Meeting Title: ABC Standup Date: 2025-08-08 Meeting participants: Mustafa Raja, Casie Aviles, Amber Lin, Vashdev Heerani, Awaish Kumar
WEBVTT
1 00:01:11.370 ⇒ 00:01:12.570 Mustafa Raja: Hey, Casey?
2 00:01:15.190 ⇒ 00:01:16.569 Casie Aviles: Hey! Hey! How are you?
3 00:01:17.320 ⇒ 00:01:18.680 Mustafa Raja: Yeah, I’m doing good.
4 00:01:21.010 ⇒ 00:01:21.890 Casie Aviles: Nice.
5 00:01:21.890 ⇒ 00:01:22.420 Amber Lin: Oh!
6 00:01:24.470 ⇒ 00:01:25.350 Casie Aviles: Hey! Amber.
7 00:01:28.570 ⇒ 00:01:35.000 Amber Lin: I’ve combined now, 3 standups in this one. So lots of stuff to run through.
8 00:01:35.260 ⇒ 00:01:39.300 Amber Lin: Let me see if I’ve correctly invited everybody here.
9 00:01:39.990 ⇒ 00:01:47.319 Amber Lin: Okay, it’s good, since just you 2 are here for now let’s go through.
10 00:01:48.220 ⇒ 00:01:52.809 Amber Lin: Oh, let’s go through
11 00:01:57.300 ⇒ 00:01:58.790 Amber Lin: for ABC.
12 00:02:08.400 ⇒ 00:02:15.440 Amber Lin: Oh, do we manage, copy and paste this in the mechanical central Doc.
13 00:02:15.984 ⇒ 00:02:22.190 Casie Aviles: Yes, you can. Can you click on the this ticket? Okay, thank you. Yes, save.
14 00:02:24.190 ⇒ 00:02:25.539 Casie Aviles: I’ve added this.
15 00:02:25.670 ⇒ 00:02:31.240 Casie Aviles: So this is their mechanical central Doc. I pasted our draft.
16 00:02:31.870 ⇒ 00:02:35.340 Casie Aviles: which was the one we took from their spreadsheet.
17 00:02:36.830 ⇒ 00:02:39.570 Casie Aviles: I put it at the bottom, most part.
18 00:02:40.670 ⇒ 00:02:43.399 Amber Lin: Awesome. Okay, I’ll close this.
19 00:02:47.280 ⇒ 00:02:53.270 Amber Lin: And then, how’s the inspector issue going? Are you guys meeting with them again?
20 00:02:55.130 ⇒ 00:03:02.193 Casie Aviles: We? We, I there’s no, we don’t have a meeting scheduled. I I was asking for a review if we could.
21 00:03:02.960 ⇒ 00:03:04.550 Casie Aviles: we’re good with that.
22 00:03:06.520 ⇒ 00:03:17.499 Casie Aviles: But yeah, I think what for now, like what I can say is that I’ve been actively working to improve that but that involved a lot of manual checking as well.
23 00:03:19.090 ⇒ 00:03:20.000 Casie Aviles: So what
24 00:03:20.290 ⇒ 00:03:27.040 Casie Aviles: so for those errors that I’ve recreated and resolved they they should be on like the doc that I shared
25 00:03:28.700 ⇒ 00:03:35.529 Casie Aviles: But what I will say is, this will still not be what I’m yeah, based on just what I think.
26 00:03:35.930 ⇒ 00:03:40.425 Casie Aviles: This will not be like completely, 100% error free. Still,
27 00:03:41.550 ⇒ 00:03:47.450 Casie Aviles: and there are a lot of factors to that. So number one is also like we need to reevaluate.
28 00:03:47.650 ⇒ 00:03:49.369 Casie Aviles: probably how we set it up.
29 00:03:50.060 ⇒ 00:03:54.140 Casie Aviles: I still think the idea behind the master inspector Sheet is good.
30 00:03:54.360 ⇒ 00:03:54.950 Casie Aviles: It’s just.
31 00:03:54.950 ⇒ 00:03:55.400 Amber Lin: Okay.
32 00:03:55.400 ⇒ 00:04:01.729 Casie Aviles: The execution probably needs to be re-evaluated, and I think I would need some support. There.
