:21:28.799 Nicolas Sucari: have these for Tuesday, then next week we can start working on implementing real with whichever table do we have. And so so that we can just start trying these sources and see how the dashboards looks.
233 00:21:28.850 ⇒ 00:21:36.509 Nicolas Sucari: Don’t worry. Then we need to change any of the sources just to show some of these data in in a real dashboard. What do you think.
234 00:21:37.875 ⇒ 00:21:38.180 Brian Pei: Yeah.
235 00:21:38.180 ⇒ 00:21:49.679 Nicolas Sucari: I mean, I I know I know they are not gonna be like final versions of the table yet, but we can then change the the tables so that we can give a man just a quick view of
236 00:21:49.690 ⇒ 00:21:51.940 Nicolas Sucari: of the real ui.
237 00:21:52.890 ⇒ 00:21:55.359 Brian Pei: Yeah, I need to meet.
238 00:21:55.690 ⇒ 00:21:59.230 Brian Pei: Maybe Monday. I’ll find time with Patrick to set up.
239 00:21:59.230 ⇒ 00:22:01.670 Nicolas Sucari: That. Let me know I can help you. Yeah.
240 00:22:02.336 ⇒ 00:22:03.003 Brian Pei: Yeah.
241 00:22:03.670 ⇒ 00:22:04.800 Nicolas Sucari: Can go with that.
242 00:22:04.800 ⇒ 00:22:05.120 Brian Pei: And.
243 00:22:05.120 ⇒ 00:22:06.979 Nicolas Sucari: Yeah, I’m trying to figure that out.
244 00:22:07.790 ⇒ 00:22:18.629 Payas Parab: Remind me, there’s like that, like the out of the box. Kind of like that out of the box. Kind of tool you can use e-commerce specific that you can like play around with the data right? I believe Robert showed me.
245 00:22:19.098 ⇒ 00:22:25.449 Payas Parab: Are there any other like front application layers we’re thinking about, because we also like, you know, we’ve used Meta base before
246 00:22:25.470 ⇒ 00:22:29.769 Payas Parab: heck stop tech like there’s a few others where we can start building. These. Are there any other
247 00:22:29.780 ⇒ 00:22:36.030 Payas Parab: like dashboard level, like visualization layer that you guys are planning to use? Or is everything going to be real?
248 00:22:37.230 ⇒ 00:22:46.579 Nicolas Sucari: No, we are planning to use real release for that data exploration for Aman or or you, or whoever wants to go and quickly access.
249 00:22:46.580 ⇒ 00:22:47.400 Payas Parab: It’s different.
250 00:22:47.400 ⇒ 00:22:53.270 Nicolas Sucari: Layers of the data. But if we then need like something specific, we can start thinking of other tools
251 00:22:53.420 ⇒ 00:22:55.220 Nicolas Sucari: and really has a.
252 00:22:55.220 ⇒ 00:23:01.959 Payas Parab: Is in really able to like, make a data set or dashboard with like a sequel. Query at all or no, is it purely
253 00:23:02.610 ⇒ 00:23:04.720 Payas Parab: like no code tool.
254 00:23:04.720 ⇒ 00:23:06.029 Nicolas Sucari: Yes, yes, you can.
255 00:23:06.030 ⇒ 00:23:06.360 Payas Parab: You can.
256 00:23:06.360 ⇒ 00:23:07.470 Nicolas Sucari: I mean, it’s
257 00:23:07.920 ⇒ 00:23:17.129 Nicolas Sucari: you can write your own queries and create that query into a dashboard if you want so it’s it’s all like, manage through the code real.
258 00:23:17.280 ⇒ 00:23:19.700 Nicolas Sucari: So, yeah, you can get anything.
259 00:23:19.700 ⇒ 00:23:20.000 Payas Parab: Okay.
260 00:23:20.000 ⇒ 00:23:23.200 Nicolas Sucari: And write some queries on that tables. Yeah.
261 00:23:23.200 ⇒ 00:23:23.560 Payas Parab: Yep.
262 00:23:23.560 ⇒ 00:23:43.190 Uttam Kumaran: Yeah, we actually haven’t made a decision. Pious on Bi tool, are we? We use real for a bunch of other clients? And it’s super easy to use with Dbt, so we’re like, if they haven’t made a decision, then that’s gonna be our like front runner. Basically, the one thing I like about is, we’ll at least get to have them to click around and see something, and then.
