Meeting Title: Eden Revenue Data Sync Date: 2026-03-12 Meeting participants: Awaish Kumar, Mustafa Raja, Demilade Agboola
WEBVTT
1 00:00:21.980 ⇒ 00:00:23.000 Mustafa Raja: Hey.
2 00:00:24.480 ⇒ 00:00:25.050 Awaish Kumar: Hello.
3 00:00:27.770 ⇒ 00:00:35.740 Awaish Kumar: Yeah, can you just, like, really have a lot of things to do today. Can you just… can you just get started?
4 00:00:36.150 ⇒ 00:00:42.110 Awaish Kumar: Can you just open the… Tableau.
5 00:00:51.710 ⇒ 00:00:53.110 Awaish Kumar: I ended up…
6 00:00:59.460 ⇒ 00:01:01.010 Awaish Kumar: Hi, Demi.
7 00:01:04.790 ⇒ 00:01:05.150 Demilade Agboola: Hello.
8 00:01:05.150 ⇒ 00:01:06.930 Mustafa Raja: Yeah, okay, so…
9 00:01:06.930 ⇒ 00:01:08.170 Awaish Kumar: What I’m actually trying to.
10 00:01:08.170 ⇒ 00:01:09.680 Mustafa Raja: The values are pretty much…
11 00:01:10.220 ⇒ 00:01:10.870 Awaish Kumar: Sorry?
12 00:01:11.920 ⇒ 00:01:15.050 Mustafa Raja: Oh, values… I’m saying the values are matching.
13 00:01:16.280 ⇒ 00:01:19.220 Awaish Kumar: Like, what are the… revenue is not much.
14 00:01:19.220 ⇒ 00:01:19.970 Demilade Agboola: she needs it.
15 00:01:20.870 ⇒ 00:01:21.670 Mustafa Raja: Sorry?
16 00:01:21.670 ⇒ 00:01:24.359 Demilade Agboola: I don’t think… is this our revenue matching? Can I see, please?
17 00:01:27.330 ⇒ 00:01:28.899 Awaish Kumar: No, it is not.
18 00:01:28.970 ⇒ 00:01:30.940 Demilade Agboola: Those two data total revenue is not matching.
19 00:01:32.830 ⇒ 00:01:33.780 Demilade Agboola: It’s 3…
20 00:01:33.780 ⇒ 00:01:35.530 Mustafa Raja: 30 day total revenue.
21 00:01:35.530 ⇒ 00:01:36.310 Awaish Kumar: On the top.
22 00:01:36.310 ⇒ 00:01:38.890 Demilade Agboola: On the top, just so you don’t have to go too far.
23 00:01:39.060 ⇒ 00:01:40.900 Demilade Agboola: Just topless, the top, the key…
24 00:01:40.900 ⇒ 00:01:48.050 Mustafa Raja: Yeah, I think this might be the filter, because this one might match 6273…
25 00:01:48.210 ⇒ 00:01:53.259 Mustafa Raja: Yeah, this one matches, so I’m going to match the filters for these two.
26 00:01:53.680 ⇒ 00:01:55.230 Mustafa Raja: Let me open this up.
27 00:01:55.230 ⇒ 00:01:58.299 Demilade Agboola: Here, let’s play 6-2-7-3, this is 6-3-9-5.
28 00:01:58.880 ⇒ 00:02:00.170 Demilade Agboola: Right? Am I…
29 00:02:00.170 ⇒ 00:02:13.310 Mustafa Raja: Yeah, 6273… 667… Yeah, I’d say… Yes, but the number up top is not matching, that’s what I’m… that’s what I’m seeing. Yeah, yeah, so that… that… that’s just going to be some filter that I’m missing.
30 00:02:13.310 ⇒ 00:02:15.820 Demilade Agboola: Oh, okay. And when did you refresh this data?
31 00:02:17.400 ⇒ 00:02:18.440 Demilade Agboola: the Tableau data.
32 00:02:18.440 ⇒ 00:02:21.829 Mustafa Raja: Ablohan, I think you refreshed? I didn’t refresh the OMI.
33 00:02:21.830 ⇒ 00:02:24.389 Demilade Agboola: No, I didn’t, I just told you how to do it, but, yeah.
34 00:02:31.040 ⇒ 00:02:31.730 Mustafa Raja: Hmm.
