Meeting Title: Brainforge Data Standup Date: 2025-02-26 Meeting participants: Uttam Kumaran, Bo Yoon, Sahana Asokan, Awaish Kumar


WEBVTT

1 00:04:12.710 00:04:13.800 Bo Yoon: Hey, guys.

2 00:04:14.610 00:04:15.160 Uttam Kumaran: Hey!

3 00:04:15.850 00:04:16.510 Awaish Kumar: Hello!

4 00:04:22.657 00:04:29.319 Uttam Kumaran: Yeah, I guess, Beau, any questions on sort of modeling stuff. I saw you in a way, basically chat chatted through.

5 00:04:29.550 00:04:32.959 Uttam Kumaran: Is there any other questions about where anything lives that we want to talk about.

6 00:04:34.473 00:04:40.769 Bo Yoon: Yeah, I actually had a you. I guess we got the the data from Shippo.

7 00:04:42.239 00:04:49.879 Bo Yoon: Is that also updating the the order, details, table all the columns in there.

8 00:04:50.910 00:04:56.329 Uttam Kumaran: Yeah, I think. So. That’s that’s 2 pieces. So one, yeah, shipments is available. And if you go to dim shipments, you’ll see.

9 00:04:56.330 00:04:56.794 Bo Yoon: Yeah,

10 00:04:57.260 00:04:58.289 Uttam Kumaran: Stuff there.

11 00:04:58.490 00:05:04.709 Uttam Kumaran: I think, probably order details. It’s probably a specific con like, I think you probably need to talk to a wish about which fields

12 00:05:05.476 00:05:09.760 Uttam Kumaran: you need that way. We can confirm that it’s been brought over.

13 00:05:10.611 00:05:19.309 Uttam Kumaran: Order details is like a bunch of stuff. So it’s hard for us to be like order details. We’re splitting up into like 5 tables, because it has, like a hundred columns.

14 00:05:19.410 00:05:20.010 Uttam Kumaran: So.

15 00:05:20.010 00:05:20.740 Bo Yoon: Yeah.

16 00:05:20.740 00:05:28.119 Uttam Kumaran: I just need to know which column, I guess away. She needs to know which column you need, and it could probably point you to where to go, get it.

17 00:05:31.250 00:05:32.230 Bo Yoon: Okay.

18 00:05:32.720 00:05:33.740 Awaish Kumar: Yeah, but

19 00:05:34.820 00:05:40.407 Bo Yoon: But in the order details table it. It has the same columns as the

20 00:05:41.410 00:05:45.599 Bo Yoon: as a shipment table that you shared with me yesterday.

21 00:05:45.900 00:05:50.499 Bo Yoon: Yeah. Delivery to city delivery to zip code.

22 00:05:50.820 00:05:52.879 Bo Yoon: Those count as columns. So.

23 00:05:57.828 00:06:01.411 Uttam Kumaran: Yeah. But can you just let like, can you list them out.

24 00:06:01.710 00:06:03.310 Bo Yoon: Yeah, yeah, yeah, sure, yeah, yeah.

25 00:06:05.010 00:06:10.520 Awaish Kumar: I think what what Bo is saying that, like in their dashboard, they are still using order details, table

26 00:06:11.380 00:06:12.030 Awaish Kumar: and.

27 00:06:12.030 00:06:17.470 Uttam Kumaran: Yes, they are, but I wanted to move to our mark, but like I think he needs one or 2 columns.

28 00:06:17.600 00:06:21.199 Uttam Kumaran: I don’t know where it is in the new mart. So basically, I’m like, just write down which

29 00:06:22.810 00:06:26.149 Uttam Kumaran: which old ones you want, and we’ll figure out where where they live in the new mart.

30 00:06:27.120 00:06:32.699 Awaish Kumar: Yeah, we can add them in the new mark, but they they are also missing in the old mark, like

31 00:06:32.860 00:06:38.479 Awaish Kumar: one of the question from? Who is that? He needs marketing product, name in order details table

32 00:06:39.600 00:06:40.959 Awaish Kumar: in the old table.

