Meeting Title: Stella-Source-Weekly-Data-Meeting Date: 2024-05-29 Meeting participants: Nick Baker, Robert Tseng, Nicolas Sucari, Uttam Kumaran
WEBVTT
1 00:00:18.490 ⇒ 00:00:19.365 Uttam Kumaran: A.
2 00:00:21.330 ⇒ 00:00:22.100 Nicolas Sucari: Hate them.
3 00:00:49.580 ⇒ 00:00:50.320 Robert Tseng: You guys.
4 00:00:52.000 ⇒ 00:00:52.860 Nicolas Sucari: Hi Robert!
5 00:00:53.510 ⇒ 00:00:54.060 Robert Tseng: Hey? Nico.
6 00:00:54.060 ⇒ 00:00:54.570 Uttam Kumaran: A.
7 00:00:54.570 ⇒ 00:00:55.600 Robert Tseng: Good to meet you.
8 00:00:56.680 ⇒ 00:00:57.949 Nicolas Sucari: Yeah, nice to meet you.
9 00:01:00.387 ⇒ 00:01:01.700 Uttam Kumaran: Cool. It’s just
10 00:01:02.240 ⇒ 00:01:04.650 Uttam Kumaran: wait for Nick.
11 00:02:08.729 ⇒ 00:02:11.389 Uttam Kumaran: Okay, maybe we
12 00:02:12.300 ⇒ 00:02:28.660 Uttam Kumaran: get started. I message, so we’re getting a bit organized on our end. Sorry, Nico. Thunder. But we’re kind of setting up
13 00:02:28.660 ⇒ 00:02:45.520 Uttam Kumaran: like some notion pages for every single one of our clients, basically with like with like links and where everything is like access to like docs and stuff like that. So we should have something over and off, of course, like meeting notes. So we should have something over to you on that
14 00:02:45.540 ⇒ 00:02:54.940 Uttam Kumaran: soon. I’m basically re reading notes from that notion right now. So kind of the things we wanted to go through are
15 00:02:55.217 ⇒ 00:03:01.360 Uttam Kumaran: for on my side are really like 5 tran and azure setup. So on the 5 tran side I know we turned off
16 00:03:01.440 ⇒ 00:03:09.620 Uttam Kumaran: the full story connector and so I think that that’s honestly, was the big driver of a lot of
17 00:03:10.948 ⇒ 00:03:15.820 Uttam Kumaran: spend. So I think we should be okay for, but I know we have
18 00:03:15.830 ⇒ 00:03:18.190 Uttam Kumaran: the trial until
19 00:03:18.370 ⇒ 00:03:19.550 Uttam Kumaran: June
20 00:03:19.700 ⇒ 00:03:22.560 Uttam Kumaran: 6 or so. But and I know we just added
21 00:03:22.590 ⇒ 00:03:26.659 Uttam Kumaran: the database in today, so we’ll have to wait a little bit to see like what we end up
22 00:03:26.700 ⇒ 00:03:35.590 Uttam Kumaran: at. Spend wise if we end up at 1,000 to give you a sense of like what the cut offs are. If we end up at 1,000 a month.
23 00:03:35.690 ⇒ 00:03:40.050 Uttam Kumaran: it’s worth us going to annual because we’ll get
24 00:03:40.140 ⇒ 00:03:42.900 Uttam Kumaran: we’ll get like 15% discount
25 00:03:42.930 ⇒ 00:03:44.163 Uttam Kumaran: on that
26 00:03:45.100 ⇒ 00:03:46.500 Uttam Kumaran: potentially even more.
27 00:03:46.540 ⇒ 00:03:47.550 Uttam Kumaran: So
28 00:03:47.570 ⇒ 00:03:51.237 Uttam Kumaran: that’s 1 thing. So we’ll kind of have to see where we land.
29 00:03:51.570 ⇒ 00:03:59.720 Uttam Kumaran: but I don’t think any other updates on the 5 trans. Side on the azure side. I’m literally texting with the
30 00:03:59.800 ⇒ 00:04:02.880 Uttam Kumaran: A Hub snowflake rep. They’re like having trouble finding
31 00:04:03.070 ⇒ 00:04:04.969 Uttam Kumaran: the account. And I’m like.
32 00:04:06.060 ⇒ 00:04:13.319 Uttam Kumaran: I’m really like what the fuck. I don’t know what the fuck that that means, like I was like I could add you to the account
33 00:04:13.510 ⇒ 00:04:17.340 Uttam Kumaran: like I don’t know. He’s like we’re having. We’re still trying to track down the account. I was like
34 00:04:17.640 ⇒ 00:04:24.405 Uttam Kumaran: what. So I sent him like a bunch of stuff
35 00:04:25.130 ⇒ 00:04:28.509 Uttam Kumaran: and he basically was like, I just need to flip a switch. Basically.