33 00:04:02.150 ⇒ 00:04:02.860 Amber Lin: Okay.
34 00:04:04.240 ⇒ 00:04:11.709 Casie Aviles: Yes, that’s 1 thing, and there should be like a broader fix. Because what? Why, what I did these past few days is just take a short term fix.
35 00:04:12.100 ⇒ 00:04:14.540 Casie Aviles: and you know I’m I’m still kind of
36 00:04:14.960 ⇒ 00:04:19.439 Casie Aviles: worried that there might still be things I missed just because I’m not the domain expert.
37 00:04:21.339 ⇒ 00:04:28.313 Casie Aviles: So I mean, like I’m not. I don’t know. Like everything that I might miss, because they know the inspectors right and
38 00:04:29.520 ⇒ 00:04:42.400 Casie Aviles: so I guess I’m not sure like how we bridge that gap. Maybe there should be like a way for them and me to work to have a working session. I don’t know if that helps, but
39 00:04:42.700 ⇒ 00:04:44.939 Casie Aviles: those are just things at the top of my head.
40 00:04:45.750 ⇒ 00:04:56.129 Amber Lin: I see. Okay, yeah, I think a working session might help. But probably we should look at how like how we set up the master inspector sheet.
41 00:04:56.830 ⇒ 00:05:06.099 Amber Lin: I can help look at it. I just don’t know how much help I would be which is written spreadsheets, but I I know he is quite busy, so.
42 00:05:06.100 ⇒ 00:05:07.080 Casie Aviles: Yes, he is.
43 00:05:07.080 ⇒ 00:05:10.520 Amber Lin: I’ll do that here.
44 00:05:13.360 ⇒ 00:05:19.670 Casie Aviles: Is there anything like I? I can do immediately right now, in order to help you with that, or.
45 00:05:20.350 ⇒ 00:05:24.250 Amber Lin: Oh, see!
46 00:05:25.510 ⇒ 00:05:26.893 Casie Aviles: Do you need to like
47 00:05:28.580 ⇒ 00:05:33.769 Casie Aviles: Let them know now that it’s working? Or is there like a time? Yeah.
48 00:05:33.960 ⇒ 00:05:40.420 Amber Lin: Oh, I know we paused it for now, right? Because we just paused.
49 00:05:40.600 ⇒ 00:05:44.720 Amber Lin: What we have for now and then we’re still doing the testing.
50 00:05:45.460 ⇒ 00:05:46.540 Casie Aviles: Yes, yes.
51 00:05:54.290 ⇒ 00:06:02.390 Amber Lin: Oh, we can try to.
52 00:06:03.770 ⇒ 00:06:09.909 Amber Lin: Okay, when are you online? Until.
53 00:06:11.810 ⇒ 00:06:17.520 Casie Aviles: I’ll be online until oh, it’s probably 7 Am. My time.
54 00:06:18.890 ⇒ 00:06:24.660 Amber Lin: Oh! Which is which would be Oh.
55 00:06:24.930 ⇒ 00:06:27.599 Casie Aviles: It’s I’m not sure la time, but.
56 00:06:28.750 ⇒ 00:06:31.829 Amber Lin: For central time for Uton’s time. What what would that be?
57 00:06:32.380 ⇒ 00:06:38.010 Casie Aviles: That would be 6 Pm. I think this time.
58 00:06:38.810 ⇒ 00:06:46.250 Amber Lin: Oh, okay, I’m gonna put a placeholder just so that I remember to look at the inspector sheet.
59 00:06:50.760 ⇒ 00:07:00.170 Amber Lin: I’m just gonna put a placeholder. I’m gonna invite you you guys. Casey, are you the only one working on the inspector sheet? Or should I invite both of you.
60 00:07:03.160 ⇒ 00:07:04.930 Casie Aviles: Both of who me and Uta.
61 00:07:05.737 ⇒ 00:07:11.990 Amber Lin: You tell me, Mustafa, should I invite Mustafa on the instructor sheet as well? Are you guys both working on it?
62 00:07:12.390 ⇒ 00:07:14.920 Casie Aviles: It’s mostly me working on it.
63 00:07:15.200 ⇒ 00:07:16.769 Amber Lin: Okay. Sounds good.
64 00:07:22.870 ⇒ 00:07:24.649 Casie Aviles: Okay. Thank you.