33 00:06:41.280 00:06:43.689 Awaish Kumar: So which is not there. So you like.

34 00:06:44.470 00:06:49.400 Awaish Kumar: we need to like to support that. We need to update order details as well.

35 00:06:59.540 00:07:02.690 Uttam Kumaran: Oh, no, no, no, we shouldn’t be updating order details.

36 00:07:04.010 00:07:05.349 Awaish Kumar: Okay, so like.

37 00:07:05.870 00:07:06.699 Awaish Kumar: But I want.

38 00:07:06.700 00:07:08.819 Uttam Kumaran: Him to. He. He wants to move

39 00:07:09.090 00:07:15.460 Uttam Kumaran: his queries to the new mart, but he’s missing some fields that were previously in order. Details.

40 00:07:19.230 00:07:27.639 Awaish Kumar: Yeah, the the recent, like, like the last question I saw about missing of the standardized product.

41 00:07:29.830 00:07:33.070 Awaish Kumar: Product, name marketing product, marketing product. Name

42 00:07:33.240 00:07:44.390 Awaish Kumar: in the order, details, table. What he said was, it is available in the product sales summary which basically we created the table. And we added this marketing product name.

43 00:07:44.700 00:07:49.800 Awaish Kumar: But in the order details table, it’s not there, whereas in the old model it was not there.

44 00:07:52.520 00:07:58.549 Bo Yoon: Yeah, yeah, that. That’s that’s actually what I what I needed another column in the order details, table

45 00:07:59.830 00:08:01.530 Bo Yoon: marketing product name.

46 00:08:04.040 00:08:09.419 Bo Yoon: And I I thought that would be like kind of hard to do, since we’ll have to

47 00:08:10.850 00:08:13.910 Bo Yoon: sort of map those

48 00:08:14.540 00:08:24.749 Bo Yoon: 6 months, or something like that, because the names in the order. Details table are are kind of long. It it also have like bundles.

49 00:08:25.800 00:08:43.860 Bo Yoon: So to get a marketing product name in that table that yeah, I guess there’ll be something

50 00:08:45.380 00:08:47.310 Bo Yoon: not easy to do, I guess.

51 00:08:47.600 00:08:53.549 Uttam Kumaran: But leave that. Leave that to us, I guess. Just say just say what you need, and we’ll go figure it out.

52 00:08:53.990 00:08:58.699 Bo Yoon: Yeah, yeah, I mean, basically, that’s that’s what I need for in the orders detail table. So.

53 00:08:59.020 00:09:03.730 Uttam Kumaran: But then, can we like I want us to stop. Try to stop using that table like.

54 00:09:04.360 00:09:06.830 Bo Yoon: Stop using it, then.

55 00:09:07.510 00:09:12.480 Uttam Kumaran: But like, that’s what I mean is like, I want us to try to move towards using dim order or fact orders.

56 00:09:13.760 00:09:17.109 Bo Yoon: Back orders. I haven’t.

57 00:09:18.040 00:09:25.160 Uttam Kumaran: So I guess, like, that’s what I wish. Maybe you should meet with Bo, and sort of do like an onboarding onto our new March, because I want him to start to move

58 00:09:25.290 00:09:31.120 Uttam Kumaran: like I want to get rid of order. Details, you know, is like super effed up, like I want to get out of there.

59 00:09:31.590 00:09:33.980 Uttam Kumaran: So for new analyses.

60 00:09:34.220 00:09:40.389 Uttam Kumaran: I want us to use the march like, and we’re gonna be missing stuff. It’s okay. But just need to work on.

61 00:09:41.580 00:09:45.599 Uttam Kumaran: you know. That’s yeah.

62 00:09:46.750 00:09:48.166 Awaish Kumar: So in the new

63 00:09:50.040 00:09:52.239 Bo Yoon: Where is that table that we’re talking about? The.

64 00:09:52.240 00:09:57.319 Awaish Kumar: Yeah, in the new mart we have to like, we have a table called Fact Transactions.

65 00:09:57.790 00:09:59.340 Bo Yoon: Martin does.