35 00:02:32.440 ⇒ 00:02:33.300 Awaish Kumar: But the point is.
36 00:02:33.300 ⇒ 00:02:35.810 Mustafa Raja: Let me see what I’m… For the double…
37 00:02:37.150 ⇒ 00:02:40.870 Awaish Kumar: top chart, does it include abandoned orders or
38 00:02:42.050 ⇒ 00:02:44.599 Awaish Kumar: Or does it? This one? Yes, this one.
39 00:02:47.100 ⇒ 00:02:49.110 Mustafa Raja: Here is, let me see…
40 00:02:53.040 ⇒ 00:02:55.480 Mustafa Raja: Total revenue 30 day…
41 00:03:01.470 ⇒ 00:03:02.999 Mustafa Raja: So this is…
42 00:03:21.780 ⇒ 00:03:26.420 Mustafa Raja: So this is total revenue, and I am filtering it.
43 00:03:30.980 ⇒ 00:03:32.920 Mustafa Raja: If I only get 13…
44 00:03:37.810 ⇒ 00:03:38.660 Mustafa Raja: Nope.
45 00:03:44.060 ⇒ 00:03:47.030 Mustafa Raja: Yeah, this is weird and why it’s not matching.
46 00:03:47.370 ⇒ 00:03:49.659 Awaish Kumar: Yeah, but why we are saying 31 days?
47 00:03:54.330 ⇒ 00:04:00.480 Awaish Kumar: We should be, like, including the current, we should have, like, 30 days? Yeah, 31 days, maybe.
48 00:04:00.960 ⇒ 00:04:02.529 Awaish Kumar: That’s what it was doing.
49 00:04:02.530 ⇒ 00:04:05.159 Mustafa Raja: Yeah, this is… hmm, this is enough.
50 00:04:05.460 ⇒ 00:04:09.720 Awaish Kumar: No, but we don’t need complete days. We need all the data until today.
51 00:04:13.160 ⇒ 00:04:14.369 Mustafa Raja: And this is the North.
52 00:04:15.910 ⇒ 00:04:21.639 Awaish Kumar: I think from the Tableau I, we figured out that it was actually using 30 volunteers, right?
53 00:04:22.470 ⇒ 00:04:24.409 Mustafa Raja: Yeah, that’s what we figured out.
54 00:04:29.570 ⇒ 00:04:32.670 Mustafa Raja: And this is what we are saying here also, no?
55 00:04:36.210 ⇒ 00:04:36.920 Awaish Kumar: Yeah.
56 00:04:37.650 ⇒ 00:04:41.389 Awaish Kumar: If we are doing this here, then we don’t need a filter, why do we need…
57 00:04:41.560 ⇒ 00:04:51.210 Demilade Agboola: Yeah, so we don’t need a filter. And also, like, if the number matches in the overall chart, why isn’t, like, why is there a difference? Are we using, like, what’s different there that we’re not doing here?
58 00:04:51.450 ⇒ 00:04:53.110 Mustafa Raja: Yeah, I’m trying to figure that out.
59 00:04:55.620 ⇒ 00:04:57.379 Awaish Kumar: Yeah, but why don’t we have this…
60 00:04:57.830 ⇒ 00:05:01.409 Awaish Kumar: If we have the condition SQL, why we are having the filter again?
61 00:05:03.150 ⇒ 00:05:07.150 Mustafa Raja: No, no, no, so this is, this is some other field, right?
62 00:05:07.470 ⇒ 00:05:11.470 Mustafa Raja: This is… and this is some other, definition.
63 00:05:12.680 ⇒ 00:05:18.080 Mustafa Raja: So I could just, use this, but then we wouldn’t have this comparison.
64 00:05:18.530 ⇒ 00:05:19.350 Awaish Kumar: Okay.
65 00:05:20.220 ⇒ 00:05:25.369 Mustafa Raja: To build this comparison, we have to build it in, you know, in this fashion.
66 00:05:26.670 ⇒ 00:05:30.380 Awaish Kumar: Okay, it’s not abomin, and…
67 00:05:32.140 ⇒ 00:05:38.219 Awaish Kumar: Okay, can you, like, Diamond, can you help us also, in parallel, look at, like, how
68 00:05:38.330 ⇒ 00:05:40.180 Awaish Kumar: It’s being calculated in Tableau.