263 00:23:43.230 ⇒ 00:23:48.750 Uttam Kumaran: if he likes metabase or likes that he can make that decision, or if he likes real, then we’ll we’ll go with that. It’s.
264 00:23:49.046 ⇒ 00:23:56.459 Payas Parab: Like, I think, the real like the out of the box components of it, because when Robert demoed it for me, seem really compelling, because
265 00:23:56.490 ⇒ 00:24:01.260 Payas Parab: they don’t want to have to rely on like someone to like. Write, sequel right whatever, right anytime.
266 00:24:01.260 ⇒ 00:24:06.279 Uttam Kumaran: Or even like, do yeah, or even like, make modifications to dashboards and stuff like, I don’t think that’s
267 00:24:06.290 ⇒ 00:24:08.000 Uttam Kumaran: like where the juice is.
268 00:24:08.180 ⇒ 00:24:12.989 Uttam Kumaran: It’s like, can we get the tables in there with, like the metrics and dimensions, and then
269 00:24:13.010 ⇒ 00:24:29.870 Uttam Kumaran: have them something that they can quickly compare time periods, compare across dimensions like parameterize filters. And it’s super quick. That’s the biggest thing that it does. And it’s all as code. So yeah, you basically, you can run it locally on your machine. Change the SQL. Query to add a dimension, and then like.
270 00:24:30.410 ⇒ 00:24:32.959 Uttam Kumaran: push the query, push the Pr. And
271 00:24:34.100 ⇒ 00:24:34.500 Uttam Kumaran: pretty easy.
272 00:24:34.500 ⇒ 00:24:46.099 Payas Parab: They need. They need something that they can play around with, because they found amplitude to be like enough like able to like Justin was able to play around with it, do some small things in there easily. So I think we need some front end that’s like
273 00:24:46.140 ⇒ 00:24:51.149 Payas Parab: easily toggleable. But I think they’re also looking at adding, like basically a sequel
274 00:24:51.160 ⇒ 00:24:54.799 Payas Parab: analyst to their company to basically like help them.
275 00:24:54.800 ⇒ 00:24:55.260 Uttam Kumaran: Nice.
276 00:24:55.260 ⇒ 00:25:05.360 Payas Parab: Like ad hoc analyses and things like that. So I know the ad hoc analyses come out a lot. I haven’t seen real the real like Robert Demo, the out of the box thing. But like as far as like
277 00:25:05.994 ⇒ 00:25:09.959 Payas Parab: like, you know, like executive presentations of like data and things like that. I’ve seen
278 00:25:10.660 ⇒ 00:25:14.370 Payas Parab: really great work out of company. We used to use hacks at a startup. I was working at.
279 00:25:14.370 ⇒ 00:25:16.689 Uttam Kumaran: Yeah, hex is pretty good for like notebooks.
280 00:25:16.690 ⇒ 00:25:19.820 Payas Parab: Hex and what’s the other one mode so like.
281 00:25:19.820 ⇒ 00:25:20.530 Uttam Kumaran: Code, yeah.
282 00:25:20.530 ⇒ 00:25:30.539 Payas Parab: Yeah, I I just like, if if they have someone who can write scripts right and is going to like, Do ad hoc scripts for them. I think there’s a world in which we also set up another tool.
283 00:25:30.540 ⇒ 00:25:31.230 Uttam Kumaran: For sure.
284 00:25:31.230 ⇒ 00:25:34.890 Payas Parab: Should just be connecting to the Snowflake instance. If I’m correct, right.
285 00:25:34.890 ⇒ 00:25:35.730 Uttam Kumaran: Exactly. Yeah, like.
286 00:25:35.730 ⇒ 00:25:36.090 Payas Parab: Members.
287 00:25:36.090 ⇒ 00:25:44.340 Uttam Kumaran: You could run queries there and then just have text locally. Or again, it depends on their workflow. But that’s exactly it. Yeah.
288 00:25:44.340 ⇒ 00:25:44.850 Payas Parab: Okay.