66 00:10:00.300 00:10:06.590 Awaish Kumar: Like you can see it in the prod. DVD. Mart as well, and.

67 00:10:06.590 00:10:09.540 Bo Yoon: A little bit more. Fact.

68 00:10:09.800 00:10:10.930 Bo Yoon: 1st order.

69 00:10:10.930 00:10:19.810 Awaish Kumar: Track underscore transactions. So this is one of the table which has fields related to orders and

70 00:10:20.090 00:10:22.240 Awaish Kumar: but like it.

71 00:10:22.490 00:10:30.030 Awaish Kumar: it will have related to like order, id customer id things like product, id things like that, and then it will have some

72 00:10:30.380 00:10:33.890 Awaish Kumar: mayor, mayors like metrics, revenue, transaction, revenue.

73 00:10:34.140 00:10:45.299 Awaish Kumar: and stuff like that. But if you need more detail, like, okay, I need more detail about products, then we have to join it with the import products. And if you need more details about orders, then we need to join it with

74 00:10:45.510 00:10:46.870 Awaish Kumar: dim orders.

75 00:10:48.000 00:10:49.650 Awaish Kumar: Okay, okay, got it.

76 00:10:49.650 00:10:57.440 Awaish Kumar: Okay? Right? So if you think like, okay. Now, these joints are getting complicated. Then we can help create summary tables.

77 00:10:58.450 00:10:59.300 Bo Yoon: Hmm.

78 00:11:00.380 00:11:07.769 Bo Yoon: okay, yeah. I think I can work with this. If I have the the location columns and the marketing product

79 00:11:08.980 00:11:12.469 Bo Yoon: name, let let me let me double check.

80 00:11:13.780 00:11:16.189 Bo Yoon: I mean, I mean, let me take a look and.

81 00:11:16.510 00:11:17.510 Awaish Kumar: I’m good.

82 00:11:18.260 00:11:19.300 Bo Yoon: Hmm, yeah.

83 00:11:21.490 00:11:26.040 Awaish Kumar: But even if it’s not there, I will make sure, like I can edit.

84 00:11:26.400 00:11:28.030 Awaish Kumar: And now new mark. Yep.

85 00:11:28.580 00:11:28.933 Bo Yoon: Okay,

86 00:11:29.740 00:11:35.510 Bo Yoon: I will add what I need on the on the Google sheet that what Tom shared yesterday.

87 00:11:37.250 00:11:38.310 Bo Yoon: So

88 00:11:38.480 00:11:45.750 Bo Yoon: yeah, so so from now on. We’re gonna use this fact transactions table, I guess, rather than the order details. Table.

89 00:11:49.370 00:11:50.040 Uttam Kumaran: Yes.

90 00:11:50.580 00:11:51.320 Bo Yoon: Okay.

91 00:11:54.460 00:11:56.189 Uttam Kumaran: It may not have everything so.

92 00:11:56.710 00:12:02.000 Uttam Kumaran: But that’s the feedback we want. We want to like, I want to deprecate order details. Dude. It’s so bad.

93 00:12:02.580 00:12:06.720 Bo Yoon: Yeah, yeah, sure, okay.

94 00:12:16.700 00:12:18.939 Uttam Kumaran: Okay, cool any other items.

95 00:12:20.409 00:12:25.430 Uttam Kumaran: I wish I pushed your. I’m I’m I asked Sahana to look at your Pr. Did she leave any comments yet.

96 00:12:30.710 00:12:32.280 Uttam Kumaran: You’re on mute if you’re talking

97 00:12:35.760 00:12:36.900 Uttam Kumaran: okay, I don’t know if she.

98 00:12:36.900 00:12:37.930 Awaish Kumar: Yeah, I did.

99 00:12:37.990 00:12:42.070 Awaish Kumar: Yeah, yeah, I saw your message, but she didn’t left any comments yet.

100 00:12:43.100 00:12:47.169 Uttam Kumaran: Okay, okay. Sahan is here. Maybe we can ask her also.

101 00:12:48.880 00:12:49.600 Sahana Asokan: Hello!