69 00:05:43.500 ⇒ 00:05:45.470 Demilade Agboola: Okay, let me look at it right now.
70 00:05:55.980 ⇒ 00:05:59.170 Awaish Kumar: I can look in what the numbers are in BigQuery.
71 00:06:42.410 ⇒ 00:06:45.460 Demilade Agboola: Okay, so this is the formula. I’m sending the formula in the chat.
72 00:06:45.590 ⇒ 00:06:48.869 Demilade Agboola: Zoom chat, so this is what’s used to calculate the total revenue.
73 00:06:50.420 ⇒ 00:06:53.010 Demilade Agboola: So, less than equals to 30 days.
74 00:06:53.210 ⇒ 00:06:57.560 Demilade Agboola: It’s not abandoned, is not canceled, and is not error.
75 00:06:58.050 ⇒ 00:07:02.930 Mustafa Raja: So, canceled and error are, the values just don’t exist in the current status.
76 00:07:02.930 ⇒ 00:07:03.880 Awaish Kumar: Okay.
77 00:07:03.880 ⇒ 00:07:04.620 Demilade Agboola: Oh, okay.
78 00:07:04.840 ⇒ 00:07:06.810 Demilade Agboola: I’m just telling you what the formula is.
79 00:07:07.190 ⇒ 00:07:11.109 Demilade Agboola: Then sum up the transaction revenue, or else it’s zero.
80 00:07:12.570 ⇒ 00:07:14.949 Demilade Agboola: So that’s basically what I see.
81 00:07:14.950 ⇒ 00:07:17.400 Mustafa Raja: This is what we are doing, though.
82 00:07:52.650 ⇒ 00:07:53.630 Mustafa Raja: 15 days.
83 00:09:02.190 ⇒ 00:09:07.959 Awaish Kumar: You know, and… Can we refresh right now, Tableau, and see the number?
84 00:09:08.810 ⇒ 00:09:10.680 Demilade Agboola: Oh, sure, let me do that.
85 00:09:14.590 ⇒ 00:09:17.749 Awaish Kumar: Because BigQuery numbers are matching with what was found.
86 00:09:17.850 ⇒ 00:09:19.330 Awaish Kumar: Excuse me on me.
87 00:09:20.100 ⇒ 00:09:24.569 Demilade Agboola: Okay, so my thing is… Gustavo, can you send me back to the dashboard? Dashboard view?
88 00:09:25.170 ⇒ 00:09:26.619 Mustafa Raja: Which one? On YouTube?
89 00:09:26.620 ⇒ 00:09:29.010 Demilade Agboola: The dashboard view, yeah, the full, only dashboard view.
90 00:09:31.700 ⇒ 00:09:37.779 Demilade Agboola: My own thing is, like, I’m wondering why, like, it’s not matching the number at the bottom. Like, total revenue…
91 00:09:37.780 ⇒ 00:09:38.220 Mustafa Raja: This one…
92 00:09:38.370 ⇒ 00:09:39.250 Demilade Agboola: Yes.
93 00:09:39.820 ⇒ 00:09:42.010 Demilade Agboola: is what we have in Tableau.
94 00:09:44.280 ⇒ 00:09:52.559 Demilade Agboola: But the number up top is different. That’s what I’m curious about, like, what calculation are you using to calculate total revenue for each of these?
95 00:09:54.110 ⇒ 00:10:00.179 Mustafa Raja: Oh, this, yeah, so I just refreshed… I just, refreshed it without cache, and this now matches.
96 00:10:01.280 ⇒ 00:10:02.499 Demilade Agboola: Okay, alright then.
97 00:10:02.500 ⇒ 00:10:05.540 Mustafa Raja: Yeah, so maybe if we… if we refresh Tableau.
98 00:10:06.130 ⇒ 00:10:07.950 Demilade Agboola: Sure, I’ll refresh Dablo now.
99 00:10:11.120 ⇒ 00:10:17.620 Demilade Agboola: This has two data sources… Refresh the first one…
100 00:10:21.510 ⇒ 00:10:22.339 Demilade Agboola: And then…
101 00:10:41.340 ⇒ 00:10:43.489 Demilade Agboola: So they are refreshing right now, I’ll let you know when it’s done.
102 00:10:44.720 ⇒ 00:10:45.560 Mustafa Raja: Okay.