36 00:04:28.650 ⇒ 00:04:50.789 Uttam Kumaran: it’s this account rep that I’ve been working on. I’ve been working with. And so it’s nice, because I can literally just call him on the phone. And I called him yesterday, and he was like I should have it done tomorrow. So looks like he probably just started on it. Today. He’s in Denver. So ideally, we could turn that on and basically finish up the private link stuff. The other thing I found out on the Snowflake side
37 00:04:50.800 ⇒ 00:04:51.910 Uttam Kumaran: is
38 00:04:52.517 ⇒ 00:05:05.690 Uttam Kumaran: he called me. It was like another thing for you to notice if you sign an annual contract with. So for Snowflake as well, that’s like a minimum of 12 K. He can get us an additional 2 K
39 00:05:05.710 ⇒ 00:05:07.420 Uttam Kumaran: in credit
40 00:05:07.430 ⇒ 00:05:17.310 Uttam Kumaran: which brings the total thing down to 10 k. Per year, he said. He told me it was like azure is just giving us money for anybody who is like
41 00:05:17.650 ⇒ 00:05:21.479 Uttam Kumaran: using Snowflake with azure workflows, and as a new customer.
42 00:05:23.110 ⇒ 00:05:32.110 Uttam Kumaran: so he was like, we just have a pool of credits that we can use for that. And you guys will apply just I just pretty much have to.
43 00:05:33.260 ⇒ 00:05:35.737 Uttam Kumaran: I just pretty much have to.
44 00:05:36.440 ⇒ 00:05:39.999 Uttam Kumaran: apply that. So hopefully, we have some additional discounts there.
45 00:05:40.760 ⇒ 00:05:41.500 Robert Tseng: Got it.
46 00:05:42.120 ⇒ 00:05:49.250 Robert Tseng: Do you think we’re gonna I mean, I don’t know somebody check. I don’t. I don’t even. Well, yeah. Maybe once we add all the data, and we’ll hit one KA month. But
47 00:05:50.000 ⇒ 00:06:08.176 Robert Tseng: I I mean, I don’t know. I think I I had told them that storage was cheap. You know, the the connectors was going to be the the main driver of the cost. Now that we turn full story off, I’m gonna assume that, like the amount of data that’s coming in without full story is gonna drop by like 50. So
48 00:06:08.730 ⇒ 00:06:18.980 Robert Tseng: yeah, I guess we’ll see how things shake out in the next week. But but yeah, I wonder how where I the 5 tran, I’m sure will. Yeah, I think annual will probably make will make sense. And then.
49 00:06:19.220 ⇒ 00:06:23.470 Robert Tseng: yeah, I wonder where we’ll we’ll land on stuff like, I don’t really have a good sense of that right now.
50 00:06:23.650 ⇒ 00:06:26.010 Uttam Kumaran: Okay, okay, great.
51 00:06:26.950 ⇒ 00:06:29.249 Uttam Kumaran: those are the big updates. Yeah.
52 00:06:29.250 ⇒ 00:06:43.949 Robert Tseng: Sorry. One more thing. So yeah, with with the azure so we have 2 like SQL. Server dB’s that they’ve connected, and I I don’t know if you caught this from Ryan, but they’re migrating to
53 00:06:44.540 ⇒ 00:06:47.940 Robert Tseng: a what do they call it?
54 00:06:48.240 ⇒ 00:07:02.079 Robert Tseng: Pretty much like another? dB, like. I don’t really understand what the heck they’re doing. But yeah, it’s like, yeah, they’re transferring to azure SQL server. So then we’ll need to recreate the connectors for the new dB,
55 00:07:02.100 ⇒ 00:07:06.749 Robert Tseng: so I don’t know what I mean to me. That just sounds like we just connected
56 00:07:06.820 ⇒ 00:07:11.949 Robert Tseng: 2. And then we’re gonna turn those 2 off and then connect you more like I don’t really understand.
57 00:07:12.220 ⇒ 00:07:18.529 Uttam Kumaran: It’s probably gonna be. It’s probably gonna be like. Once they migrate, we will turn those on in parallel, and then.
58 00:07:18.530 ⇒ 00:07:18.850 Robert Tseng: Yeah.
59 00:07:18.850 ⇒ 00:07:27.711 Uttam Kumaran: We will have 2, and then we’ll transition. And I think whatever they’re doing, just loop, loop us in and we’ll handle what we need to do.
60 00:07:28.040 ⇒ 00:07:28.400 Robert Tseng: Yeah, I.
61 00:07:28.400 ⇒ 00:07:34.729 Uttam Kumaran: Ideally. If there, if if that’s if that’s a Ryan from their side owning it ideally, we just have a little bit of a heads up.
62 00:07:34.910 ⇒ 00:07:38.670 Uttam Kumaran: or we just have a working session with them and can make sure that happens. Nothing.
63 00:07:38.670 ⇒ 00:07:44.622 Robert Tseng: Yeah, Ryan Ryan seems to be the only one that really knows, like, what’s going on on on this. So
64 00:07:45.250 ⇒ 00:07:58.309 Robert Tseng: yeah, so that exactly. So is that the blob? The blob stuff is what we’re hoping the private network stuff is gonna resolve. Right? And then, yeah. So I think that’s that’s kind of what we’re
65 00:07:58.420 ⇒ 00:07:59.250 Robert Tseng: at.
66 00:08:00.080 ⇒ 00:08:00.625 Uttam Kumaran: Okay.
67 00:08:01.400 ⇒ 00:08:02.550 Uttam Kumaran: okay, yeah, sign in.
68 00:08:02.550 ⇒ 00:08:03.560 Robert Tseng: Using bunch of sort.