102 00:12:50.800 00:12:52.608 Uttam Kumaran: Hey? We were just talking about

103 00:12:53.340 00:12:57.589 Uttam Kumaran: the Zendesk stuff. Not sure if you had a sec to review, or we can even review on this call.

104 00:12:57.910 00:13:05.350 Sahana Asokan: Yeah, let’s review on the call. I am on. Hold on another call. So if I drop off, that’s why. So.

105 00:13:05.350 00:13:06.030 Uttam Kumaran: Okay.

106 00:13:06.030 00:13:06.920 Sahana Asokan: Multitasking.

107 00:13:07.810 00:13:08.987 Uttam Kumaran: Okay, let me

108 00:13:09.710 00:13:18.469 Uttam Kumaran: let me pull it up. Yeah, I mean, we can. We can even push this as is. But I wanted to see if there’s like anything that’s like really glaringly missing

109 00:13:18.640 00:13:24.520 Uttam Kumaran: that we can catch it. Basically, yeah, we’re creating

110 00:13:24.940 00:13:32.640 Uttam Kumaran: sort of dim and fact tables. For for, like the core entities around Zendesk. So agents, brands, groups, orgs.

111 00:13:32.800 00:13:34.360 Uttam Kumaran: and then we have tickets.

112 00:13:34.943 00:13:38.819 Uttam Kumaran: And then some intermediate models to sort of calculate a few fields.

113 00:13:39.360 00:13:42.969 Uttam Kumaran: But probably the the most important thing to look at is like,

114 00:13:44.820 00:13:48.960 Uttam Kumaran: this the users table we’re bringing in

115 00:13:49.120 00:13:56.120 Uttam Kumaran: customers. I don’t know. Should we call this like customers instead? Maybe.

116 00:13:56.730 00:13:57.909 Sahana Asokan: Yeah, maybe.

117 00:13:57.910 00:14:00.989 Awaish Kumar: Actually, it’s not like it’s an intermediate table. So if.

118 00:14:01.300 00:14:04.040 Uttam Kumaran: Oh, yeah, this one like. But this is this is from

119 00:14:06.090 00:14:10.160 Uttam Kumaran: like users, I guess technically, are the customers right?

120 00:14:10.160 00:14:13.450 Awaish Kumar: Yeah, but like in the Dbt, we have this.

121 00:14:13.450 00:14:14.690 Uttam Kumaran: Oh, we do have another one.

122 00:14:14.690 00:14:18.419 Awaish Kumar: All across. We have the in the sales MoD. We have dim customers.

123 00:14:20.870 00:14:22.080 Uttam Kumaran: Yeah.

124 00:14:22.490 00:14:28.529 Sahana Asokan: Maybe we just change it to like something Zendesk specific, because I think dim users is kind of more of like a

125 00:14:28.760 00:14:30.260 Sahana Asokan: central.

126 00:14:30.490 00:14:32.590 Sahana Asokan: I don’t know like I agree.

127 00:14:32.590 00:14:33.660 Uttam Kumaran: Yeah, maybe.

128 00:14:33.770 00:14:38.980 Uttam Kumaran: Yeah. Maybe a way. Ask chat. Gpt. But I don’t know. Maybe dim, like Zendesk.

129 00:14:39.260 00:14:45.629 Uttam Kumaran: like, what is what is the what is on the opposite side of like the support staff, like their word for that like

130 00:14:46.280 00:14:50.860 Uttam Kumaran: client, them Zendesk customer, or something like that.

131 00:14:51.060 00:14:57.069 Sahana Asokan: Yeah, like dim Zendesk users, or like customers, is fine. I think.

132 00:14:58.800 00:15:03.050 Uttam Kumaran: I think, something to indicate that these aren’t the internal like this is an internal staff, basically

133 00:15:03.752 00:15:08.385 Uttam Kumaran: but otherwise I think this is fine.

134 00:15:14.400 00:15:21.659 Uttam Kumaran: okay? And then this is what’s, in fact, tickets. So you have all the ticket related information org requester, assignee submitter.