65 00:07:25.570 ⇒ 00:07:30.710 Amber Lin: Yeah, okay, I’ll send that and then
66 00:07:31.500 ⇒ 00:07:35.130 Amber Lin: 1st step. How is the this ticket?
67 00:07:38.800 ⇒ 00:07:39.890 Casie Aviles: Oh, sorry. Your screen. 8.
68 00:07:39.890 ⇒ 00:07:45.779 Amber Lin: Oh, sorry I’m not sharing my screen here, this one, the transcript Api.
69 00:07:46.670 ⇒ 00:07:50.990 Vashdev Heerani: Yes, I I pushed the code for for this this one.
70 00:07:50.990 ⇒ 00:07:51.550 Amber Lin: Oh!
71 00:07:51.730 ⇒ 00:07:54.389 Vashdev Heerani: So it it should be in the Pr.
72 00:07:55.090 ⇒ 00:07:55.610 Amber Lin: Awesome.
73 00:07:56.020 ⇒ 00:07:58.319 Amber Lin: Did you tag a wish to review.
74 00:07:59.400 ⇒ 00:08:02.800 Vashdev Heerani: Nope, I just is the Pr.
75 00:08:03.350 ⇒ 00:08:04.830 Amber Lin: Oh, okay. Sounds good.
76 00:08:04.980 ⇒ 00:08:09.500 Vashdev Heerani: I I ask him in the in the slack message.
77 00:08:09.820 ⇒ 00:08:11.830 Amber Lin: Okay, yeah. Sounds good.
78 00:08:11.990 ⇒ 00:08:13.270 Amber Lin: Oh.
79 00:08:23.720 ⇒ 00:08:27.400 Amber Lin: alright. Let’s look at data platform.
80 00:08:27.710 ⇒ 00:08:28.700 Amber Lin: Oh, wow!
81 00:08:31.505 ⇒ 00:08:39.490 Amber Lin: Okay, this is done.
82 00:08:44.422 ⇒ 00:08:47.499 Amber Lin: Vasha, do you have the modeling tickets you need.
83 00:08:49.793 ⇒ 00:08:51.079 Vashdev Heerani: Nope, Nope.
84 00:08:51.430 ⇒ 00:09:04.479 Amber Lin: I see I need a way to help me define what modeling is needed. But, Casey, how is these? I guess. How is this linear dashboard? Mvp.
85 00:09:05.720 ⇒ 00:09:09.750 Casie Aviles: Oh, no, I haven’t really gotten any progress here yet.
86 00:09:10.370 ⇒ 00:09:15.160 Amber Lin: Oh, okay, would you have today time today to look into this.
87 00:09:18.460 ⇒ 00:09:22.902 Casie Aviles: Okay, I’ll I’ll try. I’ll move stuff out of the way. If this is
88 00:09:23.867 ⇒ 00:09:25.769 Amber Lin: What other stuff do you have.
89 00:09:26.440 ⇒ 00:09:29.568 Casie Aviles: I just have, like the internal AI stuff.
90 00:09:30.336 ⇒ 00:09:31.090 Amber Lin: I see
91 00:09:31.742 ⇒ 00:09:45.079 Amber Lin: I think on that. Let them know. I think I think he’ll be able to tell you. Hey? Do I do this first, st or do that first.st I do know that since they’re both in internal they’re less
92 00:09:45.190 ⇒ 00:09:50.730 Amber Lin: priority than the client projects, but I don’t know how he decides between the data platform and the AI team.
93 00:09:51.690 ⇒ 00:10:03.339 Amber Lin: Okay, yeah, let me just send a quick message in data platform data hold on
94 00:10:09.360 ⇒ 00:10:10.600 Amber Lin: or
95 00:10:13.960 ⇒ 00:10:15.290 Amber Lin: question mark.
96 00:10:15.530 ⇒ 00:10:16.810 Amber Lin: And the
97 00:10:20.440 ⇒ 00:10:22.690 Amber Lin: anyhow, we
98 00:10:33.970 ⇒ 00:10:37.589 Amber Lin: alright just making sure that there’s no modeling tickets here.
99 00:10:38.481 ⇒ 00:10:42.479 Amber Lin: Nope, okay, so that’s my data platform.