69 00:08:03.560 ⇒ 00:08:13.260 Uttam Kumaran: No, no, no, that’s it’s it’s just this is what happened. So it’s like, that’s why I was more like even when we were in the planning process. It’s like
70 00:08:13.750 ⇒ 00:08:25.254 Uttam Kumaran: we could. You just don’t know. You don’t know. And I was talking to Nico about this here yesterday. So it’s like. It’s just what happened. So we roll with the punches. I mean I was. I was happy to meet everybody, and as you mentioned, it seems like they’re
71 00:08:28.540 ⇒ 00:08:33.499 Uttam Kumaran: like, it. Seems like everybody’s nice and willing to work with us. So yeah.
72 00:08:34.280 ⇒ 00:08:43.060 Robert Tseng: Yeah, I’ll give some updates on, like how the deliverable has changed. With with the with the renewal. I we’ve extended for another 3 months with them. So
73 00:08:43.921 ⇒ 00:08:52.030 Robert Tseng: yeah, hopefully, that gives us more like time to deliver on this. But we we can address that after whatever else you have in our agenda.
74 00:08:52.500 ⇒ 00:08:55.491 Uttam Kumaran: Okay, I just wanted to.
75 00:08:56.627 ⇒ 00:08:59.552 Uttam Kumaran: I just wanted to talk about
76 00:09:02.290 ⇒ 00:09:12.604 Uttam Kumaran: see anything on the Zendesk side. So I know I message, Nick. Let me just see if he’s I’ll just send him a text, see if he’s available.
77 00:09:15.250 ⇒ 00:09:22.260 Nicolas Sucari: Oh, so Nick just answered, a couple of minutes ago that in slack he’s stuck in our meeting. Yeah.
78 00:09:22.770 ⇒ 00:09:23.380 Uttam Kumaran: Okay.
79 00:09:23.960 ⇒ 00:09:24.620 Robert Tseng: Okay.
80 00:09:29.970 ⇒ 00:09:31.310 Uttam Kumaran: Okay, then we can just.
81 00:09:31.460 ⇒ 00:09:37.793 Uttam Kumaran: I guess, like, let me so talk. Let’s talk about the modeling stuff. I’ve been following a little bit. But
82 00:09:38.460 ⇒ 00:09:46.469 Uttam Kumaran: I know he’s working with you on like some of the specific modeling things, I guess. Give me a sense of like how it’s going overall.
83 00:09:46.470 ⇒ 00:09:52.210 Robert Tseng: Yeah, maybe it’d be best if I could just share you what I what I shared the client? So maybe I’ll I’ll
84 00:09:53.550 ⇒ 00:09:55.308 Robert Tseng: I’ll I’ll sure be one
85 00:10:00.540 ⇒ 00:10:04.330 Robert Tseng: Oh, give me a second to pull up multiple links.
86 00:10:22.480 ⇒ 00:10:26.710 Robert Tseng: okay, sharing my screen now.
87 00:10:27.980 ⇒ 00:10:36.878 Robert Tseng: Yeah. So on the right. I don’t know if Nico seen this. But this is basically our project, Doc. I see there’s few people in it. I don’t know who these are. But
88 00:10:37.560 ⇒ 00:10:39.690 Robert Tseng: yeah, this is the
89 00:10:39.770 ⇒ 00:10:41.409 Robert Tseng: the scope that we
90 00:10:41.470 ⇒ 00:10:50.359 Robert Tseng: approved on April 4th to go and execute on. Obviously things have changed. Then a bit more complex, and we’re more or less behind schedule at this point.
91 00:10:50.671 ⇒ 00:11:14.570 Robert Tseng: On like getting some of these dashboards out. So yeah, we have the implementation set up like clear on that dashboard stuff. It’s pretty much like a 3 part dashboard. There was an out account management piece. I can reshare the mock ups if you guys wanted to see what that was supposed to look like. We’ve kind of sunset this at this point, what we realized was the data that we actually need to pull in from here.
92 00:11:15.038 ⇒ 00:11:21.910 Robert Tseng: Like, it’s moved. Since the start of our engagement, we were expecting netsuite and production data to be enough to build this out.
93 00:11:22.030 ⇒ 00:11:35.429 Robert Tseng: Turns out they’ve moved off next week. They’ve switched on Maxio, and they use Hubspot. So we don’t have Maxio and Hubspot in in Snowflake right now, and so we we can’t. We can’t deliver this right now. So we’ve we’ve pushed that off
94 00:11:36.180 ⇒ 00:11:42.460 Robert Tseng: on this side with full story, and just wanting to understand. I think this was more just like
95 00:11:42.730 ⇒ 00:11:44.570 Robert Tseng: operationally like.
96 00:11:45.027 ⇒ 00:12:06.889 Robert Tseng: like they had like this customer health score. And wanting to. Yeah, I think this this wasn’t really in a place. Well, we we turned on full story. Turns out we don’t want to be paying $1,000 a month for full story. If we’re only using 2 metrics, which is number of dead clicks and like active time and platform, there’s other ways to back into that.
97 00:12:06.890 ⇒ 00:12:24.680 Robert Tseng: And I think it was good for the team for me to show their team and be like full story is just a qualitative tool whatever you’re trying to get out of the on the quantitative side, it’s not worth what we’re paying for it. So I think that’s fine. But we basically have folded this part of the dashboard as well.