135 00:15:21.900 00:15:24.750 Uttam Kumaran: You have the types, tags ratings

136 00:15:25.250 00:15:31.420 Uttam Kumaran: when it was created. Updated. Wait times, resolution times reply. Times

137 00:15:32.390 00:15:35.440 Uttam Kumaran: feel like, you may have to just figure out what we’re missing.

138 00:15:35.710 00:15:37.739 Uttam Kumaran: Yeah. But this has a lot of stuff.

139 00:15:38.360 00:15:43.109 Sahana Asokan: More detail. But as long as we’re I’m assuming you’re just getting everything that we have right.

140 00:15:43.110 00:15:44.919 Uttam Kumaran: Yeah. For the most part.

141 00:15:45.240 00:15:50.740 Sahana Asokan: And we we’re gonna have to work with what we have regardless. But yeah, more in-depth look.

142 00:15:51.050 00:15:59.920 Uttam Kumaran: We could probably do some more calculated stuff like, for example, we are calculating the 1st resolution time in different fields. But like.

143 00:16:00.530 00:16:03.199 Uttam Kumaran: if you’re like, Hey, I need this thing. We’ll add it. So

144 00:16:03.610 00:16:07.100 Uttam Kumaran: I think this is a good 1st pass otherwise. But I guess.

145 00:16:07.100 00:16:10.290 Sahana Asokan: Pharmacy level metadata from Zendesk or no.

146 00:16:12.730 00:16:14.910 Uttam Kumaran: Oh, wait! Did you see anything about pharmacies?

147 00:16:15.500 00:16:17.620 Uttam Kumaran: Maybe it’s in ticket tags or something.

148 00:16:20.250 00:16:20.990 Awaish Kumar: Like.

149 00:16:22.410 00:16:27.220 Uttam Kumaran: Like. Would that be the agents associated with the pharmacy? Or how do you think that association happens.

150 00:16:27.640 00:16:28.790 Sahana Asokan: More about like

151 00:16:29.544 00:16:39.530 Sahana Asokan: like. For example, if a user is getting their order shipped to a pharmacy like, is there any tickets tied to that specific pharmacy? And how does that affect?

152 00:16:39.670 00:16:40.170 Sahana Asokan: Look for.

153 00:16:40.170 00:16:46.990 Uttam Kumaran: Well, like ideally, we would be able to join dim Zendesk customers.

154 00:16:47.270 00:16:54.869 Uttam Kumaran: You should be able to join this to dim customers and then join that to dim orders or fact orders basically.

155 00:16:55.290 00:17:00.949 Sahana Asokan: Do we have a transact like? Is there a transaction id associated with the ticket, or an agent.

156 00:17:01.247 00:17:03.330 Awaish Kumar: No, like not not in here like.

157 00:17:03.500 00:17:05.319 Awaish Kumar: That’s how we have to do is like

158 00:17:05.619 00:17:08.699 Awaish Kumar: for the ticket. We have a customer Id.

159 00:17:08.810 00:17:12.699 Awaish Kumar: And then with using the customer, id, we join it with with the.

160 00:17:13.200 00:17:15.310 Awaish Kumar: with the orders or transactions. Yeah.

161 00:17:16.180 00:17:22.899 Sahana Asokan: So, but I know I guess I was just confused, right? Because, like, when I’m like, if I’m like talking to customer service about a specific order.

162 00:17:23.579 00:17:27.780 Sahana Asokan: I would assume like order, Id, or there’s some kind of like what.

163 00:17:27.780 00:17:32.219 Uttam Kumaran: I think it’s gonna be. Yeah. Is there a tag in the Zendesk ticket about the order?

164 00:17:33.676 00:17:40.960 Awaish Kumar: There is like a field where where we have this bask user. Id, I can see if there is more

165 00:17:41.390 00:17:44.290 Awaish Kumar: anything related to order. Id. I can add that.

166 00:17:44.460 00:17:49.674 Sahana Asokan: Yeah, let’s check that, because I think that would be very helpful, because it’s about like.

167 00:17:50.170 00:18:08.820 Sahana Asokan: how long is each ticket taking to get resolved right. It’s not necessarily how long is something taking getting? It’s not about the customers over like overall tickets. It should be at the customer level, and the order level, preferably. So. Yeah, let me know what comes up for that.