103 00:10:49.410 ⇒ 00:10:51.730 Mustafa Raja: So… how’s the day going?
104 00:10:58.880 ⇒ 00:11:03.989 Demilade Agboola: So far it’s good, just a lot of… there’s a lot of things happening, but…
105 00:11:04.460 ⇒ 00:11:08.330 Demilade Agboola: Defaults Magic Spoon and eating all at the same time, so… Kind of busy.
106 00:11:08.330 ⇒ 00:11:08.890 Mustafa Raja: Yeah.
107 00:11:14.550 ⇒ 00:11:15.430 Demilade Agboola: How’s your day going?
108 00:11:16.750 ⇒ 00:11:22.439 Mustafa Raja: Yeah, I just, started early, looked into the default thing.
109 00:11:23.210 ⇒ 00:11:30.439 Mustafa Raja: For the opportunities cleaned, we just don’t have the definition for that. And I found one other table that we don’t have definition of.
110 00:11:32.210 ⇒ 00:11:33.150 Demilade Agboola: Yeah, so…
111 00:11:33.150 ⇒ 00:11:37.960 Mustafa Raja: Because the table that they’re building, the summary they’re building,
112 00:11:38.080 ⇒ 00:11:50.230 Mustafa Raja: the granularity for it is monthly, right? But they have, KPIs per day also. And that is coming from another table that we don’t have access to.
113 00:11:50.850 ⇒ 00:11:58.030 Demilade Agboola: That’s… again, that’s why I said last week that we need, or like I mentioned, we need access to all their views, because that’s.
114 00:11:58.030 ⇒ 00:11:58.500 Mustafa Raja: Yeah.
115 00:11:58.500 ⇒ 00:12:00.459 Demilade Agboola: Get to be able to start to do all of this.
116 00:12:00.890 ⇒ 00:12:02.469 Demilade Agboola: And then Kate.
117 00:12:02.470 ⇒ 00:12:03.260 Mustafa Raja: Mrs.
118 00:12:03.390 ⇒ 00:12:05.650 Demilade Agboola: we have it, and I’m like, no, we don’t have it.
119 00:12:05.750 ⇒ 00:12:06.510 Demilade Agboola: Buds.
120 00:12:07.400 ⇒ 00:12:15.180 Mustafa Raja: Yeah, so this is… this is what I’m talking about. I think we’re missing this one also. Heading metric pacing inputs.
121 00:12:16.270 ⇒ 00:12:17.010 Demilade Agboola: Yeah.
122 00:12:20.760 ⇒ 00:12:22.080 Mustafa Raja: Amy’s.
123 00:12:22.790 ⇒ 00:12:25.770 Mustafa Raja: Let’s focus on Eden for now.
124 00:12:29.060 ⇒ 00:12:29.930 Mustafa Raja: Boom.
125 00:12:40.990 ⇒ 00:12:44.119 Demilade Agboola: I have to hop in, like, 2 minutes, because I have an interview.
126 00:12:44.840 ⇒ 00:12:47.320 Demilade Agboola: But… I…
127 00:12:48.260 ⇒ 00:12:52.299 Demilade Agboola: The first refresh is done, I’m waiting for the second one to be done, I’ll let you know.
128 00:12:53.230 ⇒ 00:12:54.590 Demilade Agboola: Yeah, it’s gone.
129 00:12:57.970 ⇒ 00:13:02.280 Demilade Agboola: Okay, yes, it’s done, so let’s quickly… can you refresh the dashboard, please?
130 00:13:13.170 ⇒ 00:13:21.729 Mustafa Raja: Okay, 3… 395773. Yeah, 395773. This is good, 2671.
131 00:13:21.730 ⇒ 00:13:24.189 Awaish Kumar: First one, take the screenshots from both.
132 00:13:24.450 ⇒ 00:13:26.760 Mustafa Raja: Okay, good. Send it in the jail.
133 00:13:26.900 ⇒ 00:13:29.090 Awaish Kumar: That does match, and second thing…
134 00:13:29.490 ⇒ 00:13:31.059 Mustafa Raja: What I want is…
135 00:13:31.060 ⇒ 00:13:33.970 Awaish Kumar: What is the refresh time for the tableau?
136 00:13:34.070 ⇒ 00:13:34.860 Awaish Kumar: Extract?