98 00:12:24.740 ⇒ 00:12:38.430 Robert Tseng: So all we were left with was the Zendesk. And it’s like, Okay, these are all pretty basic things that we could capture in inside us, using the modeling that I guess, like Nick, Nick set up but obviously, as you
99 00:12:38.779 ⇒ 00:12:48.689 Robert Tseng: yeah, I think, what? As I was recreating like what they had before, which was just this really rudimentary power. Vi. Sorry can’t really zoom in more. It’s just a screenshot
100 00:12:49.061 ⇒ 00:12:54.179 Robert Tseng: but it’s basically like a, you know, tickets broken out by company. And then, like.
101 00:12:54.360 ⇒ 00:12:56.839 Robert Tseng: like, take a satisfaction rating. Yeah.
102 00:12:56.880 ⇒ 00:13:07.900 Robert Tseng: I’ve like redesigned. It simplified it to something along these lines. So this was like the 1st v 1 i put out to them. It’s like number of new tickets, open tickets. Medium. 1st reply time.
103 00:13:07.950 ⇒ 00:13:18.030 Robert Tseng: and then just like some time based charting around here on like what their ticket volume over time looks like by status, and then also like how their ratings have fluctuated
104 00:13:18.535 ⇒ 00:13:42.679 Robert Tseng: and then I also cut down one of Nick’s big tables into like a summary table, with pretty much every other metric that I feel like is relevant to business questions that I’ve heard from them before. So the hope is like they. The client, would take this table, review it and see, is there anything else we want to pull out and turn into a chart. And so the feedback I got from them was like, Hey.
105 00:13:42.680 ⇒ 00:13:51.230 Robert Tseng: we want to break out by ticket tag as well. So this was one of the modeling requests I gave to Nick. Is basically saying like, Hey, like.
106 00:13:51.400 ⇒ 00:13:57.209 Robert Tseng: well, I mean, I could do this in sequel. And just like, but yeah, I think just knowing where that happens in the workflow.
107 00:13:57.210 ⇒ 00:13:57.540 Uttam Kumaran: Yeah.
108 00:13:57.540 ⇒ 00:14:03.469 Robert Tseng: It seems like we’re going to do something else in Dbt to spin this off into like a ticket broken out by.
109 00:14:03.640 ⇒ 00:14:05.499 Robert Tseng: well, yeah, just like number of
110 00:14:05.630 ⇒ 00:14:09.484 Robert Tseng: number of tickets broken up by that kind of chart.
111 00:14:10.372 ⇒ 00:14:11.880 Uttam Kumaran: That ticket. Tag.
112 00:14:12.120 ⇒ 00:14:13.789 Uttam Kumaran: dbt, thing is still open.
113 00:14:14.600 ⇒ 00:14:17.885 Robert Tseng: Yes, that’s still okay. So hasn’t been done yet.
114 00:14:18.350 ⇒ 00:14:38.839 Robert Tseng: yeah. And then I had a thread with Nick yesterday with some feedback from the clients. There’s a couple of missing custom fields. To make sense. I feel like modeling that he did here was pretty much like off the Zendesk open source thing. So, yeah, there are a couple couple of fields that we will need for the future. One big one is tenants. Id
115 00:14:39.550 ⇒ 00:14:54.749 Robert Tseng: so yeah, there are a lot of id like group id organization ids and stuff like that here tenant id is the only I like, yeah, I would say that’s supposed to be their primary key that
116 00:14:54.780 ⇒ 00:15:15.559 Robert Tseng: links all the different systems together like they. But they manually maintain this field tenant id in Zendesk, in Hubspot, in Maxio. And it’s pulled out of their production data. So what that means is that there are just gaps in the systems. Like, I looked through what we had in Zendesk when I went into their environment.
117 00:15:15.961 ⇒ 00:15:26.200 Robert Tseng: Someone didn’t. Yeah, like, someone is going in every week and like adding it. And like, yeah, adding it in. So I don’t like that, because that means our.
118 00:15:26.290 ⇒ 00:15:44.859 Robert Tseng: the the field that we’re joining on across systems. Isn’t that clean and we’re dependent on them to maintain it across the systems. But that’s the only one we really have to eventually like. Bring this reporting and fold it together with other with the other systems. So that was like one
119 00:15:44.870 ⇒ 00:15:48.390 Robert Tseng: thing I mentioned to Nick that we need to go fish out of Zendesk
120 00:15:48.500 ⇒ 00:15:56.619 Robert Tseng: I sent send sent him a screenshot of like where we could find that. And we can. We can jump in together and and pair on that if he needs help.
121 00:15:57.007 ⇒ 00:16:03.800 Robert Tseng: and then the last, the second data point we needed to bring in they call it like
122 00:16:03.960 ⇒ 00:16:11.400 Robert Tseng: secure fab tags. That’s just their custom tag for like ticket priority.
123 00:16:11.410 ⇒ 00:16:29.849 Robert Tseng: because this is just static satisfaction. But they don’t really have a way of prioritizing like open tickets without using their custom field. So I think that’s the other important field that we need to bring in. I also sent him a screenshot in, like the description of where it should come from, so I would.
124 00:16:29.850 ⇒ 00:16:36.080 Uttam Kumaran: Yeah, I see it. Now let me. We’re gonna I’m gonna let me look in 5 trying to see where we can get it. If it’s not already coming in.