168 00:18:09.960 00:18:16.899 Awaish Kumar: Okay, I I will have a look at it. If we have any basket, id or something to join it with, I can add it in the

169 00:18:17.530 00:18:23.290 Awaish Kumar: and in the ticket like effect tickets, or something like that.

170 00:18:23.670 00:18:31.300 Sahana Asokan: Okay, sounds good. Yeah. The only reason I’m asking. And this is only Zendesk. Right? This is this is not about the bask data. Right?

171 00:18:31.300 00:18:33.490 Uttam Kumaran: Yeah, this is just zendesk.

172 00:18:33.720 00:18:34.880 Sahana Asokan: Okay. Okay. Cool.

173 00:18:42.380 00:18:48.470 Uttam Kumaran: And then, yeah, I don’t know. Maybe there’s this. Maybe we should make a summary table, a waste where we do the where we have the

174 00:18:49.680 00:18:53.260 Uttam Kumaran: a join, or I don’t know like, or maybe we should consider as part of like

175 00:18:53.520 00:19:03.530 Uttam Kumaran: something else to show which customers have which tickets. But I guess if you have the join, then, Sahana, we have all the. We have all the dim fact tables. So you image maybe, like a couple of step, join.

176 00:19:03.530 00:19:04.030 Sahana Asokan: Yeah, that’s.

177 00:19:04.030 00:19:10.399 Uttam Kumaran: But I I’m kind of like, go for it. And then, if it’s like complicated, we’ll then build a summary table later. That’s okay.

178 00:19:10.840 00:19:27.650 Sahana Asokan: Yeah, yeah, that’s fine. I don’t think you guys need to build that. Now, let’s see if that those joins happen a lot. If they happen a lot. Then there probably is a used case for a unified table, but it also depends on the amount of data like, if it’s not that much, we can easily noodle it together. So yeah.

179 00:19:29.410 00:19:34.579 Uttam Kumaran: Okay, cool. Then I think we’re good on this. Yeah. Anything else.

180 00:19:34.580 00:19:34.900 Sahana Asokan: That’s.

181 00:19:34.900 00:19:35.510 Uttam Kumaran: Yeah.

182 00:19:35.790 00:19:41.329 Sahana Asokan: Thoroughly today. We can just push. I mean, I would say we could just push this through.

183 00:19:41.550 00:19:43.719 Uttam Kumaran: Okay? Because sort of like.

184 00:19:43.830 00:19:55.189 Uttam Kumaran: I feel like, it’s pretty good apart from, like, yeah, I just want to check a wish. If there’s a user id. Let’s get it somewhere. Let there’s an order. Id. Let’s get it somewhere in there, and I’ll approve. And let’s just push it through

185 00:19:55.370 00:20:02.900 Uttam Kumaran: that way you can actually see like what it looks like. And then there, we’re gonna iterate like small things. So that’s fine.

186 00:20:03.100 00:20:11.459 Sahana Asokan: Okay, yeah. Sounds good. I think the Zendesk one. This should be pretty straightforward. It’s the Basque stuff that I’m the Basque and ship of stuff that I’m a little more.

187 00:20:12.110 00:20:14.929 Uttam Kumaran: Yeah. So we actually do have dim shipments now.

188 00:20:15.080 00:20:21.089 Uttam Kumaran: which is pulling from ship. Oh, although it’s pulling from like a kind of like a janky ship. Oh, source which I’m trying to fix.

189 00:20:21.300 00:20:24.009 Uttam Kumaran: But there is a dim

190 00:20:24.888 00:20:28.330 Uttam Kumaran: there is a dim shipments which has

191 00:20:29.630 00:20:32.270 Uttam Kumaran: all the necessary shipment related information.

192 00:20:32.540 00:20:33.270 Sahana Asokan: And is there

193 00:20:33.270 00:20:40.909 Sahana Asokan: specific field called like for status of a shipment like when it was ordered versus when it was actually when the order.