289 00:25:44.850 ⇒ 00:25:50.549 Uttam Kumaran: Like again. They could probably run all those queries there and then, either visualize it in, excel, visualize it in sheets, or visualize it
290 00:25:50.710 ⇒ 00:25:59.820 Uttam Kumaran: in another. Whatever tool the nice thing about about real is that it hooks up, and it’s like refreshes daily and hooks right into the models that Brian creates with like
291 00:26:00.110 ⇒ 00:26:03.370 Uttam Kumaran: pretty much like very little work, additional work for him.
292 00:26:03.370 ⇒ 00:26:04.029 Payas Parab: Sure, sure.
293 00:26:04.030 ⇒ 00:26:07.460 Uttam Kumaran: Usually to do looker or something. It’s like a whole. Another person you need. So like.
294 00:26:07.460 ⇒ 00:26:08.090 Payas Parab: Yes, yes.
295 00:26:08.090 ⇒ 00:26:08.959 Uttam Kumaran: But we found out.
296 00:26:08.960 ⇒ 00:26:14.019 Payas Parab: Yeah, we wanna we wanna like we wanna put them in a good place like, set all that up for them. And then ultimately.
297 00:26:14.280 ⇒ 00:26:28.839 Payas Parab: they can hire someone to like run they they just are planning to have resourcing for that in the future. So I’m like we might as well start showing them what’s possible. But we can. We can, if real, has some of those capabilities right? Then we can do
298 00:26:28.930 ⇒ 00:26:36.090 Payas Parab: ad hoc analysis in there, if you can like quickly, run a script, build out a data set and then make it like interactive, really, easily.
299 00:26:36.577 ⇒ 00:26:41.300 Payas Parab: or like, visually clear and real. Then we can just roll with real. We’re fine with that.
300 00:26:46.170 ⇒ 00:26:47.659 Payas Parab: Okay, cool.
301 00:26:50.110 ⇒ 00:26:52.010 Nicolas Sucari: Okay, okay? So
302 00:26:52.020 ⇒ 00:26:58.199 Nicolas Sucari: I think next step is Brian to keep working on those Amazon tables. Try to get the old order
303 00:26:58.400 ⇒ 00:27:02.739 Nicolas Sucari: table from shopify and Amazon together to present on Tuesday.
304 00:27:03.166 ⇒ 00:27:07.750 Nicolas Sucari: and then next week, we can start looking into the
305 00:27:07.830 ⇒ 00:27:11.750 Nicolas Sucari: real integration and try to create those 1st views. Okay.
306 00:27:12.410 ⇒ 00:27:19.479 Payas Parab: Yup, and 1 1 other thing I wanted to just flag us the in the shopify table. So far, I know there’s a couple more that still have to be built.
307 00:27:19.530 ⇒ 00:27:25.520 Payas Parab: There is gonna be one that covers like cost, right or like fulfillment, and like cost of the orders.
308 00:27:27.100 ⇒ 00:27:27.680 Brian Pei: Oh!
309 00:27:27.680 ⇒ 00:27:28.950 Payas Parab: People that’s gonna be.
310 00:27:29.350 ⇒ 00:27:30.680 Brian Pei: In like our
311 00:27:30.880 ⇒ 00:27:32.990 Brian Pei: in the past, in our
312 00:27:33.120 ⇒ 00:27:46.060 Brian Pei: basic like core model development. If we don’t get a blueprint from the client we actually don’t have a separate table for that could you? Could you? But I mean we could. Could you describe.
313 00:27:46.340 ⇒ 00:27:55.130 Payas Parab: Yeah. So I mean, I can. It’s maybe it’s best to describe it like what we did at amplitude. So I can quickly share my screen and just show you guys the
314 00:27:55.160 ⇒ 00:28:03.920 Payas Parab: there was like there was like a table somewhere. Maybe it was like captured with the event. But there’s definitely some like shopify attribute. Let me
315 00:28:04.700 ⇒ 00:28:05.370 Payas Parab: wait.
316 00:28:05.470 ⇒ 00:28:06.680 Payas Parab: Share here.
317 00:28:11.010 ⇒ 00:28:12.780 Payas Parab: you guys are seeing amplitude.
318 00:28:15.338 ⇒ 00:28:16.370 Brian Pei: Yep, I’m seeing it.
319 00:28:16.370 ⇒ 00:28:17.010 Nicolas Sucari: Yes.