137 00:13:35.490 ⇒ 00:13:39.439 Demilade Agboola: Public is once a day, basically. Let’s just say once a day. It runs…
138 00:13:39.440 ⇒ 00:13:40.590 Awaish Kumar: Taking my time.
139 00:13:41.200 ⇒ 00:13:46.210 Demilade Agboola: Maybe… I will have to confirm, give me one second, let me quickly look at it.
140 00:13:47.240 ⇒ 00:13:50.750 Demilade Agboola: Task… So it depends on the dashboard you’re looking for.
141 00:13:50.940 ⇒ 00:13:52.910 Awaish Kumar: This one, or only this one?
142 00:13:52.910 ⇒ 00:13:56.635 Demilade Agboola: So, okay, so fact transaction… Hmm…
143 00:14:00.640 ⇒ 00:14:01.730 Demilade Agboola: Jesus Christ.
144 00:14:02.080 ⇒ 00:14:08.520 Demilade Agboola: So this one is at… 9.40 AM… my time.
145 00:14:08.730 ⇒ 00:14:13.620 Demilade Agboola: Which is… I’m 5 hours ahead of New York, so that would be 4.40am.
146 00:14:13.780 ⇒ 00:14:14.579 Demilade Agboola: You got time.
147 00:14:15.640 ⇒ 00:14:18.119 Awaish Kumar: 4.40 a.m. New York time, okay.
148 00:14:18.380 ⇒ 00:14:19.769 Awaish Kumar: Okay, thank you, Remy.
149 00:14:19.770 ⇒ 00:14:21.170 Demilade Agboola: Alright, so I have to hope now, I’m sorry.
150 00:14:21.610 ⇒ 00:14:23.160 Demilade Agboola: Yeah, bye. Have a good day.
151 00:14:24.640 ⇒ 00:14:27.689 Awaish Kumar: Mustva, okay, and then also schedule it at the same time.
152 00:14:27.920 ⇒ 00:14:28.610 Mustafa Raja: Thank you.
153 00:14:30.620 ⇒ 00:14:32.800 Mustafa Raja: Schedule it at what time?
154 00:14:32.970 ⇒ 00:14:35.390 Awaish Kumar: 4.40 New York time.
155 00:14:36.820 ⇒ 00:14:40.830 Awaish Kumar: The report that goes out to the… Come on.
156 00:14:43.160 ⇒ 00:14:45.680 Awaish Kumar: the port that goes out for the Josh?
157 00:14:47.070 ⇒ 00:14:55.370 Awaish Kumar: only way to make it similar to Tableau is that we should create a… Report at the same time.
158 00:14:55.790 ⇒ 00:14:57.509 Awaish Kumar: So the data looks the same.
159 00:14:57.860 ⇒ 00:15:05.659 Awaish Kumar: And the way is to, like, the Tableau refreshes at 4.40 AM, Eastern time zone.
160 00:15:06.010 ⇒ 00:15:09.340 Awaish Kumar: So we just have to send this report at the same time. 4.40.
161 00:15:09.460 ⇒ 00:15:11.010 Awaish Kumar: AM Eastern.
162 00:15:13.530 ⇒ 00:15:20.330 Mustafa Raja: 4.40 a.m. Eastern, okay. I’m seeing that the 60-day might be… Different.
163 00:15:21.610 ⇒ 00:15:24.870 Mustafa Raja: It’s less in Tableau and more in Omni.
164 00:15:25.400 ⇒ 00:15:26.880 Mustafa Raja: The rest matches.
165 00:15:28.470 ⇒ 00:15:30.080 Mustafa Raja: How soon are eligible.
166 00:15:31.410 ⇒ 00:15:34.660 Mustafa Raja: Yeah, so it, so it doesn’t match.
167 00:15:36.270 ⇒ 00:15:44.320 Mustafa Raja: Let me see if it matches here. 60-day total orders… 51363…
168 00:15:49.820 ⇒ 00:15:56.349 Mustafa Raja: Okay, so even Tableau’s values don’t match with… With itself, you know?
169 00:15:58.440 ⇒ 00:16:04.590 Mustafa Raja: So, Tableau on the top is saying that 16-day total orders are 55.88.
170 00:16:04.830 ⇒ 00:16:08.810 Mustafa Raja: And then at the bottom, it says, 60-day total orders.
171 00:16:09.070 ⇒ 00:16:12.830 Mustafa Raja: Or 513503.