194 00:20:40.910 00:20:46.920 Uttam Kumaran: Yeah, we do have all the dates we do have, like the sent to pharmacy, date the delivery status. So.

195 00:20:47.500 00:20:49.769 Uttam Kumaran: and again, we’ve we’ve taken

196 00:20:50.330 00:20:55.259 Uttam Kumaran: some of these from what were the previous logic was so at minimum we’ll be replicating what exists already.

197 00:20:55.849 00:21:16.989 Uttam Kumaran: But again, I think, even for Bo I mentioned, just like poke at this and tell me what else is needed. We’re gonna we’re gonna get a better ship. Oh, source. So we should have a couple more better information, but feel like it’s this is pretty good, and at least you can now again join this to dim order, to dim customer. So in. You’ll now see all of these tables available.

198 00:21:17.460 00:21:34.150 Sahana Asokan: Okay, I will look into that. Yeah, I think the for if you go back to the last screen, the one thing I wanna see here, too, or I’m hoping to see for shipments is it’s not just like when I think about the user’s journey. It’s yeah, like one half like the shipment journey is, you know, when

199 00:21:34.160 00:22:00.419 Sahana Asokan: it was shipped to the customer, like when it was delivered, when it was shipped to pharmacy, etc. But I’m trying to also see holistically like the entire picture, right? So it’s like from when the order was placed, when the order was sent, and then when, like the ship like from when the shipment information was was received from like the shipper side, like, I think I kind of want all of that. I don’t know how we’re gonna do that. But that’s kind of what I was hoping for. Because

200 00:22:00.420 00:22:11.839 Sahana Asokan: if I ask you like the business question right? Like, okay, how many hours, or how many days did it take from when the order was placed to when it was shipped? That is where I kind of need that

201 00:22:12.200 00:22:16.560 Sahana Asokan: like that early part of that journey. Does that make sense.

202 00:22:18.430 00:22:19.727 Uttam Kumaran: That makes sense.

203 00:22:20.160 00:22:29.519 Awaish Kumar: We have, like ship ship date and a delivery status date. I think if we subtract both, we get the time it took to get delivered.

204 00:22:29.810 00:22:56.869 Sahana Asokan: Yeah, we could probably get in. I mean, the other workaround is we can just get in when the order was actually placed. From like orders. I guess I’m just curious like, do we have more statuses around like order, placement like order, place, order, confirmation, order, successful, just like just to account for like, for example, like. If our payment was not successful, then that order is not confirmed, but if the payment was successful, then the order is confirmed. So I I wanna see all of that as well.

205 00:23:02.230 00:23:04.019 Uttam Kumaran: I guess I wish I’ll leave that to you.

206 00:23:06.548 00:23:08.341 Awaish Kumar: Right like

207 00:23:09.290 00:23:18.409 Sahana Asokan: It’s like. And I don’t know if that actually comes from shipment data. That’s the that’s what I would like to call out here. I’m just calling out like the overall like, question.

208 00:23:18.410 00:23:20.319 Sahana Asokan: yeah, are probably going to be asked.

209 00:23:20.320 00:23:21.460 Awaish Kumar: You know, like

210 00:23:22.070 00:23:27.409 Awaish Kumar: the what we wanted to create here is that it’s like for an order. We have a single row

211 00:23:27.530 00:23:37.119 Awaish Kumar: where we can take tell like it’s a ship date when it was shipped and when it went to the pharmacy, and then when when it went to the

212 00:23:37.430 00:23:40.230 Awaish Kumar: delivery status date. So you have all the details.

213 00:23:40.230 00:23:41.100 Sahana Asokan: I understand.

214 00:23:41.530 00:23:50.979 Awaish Kumar: But if we need like as you as I can like, if I understand correctly, if you wanted multiple rows for a single order

215 00:23:51.130 00:23:53.359 Awaish Kumar: like for every single order

216 00:23:54.168 00:24:02.500 Awaish Kumar: we have our single row when the order was placed, and then we have another row for the same order. When the

217 00:24:02.610 00:24:06.650 Awaish Kumar: order was maybe shipped, or something like that, and we have few more fields.