125 00:16:36.372 ⇒ 00:16:44.689 Uttam Kumaran: I think custom fields do come in. There’s just a we had a lot of tables from 5 tran. So I just wanna check where the custom field is that should be great.
126 00:16:44.880 ⇒ 00:16:58.800 Robert Tseng: Okay, cool. Yeah. So those are the 3 open things that I probably need from him to put out. V, 2. And I think one more revision of this, and it should be they should be ready. So at least we’ll we’ll we’ll have that to them by the end of the week.
127 00:16:59.872 ⇒ 00:17:04.810 Robert Tseng: Yeah. So that’s that’s the update on the this side of things.
128 00:17:06.079 ⇒ 00:17:13.092 Uttam Kumaran: Okay, cool. I know. Nick just joined, I guess. Well, we could do a little recap of those 3 things quickly.
129 00:17:14.169 ⇒ 00:17:15.539 Uttam Kumaran: Nick, you you there.
130 00:17:17.790 ⇒ 00:17:19.039 Nick Baker: Yeah. Sorry about that. I was.
131 00:17:19.040 ⇒ 00:17:19.966 Uttam Kumaran: I’m happy.
132 00:17:21.599 ⇒ 00:17:29.633 Uttam Kumaran: You’re good. Yeah, I guess. I guess, like this. I think we could. Just, Robert. I’ll just go through really quick. One thing we need is
133 00:17:29.990 ⇒ 00:17:38.961 Uttam Kumaran: kind of nick that those custom fields that I think Robert message about I could help, you know. Explore some of that with you like where those are. Basically
134 00:17:39.740 ⇒ 00:17:41.439 Uttam Kumaran: the second thing is
135 00:17:41.530 ⇒ 00:17:44.739 Uttam Kumaran: probably is doing the flatten on the ticket tags.
136 00:17:46.580 ⇒ 00:17:48.860 Uttam Kumaran: again, I think that that should be a pretty quick.
137 00:17:49.650 ⇒ 00:17:52.170 Uttam Kumaran: like Dvt model or view change.
138 00:17:53.940 ⇒ 00:17:57.220 Uttam Kumaran: And then what was is there a last? What was the last one.
139 00:17:57.730 ⇒ 00:18:01.413 Robert Tseng: Yeah. So 2 custom fields, and then the flat on the picket tags. I think that will.
140 00:18:01.630 ⇒ 00:18:02.010 Uttam Kumaran: Okay.
141 00:18:02.267 ⇒ 00:18:04.840 Robert Tseng: Bot me to finish to to finish this pretty much.
142 00:18:06.310 ⇒ 00:18:06.940 Robert Tseng: Yeah.
143 00:18:10.090 ⇒ 00:18:13.799 Nicolas Sucari: Ni tena is a custom field. Sorry?
144 00:18:14.480 ⇒ 00:18:15.250 Nicolas Sucari: Yeah.
145 00:18:16.270 ⇒ 00:18:19.110 Nicolas Sucari: What you mentioned Robert, about the tenant Id. That is.
146 00:18:19.110 ⇒ 00:18:19.560 Robert Tseng: Yeah.
147 00:18:19.560 ⇒ 00:18:20.259 Nicolas Sucari: Yeah, right.
148 00:18:20.790 ⇒ 00:18:23.390 Robert Tseng: It is. It is a classic field in Zendesk. Yeah.
149 00:18:28.190 ⇒ 00:18:28.850 Nicolas Sucari: Next slide.
150 00:18:31.870 ⇒ 00:18:39.460 Uttam Kumaran: So let’s I mean, I think we should try to aim to do that this week, and then that way, if you can get out of v, 2, we can
151 00:18:39.560 ⇒ 00:18:41.269 Uttam Kumaran: like again. I,
152 00:18:41.340 ⇒ 00:18:45.600 Uttam Kumaran: we get this. We get the azure stuff set up, and we can begin on the next one.
153 00:18:46.170 ⇒ 00:18:46.980 Robert Tseng: Yeah.
154 00:18:47.160 ⇒ 00:18:56.810 Robert Tseng: So I think while I’m keeping them busy with just drooling over some reporting here, cause I don’t know whatever, I guess.
155 00:18:56.980 ⇒ 00:19:06.330 Robert Tseng: where we can. Hopefully, that gives us more time, buys us more time on the back, on the back end stuff to connect project production data. Sabrina is now like kind of driving
156 00:19:06.690 ⇒ 00:19:11.546 Robert Tseng: project on internally for them, which is help more helpful for me. She’s their lead product.
157 00:19:11.850 ⇒ 00:19:12.259 Uttam Kumaran: Should get.
158 00:19:12.260 ⇒ 00:19:25.769 Robert Tseng: She’s a head of product. So but yeah, that also means that she’s gonna be like pushing for her own agenda as well. She really wants to be able to run queries on Stella data. So that’s also why she decided to jump on this project. So I think.
159 00:19:25.770 ⇒ 00:19:26.110 Uttam Kumaran: So.
160 00:19:26.110 ⇒ 00:19:43.869 Robert Tseng: The direction that we’re going to be taking. Once we jump, once we get the azure data in, is probably going to be less dashboard building. And more like, yeah, just like modeling and building queries for for her and her team. So yeah, I think learning here is.