320 00:28:17.130 ⇒ 00:28:18.699 Payas Parab: Free. Okay? So then
321 00:28:18.910 ⇒ 00:28:38.128 Payas Parab: in here, we used to have these, like, you know, we’re trying to figure out basically like cost, like shipping costs, logistics, costs like what different components go into it right? And they’re trying to do basically an analysis. This was where we like realized, we needed the data warehouse and some type of scripting, because it was like super ratchet. How we’re doing this analysis.
322 00:28:38.610 ⇒ 00:28:44.690 Payas Parab: so in the cogs on an event which I’ll show you I’ve defined.
323 00:28:44.780 ⇒ 00:28:48.119 Payas Parab: In an event there used to be this like cost table.
324 00:28:50.260 ⇒ 00:29:00.700 Payas Parab: that had this like. I don’t know exactly where it’s housed, but I’m guessing it’s some type of shopify. If I go to edit metric. And you’re looking at this. There’s like this like table with each event
325 00:29:00.750 ⇒ 00:29:16.709 Payas Parab: where there was like cost. There’s like a cost property that was like defaulted from shopify that had like cogs. So it’s like cost dot cogs cost dot, and I know these are like event properties. But there’s probably some type of table in shopify that has this information.
326 00:29:16.920 ⇒ 00:29:18.029 Payas Parab: Is it? Cop?
327 00:29:18.030 ⇒ 00:29:24.349 Brian Pei: The the cost of them, like manufacturing the coffee in that, in that example.
328 00:29:24.350 ⇒ 00:29:25.040 Nicolas Sucari: Yeah.
329 00:29:25.510 ⇒ 00:29:28.760 Nicolas Sucari: I think it’s something they load load in when they create.
330 00:29:28.760 ⇒ 00:29:39.199 Uttam Kumaran: Yeah, usually on shopify. There’s cogs. Yeah. So you can check out for the for pool parts. How we did it. But cogs will be on every product. You’ll see that.
331 00:29:39.230 ⇒ 00:29:46.770 Uttam Kumaran: Let’s see. Wait! You’ll see other stuff. If it’s not filled out, then we may need to get it from something else like for pool parts. We get it from a bunch of other sources.
332 00:29:46.920 ⇒ 00:29:50.400 Uttam Kumaran: but usually you’ll see it from the platform itself.
333 00:29:50.856 ⇒ 00:30:03.329 Uttam Kumaran: so you can make you could quickly make like a cost like a product cost table. Or if you have a products table and you just add cost in there, it just may change over time. So you may have to. Yeah, I don’t know if we want to create a history or not. So.
334 00:30:03.520 ⇒ 00:30:09.420 Payas Parab: Yeah, th, this, this we may need to like, cause they wanna they wanna be able to like break. This was the biggest like
335 00:30:09.500 ⇒ 00:30:30.800 Payas Parab: part of the reason we’re pushing them to the data warehouse is like they want. There’s like packaging cost out packaging cost, estimated shipping. And I know Brian talked about. There’s another shipping, and then, like refunds will be pretty impactful, because they essentially want to see on a product or offer level right? Like what their profitability is on these right like, which of these are less profitable, more profitable?
336 00:30:31.043 ⇒ 00:30:50.270 Payas Parab: I made a deck analyzing the gross margin. So I’m I’m actually gonna share that with you guys as well just to get a sense of like, what type of like reporting they’re looking for but I think somehow we need to bring in these like cost. That is pretty critical that we bring in the cost components into. And I still have to go through all the tables that like I just haven’t had time, but
337 00:30:50.290 ⇒ 00:30:58.230 Payas Parab: that I’m sure I’ll find some of the stuff that I’ll flag is like. Oh, this is important. This is important. So I that exercise is still on me. I owe you guys that my bad.
338 00:30:58.440 ⇒ 00:30:59.839 Brian Pei: No, it’s all good.
339 00:31:00.460 ⇒ 00:31:01.380 Brian Pei: okay.
340 00:31:01.720 ⇒ 00:31:03.079 Brian Pei: yeah. I’ll just quickly
341 00:31:03.230 ⇒ 00:31:06.710 Brian Pei: going through all the product tables trying to find.
342 00:31:08.870 ⇒ 00:31:12.910 Brian Pei: okay, I I can. I’ll dig into
343 00:31:13.050 ⇒ 00:31:16.419 Brian Pei: cost of product and or cost of products variant
344 00:31:17.440 ⇒ 00:31:19.130 Brian Pei: into the orders table.