218 00:24:06.650 00:24:10.699 Uttam Kumaran: We do have a dip. Yeah, we do have dip, we? Yeah, go ahead.

219 00:24:11.150 00:24:14.599 Awaish Kumar: We have in the bask order shipped like we have this.

220 00:24:14.920 00:24:20.010 Awaish Kumar: like, I think, order updates, or something like that where we have these multiple rows

221 00:24:20.210 00:24:32.690 Awaish Kumar: for a single order like which which is telling the journey of the order. But we then we need to know, like what exactly what columns you are looking for, because there are lots of fields, and for a single order there are lots of

222 00:24:32.880 00:24:34.440 Awaish Kumar: rose, so.

223 00:24:34.610 00:24:48.699 Sahana Asokan: Understand that I understand that it’s like I don’t like. I don’t actually know if these fields exist right like it might even have to be us, creating calculated fields to define. Like, okay, an order is confirmed. If an order is placed.

224 00:24:49.070 00:24:53.290 Sahana Asokan: the payment is confirmed, and the order is shipped. Do you see what I’m saying? Like.

225 00:24:53.290 00:24:53.620 Uttam Kumaran: Yeah.

226 00:24:53.620 00:24:55.839 Sahana Asokan: A little bit more granularity.

227 00:24:56.680 00:25:05.509 Uttam Kumaran: Can we map this out? I those are one thing I wanted to do with Eden, and I’m doing it for another client is like, I want to map the order journey because

228 00:25:06.070 00:25:15.689 Uttam Kumaran: I want to see visually these steps. It’s very. It’s been extremely hard for me to even just like to think about. There’s payments. Then there’s there’s basically like orders, payments.

229 00:25:16.250 00:25:23.489 Uttam Kumaran: Trans like, I guess payments and transactions are the same. There’s shipments. There’s deliveries like I want to just maybe see a visual

230 00:25:23.840 00:25:26.620 Uttam Kumaran: of it. So I think that would. That would probably help a little bit.

231 00:25:26.940 00:25:28.200 Sahana Asokan: Yeah, no, I agree. I think.

232 00:25:28.200 00:25:28.580 Uttam Kumaran: Yeah, yeah.

233 00:25:28.580 00:25:35.890 Sahana Asokan: They’ll probably have to set up some time with someone there and side, just because, honestly, they haven’t given me a straight up answer.

234 00:25:35.890 00:25:40.639 Uttam Kumaran: Okay, let me let me take that on, and I’ll I’ll take on this sort of like

235 00:25:41.050 00:25:48.000 Uttam Kumaran: shipments versus deliveries versus that, and and sort of get us together to make to come to like what fuels we need.

236 00:25:48.000 00:25:49.320 Sahana Asokan: Awesome. Thank you.

237 00:25:57.700 00:25:58.460 Sahana Asokan: Okay, cool.

238 00:25:59.730 00:26:06.460 Uttam Kumaran: Yeah, I think that’s it. My only other suggestion is, if you are building anything new, please please try to use the new

239 00:26:07.750 00:26:10.920 Uttam Kumaran: sales Mart and the new

240 00:26:11.491 00:26:23.049 Uttam Kumaran: marketing Mart and the new Zendesk Mart, that’s coming. We are. Gonna try and deprecate all this old shit basically, as soon as we can, so that would be helpful.

241 00:26:23.460 00:26:26.940 Sahana Asokan: Okay, yeah, sounds good. I’ll probably start playing around with it. Maybe today.

242 00:26:27.450 00:26:28.040 Uttam Kumaran: Okay.

243 00:26:28.580 00:26:32.569 Bo Yoon: So so use all the all the V 2 folders.

244 00:26:32.570 00:26:33.600 Uttam Kumaran: Yes, please.

245 00:26:33.750 00:26:34.859 Bo Yoon: Okay, got it?

246 00:26:35.480 00:26:41.750 Uttam Kumaran: Yeah, okay, thanks, guys, I appreciate the time talk soon.

247 00:26:42.280 00:26:43.309 Bo Yoon: Yeah, thank, you.