161 00:19:43.960 ⇒ 00:19:53.239 Robert Tseng: yeah. I think we ran into some walls with the reporting here the stakeholders that I was supposed to be. We were supposed I was supposed to be building these reports for?
162 00:19:53.270 ⇒ 00:20:14.380 Robert Tseng: Yeah, I think just as we’ve gone through this process, requirements keep changing. I don’t feel like they don’t really know what they want. So it’s kind of like a tug, a tug of war a bit where I think this is the only thing I can really give them right now that they’ll be happy with the other 2 like we’re not there yet. We need them. We need the Maxio and the Hubspot data in which I push back, saying
163 00:20:14.400 ⇒ 00:20:20.640 Robert Tseng: that wasn’t part of our original scope. We can’t bring that in now, but we that can be on our roadmap, for, you know, future work
164 00:20:21.020 ⇒ 00:20:28.200 Robert Tseng: so hopefully. That kind of gets them off my back for for some time. But also.
165 00:20:28.200 ⇒ 00:20:30.460 Uttam Kumaran: And the Sabrina on that stuff, too.
166 00:20:31.745 ⇒ 00:20:43.445 Robert Tseng: No, Sabrina doesn’t touch any of that. So yeah, she, yeah, I mean, this is all like Cs, like, related Cs and Ops related stuff that we’ve been starting off with. But yeah,
167 00:20:44.000 ⇒ 00:20:53.349 Robert Tseng: they’ve they’ve actually had this really. Yeah, I don’t. I don’t know how to. I’ve been pushing it off. But they keep pressuring me to the Cs people keep
168 00:20:53.670 ⇒ 00:21:02.030 Robert Tseng: pressuring me to. It’s like, Okay, we don’t need the dashboard. Just give us the data like they want snowflake access. And I’m just like, okay, I mean.
169 00:21:02.050 ⇒ 00:21:05.540 Robert Tseng: I was pushing back. But I’m like, I don’t think you know what to do with it, but
170 00:21:05.630 ⇒ 00:21:20.589 Robert Tseng: if you really want it like, sure, I’ll give you this dashboard. I’ll give you Snowflake access, and you can try to do whatever you want in it. So I think that’s what I’m gonna give them. By the end of the week. The v. 2 of the stash. And then just I don’t know.
171 00:21:20.590 ⇒ 00:21:23.130 Uttam Kumaran: And is there? Do they have an analyst on their side?
172 00:21:23.130 ⇒ 00:21:28.000 Robert Tseng: They don’t, they? I they literally don’t know what they’re doing. I have. I have no idea like what what they’re gonna do.
173 00:21:28.000 ⇒ 00:21:39.479 Uttam Kumaran: I mean, we’re we could walk them through where the tables live. I mean, it could just be nice to be like. Here’s like kind of look at our world and then just get more cozy with folks to get more requirements. Basically.
174 00:21:39.480 ⇒ 00:21:40.280 Robert Tseng: Yeah.
175 00:21:41.280 ⇒ 00:21:45.258 Robert Tseng: yeah, I think maybe that’s that’s the better way to approach it.
176 00:21:45.720 ⇒ 00:22:02.499 Robert Tseng: yeah. So if anything we can, we can, we can give them a training like I think that’s they’re pretty old school like that. I have a. We have a weekly check in with them where they always want me to give them data, walk through some things. So maybe like for next like for the next week or next week. Think
177 00:22:02.520 ⇒ 00:22:16.510 Robert Tseng: it’ll be like a hey? Like we’re gonna bring in like, I don’t know who. Maybe maybe you, Tom, or something and you can just walk them through the tables that they have. And yeah, maybe. And if they and that’ll be the handoff to them while we move on to something else.
178 00:22:17.520 ⇒ 00:22:23.309 Uttam Kumaran: Yeah, I think that’s helpful. You know, it’s also I was even gonna mention that, like Zendesk, data is very rich.
179 00:22:23.340 ⇒ 00:22:27.899 Uttam Kumaran: like, there’s a lot of things we can do, and I think you know, kind of the stuff
180 00:22:27.950 ⇒ 00:22:54.774 Uttam Kumaran: like that you have now it I is is great, and I think I think the nice thing is to think about, how do we actually affect their process like an interesting thing for me is like, I’ve worked with customer success teams. And I actually asked, like, when you look at the dash like, have you go close out certain tickets? So one thing that’s also helpful before is actually to put in ticket links and things like that, so they can go direct from the dashboard to the ticket. So I don’t know. I assume you’ve been thinking about stuff like that. But
181 00:22:55.200 ⇒ 00:23:04.320 Uttam Kumaran: yeah, there’s just a lot of we have a, we get a lot of data from Zendesk, and some of it commonly just sits there. So I think we can leverage a lot of it for stuff.
182 00:23:04.560 ⇒ 00:23:09.879 Robert Tseng: Yeah, totally. Yeah. I mean, I feel like, whatever v, 2 is good. I mean, I already have
183 00:23:09.980 ⇒ 00:23:19.531 Robert Tseng: some feedback from them to put out. V, 2. But I think that’s just gonna be a continual process to keep like bringing it closer and closer to impacting their actual process.
184 00:23:19.830 ⇒ 00:23:20.220 Uttam Kumaran: Okay.