345 00:31:20.720 ⇒ 00:31:27.660 Brian Pei: and do you think it would just be one value like it’s not split up between like plastic and coffee grounds.
346 00:31:28.220 ⇒ 00:31:33.370 Payas Parab: No, it should be one value, it should be one aggregated like the final thing that shipped how much it cost.
347 00:31:33.610 ⇒ 00:31:34.200 Brian Pei: Okay. Cool.
348 00:31:34.200 ⇒ 00:31:34.800 Payas Parab: Yeah.
349 00:31:35.970 ⇒ 00:31:39.599 Brian Pei: Alright, yeah, Nico, can you just make sure that I
350 00:31:40.420 ⇒ 00:31:42.920 Brian Pei: get that before next meeting?
351 00:31:43.420 ⇒ 00:31:44.190 Nicolas Sucari: Hey! Here!
352 00:31:44.190 ⇒ 00:31:48.010 Brian Pei: I’ll take a look just one. Okay, anyway. But yeah, okay, got it.
353 00:31:48.550 ⇒ 00:31:54.180 Brian Pei: I will try to find that I’m only hesitating because I haven’t found it yet, and I will find it.
354 00:31:54.440 ⇒ 00:31:55.250 Payas Parab: Yeah. Alright.
355 00:31:55.250 ⇒ 00:31:56.069 Nicolas Sucari: Yeah, let’s.
356 00:31:56.610 ⇒ 00:31:57.140 Payas Parab: That one separate.
357 00:31:57.140 ⇒ 00:32:11.255 Nicolas Sucari: I think we should take a look. Yeah, in the product tables. Maybe it’s there because it’s it’s kinda in in shopify. I think it’s kind of like field for each of the product skews that we have loaded there. That’s how I’ve seen it before.
358 00:32:11.550 ⇒ 00:32:12.220 Brian Pei: It should be.
359 00:32:12.220 ⇒ 00:32:13.770 Nicolas Sucari: Don’t find any tables.
360 00:32:13.920 ⇒ 00:32:16.269 Nicolas Sucari: Yeah, it should be somewhere. Yeah, exactly
361 00:32:17.185 ⇒ 00:32:17.560 Nicolas Sucari: cool.
362 00:32:18.020 ⇒ 00:32:25.870 Nicolas Sucari: But yeah, if we find any difficulty trying to, yeah, find that value maybe pay us. I don’t know if you have any access to their shopify account.
363 00:32:26.340 ⇒ 00:32:26.870 Nicolas Sucari: and.
364 00:32:26.950 ⇒ 00:32:33.249 Payas Parab: I think Robert does I I don’t have the password to it, but I believe Robert has access, so I can.
365 00:32:34.300 ⇒ 00:32:45.390 Nicolas Sucari: Yeah, maybe let’s yeah, we’re gonna try to find that that values on the tables. And if not, we can ask for that access and try to figure it out. Where in shopify is that one? Okay.
366 00:32:45.670 ⇒ 00:32:46.460 Payas Parab: Sound. Good.
367 00:32:47.200 ⇒ 00:32:47.820 Payas Parab: Okay.
368 00:32:47.820 ⇒ 00:32:48.880 Brian Pei: I’ll let you know
369 00:32:49.330 ⇒ 00:32:50.359 Brian Pei: if I find it.
370 00:32:50.360 ⇒ 00:32:51.190 Nicolas Sucari: Excellent sir!
371 00:32:51.190 ⇒ 00:32:51.960 Brian Pei: I find it.
372 00:32:54.010 ⇒ 00:32:54.680 Payas Parab: Sounds, great.
373 00:32:54.680 ⇒ 00:32:55.300 Nicolas Sucari: Great.
374 00:32:55.950 ⇒ 00:32:59.749 Nicolas Sucari: Okay, okay, guys, let’s meet Monday and see
375 00:33:00.280 ⇒ 00:33:01.550 Nicolas Sucari: how things are. Okay.
376 00:33:01.800 ⇒ 00:33:02.610 Brian Pei: Sounds good.
377 00:33:02.920 ⇒ 00:33:03.900 Brian Pei: thanks, all.
378 00:33:04.490 ⇒ 00:33:05.820 Uttam Kumaran: Thanks, guys. Bye, night.