172 00:16:14.080 ⇒ 00:16:16.160 Awaish Kumar: Okay, and what are lower numbers?
173 00:16:16.770 ⇒ 00:16:22.850 Mustafa Raja: Our numbers are… 51363.
174 00:16:25.970 ⇒ 00:16:38.169 Mustafa Raja: Let me see if rest of the values for Tableau… So, all top-level values match except total orders, and then I’m seeing that if Tableau’s value match with itself or not.
175 00:16:38.360 ⇒ 00:16:44.379 Mustafa Raja: 216 zeros… 2-1. Yeah, so total revenue also doesn’t match.
176 00:16:44.490 ⇒ 00:16:56.660 Mustafa Raja: within Tableau. So, Tableau at the top-level KPIs is 216018, and then the overall total, total revenue 60 days is
177 00:16:57.680 ⇒ 00:17:00.340 Mustafa Raja: Yeah, it’s because they… Yeah, totally.
178 00:17:00.340 ⇒ 00:17:01.290 Awaish Kumar: What’s that?
179 00:17:01.520 ⇒ 00:17:11.710 Awaish Kumar: First of all, we already know that, right? Top… bottom values don’t match with top levels, because at the bottom level, they were including the embedded orders.
180 00:17:12.079 ⇒ 00:17:19.839 Awaish Kumar: Like, on the top level, we are excluding the abandoned orders, and in the product level, they are including the abandoned orders.
181 00:17:21.290 ⇒ 00:17:22.119 Mustafa Raja: Okay.
182 00:17:24.109 ⇒ 00:17:25.019 Awaish Kumar: You can check it.
183 00:17:38.889 ⇒ 00:17:39.899 Awaish Kumar: for the…
184 00:17:43.060 ⇒ 00:17:44.370 Mustafa Raja: Burger Orders.
185 00:17:58.630 ⇒ 00:18:00.560 Awaish Kumar: This is the one, total orders.
186 00:18:02.250 ⇒ 00:18:03.440 Awaish Kumar: 60 days.
187 00:18:08.100 ⇒ 00:18:10.809 Awaish Kumar: So it excludes the abandoned orders on top.
188 00:18:10.940 ⇒ 00:18:13.890 Awaish Kumar: But if you go to the bottom chart.
189 00:18:18.530 ⇒ 00:18:21.419 Mustafa Raja: I think this is the same thing, but they’re not…
190 00:18:21.420 ⇒ 00:18:23.939 Awaish Kumar: I go to the… go back to that other chart.
191 00:18:24.650 ⇒ 00:18:25.050 Mustafa Raja: Okay.
192 00:18:28.760 ⇒ 00:18:35.130 Awaish Kumar: the product level chart, not here, not at the dashboard. I’m saying go to the… Edit?
193 00:18:35.570 ⇒ 00:18:38.880 Awaish Kumar: And go to this chart where it shows product level.
194 00:18:40.140 ⇒ 00:18:43.070 Awaish Kumar: Like, yeah, this one. Should go with…
195 00:18:43.960 ⇒ 00:18:50.049 Awaish Kumar: Open the one, yeah, this one. Now, if you look at the total orders, 60 days, it will be different.
196 00:18:58.170 ⇒ 00:18:58.910 Awaish Kumar: No?
197 00:19:00.370 ⇒ 00:19:01.750 Mustafa Raja: I think it’s just…
198 00:19:03.280 ⇒ 00:19:04.240 Awaish Kumar: What was?
199 00:19:05.930 ⇒ 00:19:06.820 Mustafa Raja: How cool!
200 00:19:08.960 ⇒ 00:19:13.150 Awaish Kumar: But I remember it was a little bit different. If you can… yeah, let’s close.
201 00:19:14.320 ⇒ 00:19:16.990 Awaish Kumar: And what about total revenue, 60 days?
202 00:19:19.720 ⇒ 00:19:20.060 Mustafa Raja: Yeah.
203 00:19:20.060 ⇒ 00:19:23.789 Awaish Kumar: Yeah, it matches. In the same… yeah, in the same tableau.
204 00:19:24.200 ⇒ 00:19:28.780 Awaish Kumar: She is… Let’s look at the calculation for 6…
205 00:19:29.850 ⇒ 00:19:38.929 Mustafa Raja: I think this matches the, 12, 13, 50, 71… 12, 13…
206 00:19:40.740 ⇒ 00:19:43.250 Mustafa Raja: And this is… this is not a difference.