185 00:23:20.220 ⇒ 00:23:28.430 Robert Tseng: Yeah. So I I think, yeah, there’s there’s definitely room for that like partnership. As moving forward on trying to get them to
186 00:23:28.460 ⇒ 00:23:30.670 Robert Tseng: embed this more into their process.
187 00:23:31.630 ⇒ 00:23:32.230 Robert Tseng: Okay.
188 00:23:32.230 ⇒ 00:23:33.970 Uttam Kumaran: Okay, great. So let’s so I think
189 00:23:34.170 ⇒ 00:23:36.679 Uttam Kumaran: now, this makes it more clear. So we’ll consider
190 00:23:36.760 ⇒ 00:23:58.689 Uttam Kumaran: one workflow for the Zendesk. And you know, we’re gonna get to be to on that. We’ll also consider one like workflow for Sabrina. And anything on like those data sources. Basically, so that’s actually helpful to know that she’s kind of owning that. And that way. You know, ideally we can. We are gonna have more
191 00:23:58.780 ⇒ 00:24:25.484 Uttam Kumaran: things associated with database, migrations and Etl. So it’s good that she’s she’s there for that cause, like running again to the same jam. But additionally, like, I think the goal for us is like just to get as much data into your hands. Modeled on that side so that you know you could help her kind of run quickly. I don’t know whether Meta base is like the best tool for like that sort of data exploration.
192 00:24:26.330 ⇒ 00:24:31.279 Uttam Kumaran: but like again, if if she’s if she’s gonna be the owner of that. Then that’s a great conversation we can have with her about like
193 00:24:31.390 ⇒ 00:24:40.118 Uttam Kumaran: if she’s gonna be writing queries, or if she actually wants to explore another tool or whether it should use dashboard. So like, that’s great to know.
194 00:24:40.590 ⇒ 00:25:05.150 Robert Tseng: I mean, I think she’s kind of leaving it on us to like advise on what tool or she actually wanted me to put together, kind of like an evaluation of different tools that have been talked about in the company. And I mean, I just went with metabase right now, since it was easy to to to stand up. But yeah, if you have any other suggestions on like other ways that we yeah making data exploration more accessible.
195 00:25:05.450 ⇒ 00:25:21.189 Robert Tseng: okay, I figured. That’s as we already do the modeling in Dbt, we don’t definitely don’t need a looker right away. And we could just use. I mean, I I don’t know. I I metabase you can run. You can run queries, and there’s a lot of drag and drop as well. So I just thought that’d be an easy one to to spin up for them. So.
196 00:25:22.310 ⇒ 00:25:25.299 Uttam Kumaran: Yeah, I think there’s a we’re actually doing an evaluation for
197 00:25:25.340 ⇒ 00:25:40.909 Uttam Kumaran: another client right now of like Vi, but also the customer facing analytics. So maybe we can even just repurpose. I mean, I was just gonna put together. I guess I don’t know. I didn’t think about if I was gonna put together slides or not, but maybe we could just repurpose that. And then I could. We can
198 00:25:41.040 ⇒ 00:25:42.470 Uttam Kumaran: present to her like
199 00:25:42.520 ⇒ 00:25:48.329 Uttam Kumaran: we’re we constantly are like talking to all the vendors, basically. And yeah, I’m a little bit allergic to doing looker
200 00:25:48.400 ⇒ 00:25:53.421 Uttam Kumaran: or tableau. But some people are old school. They like tableau looker is like a little bit. Obie.
201 00:25:53.700 ⇒ 00:25:54.260 Robert Tseng: Yeah.
202 00:25:54.260 ⇒ 00:25:58.720 Uttam Kumaran: Tableau could be nice. But there’s also some lower cost options
203 00:25:58.880 ⇒ 00:26:17.190 Uttam Kumaran: that are really cool to work with, that that we’ve been exploring. That also share. And I nothing. I think a lot about as a developer workflow. Actually, it’s something that I think commonly they didn’t get. People don’t consider when they make a bi tool. But I’m like, how fast is it for us to make an iteration.
204 00:26:17.230 ⇒ 00:26:29.940 Uttam Kumaran: and for that to get on the model on the actual dashboard, and then for that to get into the clients hands right like. If Nick pushes a new column, then it requires another step for that to get like modeled in like a
205 00:26:29.950 ⇒ 00:26:59.129 Uttam Kumaran: metabase layer or something, and then it gets the client like, I would say, that’s usually like at least probably a week if we’re if we’re being honest right. And so I think a lot about like when I make the recommendation to the client is like, if you go with this tool, although, like, maybe there are, some trade operation cycle can be a few days, or even like someone who’s someone who doesn’t. Some like more people can access that versus. There’s some tools where there’s so focus in the presentation layer that typically takes no time. So like
206 00:26:59.170 ⇒ 00:27:00.120 Uttam Kumaran: that’s
207 00:27:00.200 ⇒ 00:27:03.430 Uttam Kumaran: try to do things that like help us. That decision cause
208 00:27:03.600 ⇒ 00:27:07.540 Uttam Kumaran: like looker is really hard. Table is also kind of really difficult to use. So.
209 00:27:08.160 ⇒ 00:27:14.829 Robert Tseng: Yeah, totally. Yeah. I mean, let’s keep. Let’s keep talking about that issue. They want me to talk to her about soon.