207 00:20:09.960 ⇒ 00:20:13.860 Awaish Kumar: Yeah. If it uses the same definition, why it doesn’t match in the same?
208 00:20:14.520 ⇒ 00:20:19.539 Mustafa Raja: Yeah, I think it’s using the same definition, but the values don’t match.
209 00:20:22.630 ⇒ 00:20:24.610 Awaish Kumar: Okay, can you click on major names?
210 00:20:25.050 ⇒ 00:20:26.049 Awaish Kumar: What is that?
211 00:20:26.980 ⇒ 00:20:31.850 Mustafa Raja: Wait, I just thought maybe… Okay, major names, here.
212 00:20:31.850 ⇒ 00:20:32.470 Awaish Kumar: Yes.
213 00:20:33.600 ⇒ 00:20:34.830 Awaish Kumar: Let me just see it.
214 00:20:36.760 ⇒ 00:20:41.750 Awaish Kumar: Okay, just inspecting what… Okay.
215 00:20:41.750 ⇒ 00:20:42.570 Mustafa Raja: Okay.
216 00:20:45.630 ⇒ 00:20:46.280 Awaish Kumar: Okay.
217 00:20:54.880 ⇒ 00:20:58.379 Awaish Kumar: Okay, so I do not exactly know what’s going on here.
218 00:21:11.710 ⇒ 00:21:16.909 Awaish Kumar: So, what is the values for… let me see in BigQuery, what is the value? 60 days?
219 00:21:20.080 ⇒ 00:21:27.240 Awaish Kumar: For 60 days, it is, like, 12135071.
220 00:21:28.510 ⇒ 00:21:30.489 Mustafa Raja: Yeah, this is what I have.
221 00:21:31.710 ⇒ 00:21:32.380 Awaish Kumar: I’m kidding.
222 00:21:32.830 ⇒ 00:21:37.449 Mustafa Raja: What is in the tableau? And I think, at the top level…
223 00:21:39.250 ⇒ 00:21:42.079 Mustafa Raja: It’s the same as in Omni.
224 00:21:42.270 ⇒ 00:21:43.150 Mustafa Raja: Yeah.
225 00:21:44.740 ⇒ 00:21:47.800 Mustafa Raja: 12135071.
226 00:21:48.180 ⇒ 00:21:55.349 Mustafa Raja: Which is exactly the same as an Omni, but I don’t know why this… Why this is like this.
227 00:21:56.370 ⇒ 00:21:58.600 Awaish Kumar: We can leave it. It’s okay.
228 00:22:00.110 ⇒ 00:22:01.020 Mustafa Raja: Okay.
229 00:22:02.890 ⇒ 00:22:07.850 Awaish Kumar: Okay, now schedule it at the same time as… Thanks, Tableau.
230 00:22:14.890 ⇒ 00:22:18.270 Awaish Kumar: Yeah, but it is hard to… I know, because…
231 00:22:18.780 ⇒ 00:22:22.920 Awaish Kumar: Anytime you schedule, you know, in that moment, if there’s one order.
232 00:22:23.510 ⇒ 00:22:26.059 Awaish Kumar: Placed, you see the difference in revenue.
233 00:22:26.710 ⇒ 00:22:28.609 Mustafa Raja: So, New York time, right?
234 00:22:30.110 ⇒ 00:22:31.669 Awaish Kumar: It’s Easter time, it’s the same.
235 00:22:32.580 ⇒ 00:22:37.639 Mustafa Raja: It’s this… oh yeah, American New York. And then 5.30, you said?
236 00:22:37.640 ⇒ 00:22:38.920 Awaish Kumar: 4440.
237 00:22:40.370 ⇒ 00:22:42.100 Mustafa Raja: 4.45, does that not work?
238 00:22:42.780 ⇒ 00:22:47.520 Awaish Kumar: Yeah, it was… it was… yeah, in 15 minutes, we will have some orders, and… Then.
239 00:22:50.060 ⇒ 00:22:51.179 Mustafa Raja: Does this look good?
240 00:22:53.560 ⇒ 00:22:56.949 Awaish Kumar: Yeah, I’m saying in 15 minutes it might have extra orders.
241 00:22:57.090 ⇒ 00:23:00.419 Awaish Kumar: If it is possible, we can do 440, then it’s fine.
242 00:23:00.420 ⇒ 00:23:02.739 Mustafa Raja: No, I don’t think we can do 440.
243 00:23:02.740 ⇒ 00:23:06.319 Awaish Kumar: Maybe let’s change the time for Tableau to 4.45.
244 00:23:08.170 ⇒ 00:23:10.709 Awaish Kumar: So save it, and change the time for Tableau.
245 00:23:10.860 ⇒ 00:23:11.670 Awaish Kumar: Excellent.
246 00:23:11.940 ⇒ 00:23:13.370 Awaish Kumar: I don’t know how to do that.
247 00:23:13.640 ⇒ 00:23:14.900 Mustafa Raja: Yeah, me neither.
248 00:23:22.230 ⇒ 00:23:25.490 Awaish Kumar: It’s not in here, it’s in the sources, extracts.
249 00:23:25.750 ⇒ 00:23:34.600 Awaish Kumar: So, it’s like some… I think it is the way… I think he… Tammy showed some screenshots.
250 00:23:34.940 ⇒ 00:23:36.059 Awaish Kumar: On how to do that.
251 00:23:37.010 ⇒ 00:23:38.430 Awaish Kumar: In the Slack, right?
252 00:24:11.770 ⇒ 00:24:12.730 Mustafa Raja: What?
253 00:24:17.520 ⇒ 00:24:19.750 Awaish Kumar: No, no, you have to go to the source, I think.
254 00:24:20.870 ⇒ 00:24:21.930 Mustafa Raja: Okay.
255 00:24:22.260 ⇒ 00:24:24.949 Awaish Kumar: The source gets extracted, not the dashboard.
256 00:24:25.400 ⇒ 00:24:29.570 Awaish Kumar: The data sources, maybe you can… Click on one of them.
257 00:24:31.890 ⇒ 00:24:32.990 Mustafa Raja: Oh.
258 00:24:37.530 ⇒ 00:24:39.310 Awaish Kumar: Change the frequency or something.
259 00:24:41.630 ⇒ 00:24:42.390 Awaish Kumar: Yeah.
260 00:24:44.920 ⇒ 00:24:46.949 Awaish Kumar: Extract references.
261 00:24:49.390 ⇒ 00:24:53.190 Awaish Kumar: Click on the Extract Refreshes on the second tab.
262 00:24:54.650 ⇒ 00:25:02.169 Mustafa Raja: And the second tab… All is… oh, 440. Hmm. How do we edit this?
263 00:25:06.130 ⇒ 00:25:09.170 Mustafa Raja: I think the owner might… hmm, okay.
264 00:25:09.380 ⇒ 00:25:11.670 Awaish Kumar: Change frequency. Change frequency.
265 00:25:14.180 ⇒ 00:25:15.530 Mustafa Raja: 45…
266 00:25:17.310 ⇒ 00:25:19.299 Awaish Kumar: Yeah, don’t change anything else.
267 00:25:19.510 ⇒ 00:25:20.480 Awaish Kumar: Diamond.
268 00:25:22.200 ⇒ 00:25:23.300 Mustafa Raja: Okay, 45…
269 00:25:23.300 ⇒ 00:25:24.410 Awaish Kumar: The one as well.
270 00:25:25.400 ⇒ 00:25:25.900 Mustafa Raja: And…
271 00:25:25.900 ⇒ 00:25:27.139 Awaish Kumar: Genesis.
272 00:25:27.250 ⇒ 00:25:28.140 Mustafa Raja: Yeah.
273 00:25:29.250 ⇒ 00:25:30.739 Mustafa Raja: This one…
274 00:25:35.870 ⇒ 00:25:48.590 Mustafa Raja: Change it to 445… Okay, and then… let’s see… Okay.
275 00:25:48.960 ⇒ 00:25:51.280 Awaish Kumar: Okay, yeah, let’s see how it…
276 00:25:51.300 ⇒ 00:25:54.250 Mustafa Raja: Let me save this also…
277 00:25:59.030 ⇒ 00:26:01.229 Awaish Kumar: Okay, thank you, bye.
278 00:26:01.770 ⇒ 00:26:03.880 Mustafa Raja: Yeah, thank you, bye.