210 00:27:15.521 ⇒ 00:27:35.340 Robert Tseng: So, yeah, I mean, I, yeah, I I mean, I’m I’m open to to hearing hearing your thoughts and what other tools you recommend that are easier for for this workflow in in the future. Yeah, I think metabase was just like a personal personal choice. It wasn’t really anything yeah like that. The client asked for.
211 00:27:36.442 ⇒ 00:27:41.529 Uttam Kumaran: No, it’s it works. Metadata works well. And I think it’s like again, just get our feet with it. And then.
212 00:27:41.590 ⇒ 00:27:50.779 Uttam Kumaran: like, just like, I just wanna get get from 0 to one, and then from one to 2 we’ll have, like again, snowflake set up models set up
213 00:27:50.800 ⇒ 00:28:01.620 Uttam Kumaran: reference dashboards. Then it’s like easy to go from there like we’re not. Gonna it’s gonna it’s difficult to make the right decision upfront, because it it is based on the people, you know, a lot of the time. So.
214 00:28:01.620 ⇒ 00:28:02.880 Robert Tseng: Yeah. Totally.
215 00:28:03.810 ⇒ 00:28:04.340 Robert Tseng: Okay.
216 00:28:04.340 ⇒ 00:28:31.279 Uttam Kumaran: Okay, cool, great. I think we’ll just talk in slack. Otherwise and then we’ll get. I wanna get all this, basically. Now that we have kind of like the people. And like kind of the workflows and everything in notion, Nico, basically, also, as we’re thinking even longer term. And and we had conversations about like different dashboards in the future. Just have all of our thoughts there that way when those times come, like we have notes. And yeah, just keep
217 00:28:31.680 ⇒ 00:28:32.470 Uttam Kumaran: cool.
218 00:28:34.440 ⇒ 00:28:42.646 Uttam Kumaran: Alright, I didn’t. I didn’t start the meeting by asking how everything else is going. But I hope everything’s going well and hope new York is going well.
219 00:28:43.310 ⇒ 00:28:51.070 Robert Tseng: Yeah, yeah, it was good. I was, you know, this business travel past week and then wasn’t awesome for a bit. You were out. But yeah, hopefully.
220 00:28:51.070 ⇒ 00:28:52.139 Uttam Kumaran: Oh, yeah. How was it.
221 00:28:52.140 ⇒ 00:28:52.880 Robert Tseng: Be back.
222 00:28:53.410 ⇒ 00:29:17.818 Robert Tseng: Oh, it’s great! Just attended a conference that was like for other like tech service founders. And so it was great to meet like that. There’s a big community of them, and around the around Texas, I guess so. Met a lot of people from Dallas and and and Austin. So it was good good inspiration. And then, yeah, like, went to like other like conferences in La in San Francisco. So hopefully.
223 00:29:18.140 ⇒ 00:29:18.620 Uttam Kumaran: Thanks.
224 00:29:18.620 ⇒ 00:29:19.940 Robert Tseng: Momentum. Yeah.
225 00:29:20.660 ⇒ 00:29:29.721 Uttam Kumaran: Yeah, hell, yeah. Yeah. And I, I was just in Pennsylvania. The East coast weather was really nice this past weekend. So hopefully, you get a little bit before it gets like way too hot.
226 00:29:29.980 ⇒ 00:29:35.179 Robert Tseng: Yeah, it’s already getting a bit muggy. So I bought a dehumid dehumidifier for the 1st time.
227 00:29:35.180 ⇒ 00:29:35.920 Uttam Kumaran: Yes.
228 00:29:36.660 ⇒ 00:29:38.100 Robert Tseng: How it works, but we’ll.
229 00:29:38.100 ⇒ 00:29:45.700 Uttam Kumaran: It works real. It’ll work really, really. Well, actually, I had a humidifier and a dehumidifier, and then it gets dry, you know.
230 00:29:45.700 ⇒ 00:29:46.090 Robert Tseng: Yeah.
231 00:29:47.120 ⇒ 00:29:48.180 Uttam Kumaran: so
232 00:29:48.670 ⇒ 00:29:49.750 Uttam Kumaran: nice.
233 00:29:50.200 ⇒ 00:29:50.950 Robert Tseng: Ask.
234 00:29:52.040 ⇒ 00:29:56.494 Uttam Kumaran: Okay, cool gang. Nick, anything from your side?
235 00:29:57.394 ⇒ 00:30:06.299 Nick Baker: No, nothing crazy. Just just have a a meeting heavy week. So so I’ve been a little in and out.
236 00:30:06.610 ⇒ 00:30:07.540 Nick Baker: Okay, cool.
237 00:30:09.950 ⇒ 00:30:13.105 Uttam Kumaran: Okay, great alright guys, we’ll talk at slack.
238 00:30:13.500 ⇒ 00:30:13.890 Robert Tseng: Alright!
239 00:30:13.890 ⇒ 00:30:14.520 Nicolas Sucari: Excellent.
240 00:30:14.520 ⇒ 00:30:14.980 Robert Tseng: Hey, guys.
241 00:30:14.980 ⇒ 00:30:15.700 Nicolas Sucari: Like guys.
242 00:30:16.500 ⇒ 00:30:16.953 Uttam Kumaran: Thank you.