100 00:10:42.690 ⇒ 00:10:46.009 Amber Lin: Want to touch on insomnia cookies. Real quick.
101 00:10:47.432 ⇒ 00:10:55.359 Amber Lin: Question for Mustafa. How is it going on? Insomic cookies.
102 00:10:57.520 ⇒ 00:11:02.199 Mustafa Raja: Yeah, I was I was firstly only assigned the.
103 00:11:04.170 ⇒ 00:11:04.720 Amber Lin: Up.
104 00:11:05.210 ⇒ 00:11:11.029 Mustafa Raja: Spike which I worked on, and I guess, for the other tickets we need to. We need to talk about them.
105 00:11:13.903 ⇒ 00:11:15.770 Amber Lin: Sorry. Let me share screen.
106 00:11:21.780 ⇒ 00:11:25.780 Amber Lin: So do you know, if we have a phrase Api access.
107 00:11:25.780 ⇒ 00:11:26.999 Mustafa Raja: Yeah, we do.
108 00:11:27.430 ⇒ 00:11:27.870 Amber Lin: Okay.
109 00:11:28.362 ⇒ 00:11:34.769 Mustafa Raja: Because I also performed testing, using the Braze Api key fetch
110 00:11:35.260 ⇒ 00:11:50.729 Mustafa Raja: and confirmed that we can get the required data to fill. Fill up the sheets, although I wasn’t able to sign in to Microsoft account to access the sheets. They said, it’s something with the location.
111 00:11:51.214 ⇒ 00:11:56.600 Mustafa Raja: So maybe I’m in Pakistan, and the account was 1st logged in in us.
112 00:11:56.900 ⇒ 00:11:58.620 Mustafa Raja: That may be the issue.
113 00:12:00.270 ⇒ 00:12:03.530 Mustafa Raja: So it’s something we might need to raise with them.
114 00:12:04.750 ⇒ 00:12:05.510 Amber Lin: I see.
115 00:12:05.710 ⇒ 00:12:09.489 Mustafa Raja: Yeah, I’ve also tagged that in the spike ticket.
116 00:12:11.325 ⇒ 00:12:12.495 Amber Lin: I see
117 00:12:13.190 ⇒ 00:12:23.449 Amber Lin: Let’s see, I I do recall their access is pretty funky. I also got locked out, and then I had to figure out how to get back in so.
118 00:12:24.830 ⇒ 00:12:29.469 Amber Lin: Casey, were you able to log in? I know you have 0 contacts on this client.
119 00:12:29.690 ⇒ 00:12:38.809 Mustafa Raja: Yeah, for this. Okay, the ticket for Casey. We need the credentials for Google sheets.
120 00:12:39.490 ⇒ 00:12:40.440 Mustafa Raja: First.st
121 00:12:41.970 ⇒ 00:12:43.740 Amber Lin: Oh, okay, let me.
122 00:12:43.740 ⇒ 00:12:46.049 Mustafa Raja: Yeah, I’ve I’ve created a ticket for Robert.
123 00:12:46.730 ⇒ 00:12:49.361 Mustafa Raja: I’ve created a ticket for Robert.
124 00:12:49.800 ⇒ 00:12:50.400 Amber Lin: Oh!
125 00:12:50.400 ⇒ 00:12:53.239 Mustafa Raja: So he can go and ask for it. Yeah, yeah.
126 00:12:54.370 ⇒ 00:12:55.659 Amber Lin: Wait. Where is?
127 00:12:56.820 ⇒ 00:13:02.170 Amber Lin: Oh, sorry I I see. I remember it’s a Google sheets that one.
128 00:13:02.510 ⇒ 00:13:04.370 Mustafa Raja: Yeah, this one.
129 00:13:05.520 ⇒ 00:13:11.120 Amber Lin: Oh, okay, I’m just gonna leave it here.
130 00:13:11.820 ⇒ 00:13:17.429 Amber Lin: Google sheets, why do we need Google sheets? Just again?
131 00:13:17.825 ⇒ 00:13:24.159 Mustafa Raja: We need to. We need to insert data from breeze into the sheets. Right?
132 00:13:25.490 ⇒ 00:13:30.209 Amber Lin: Yes. Are we using their sheet or our data sheet?
133 00:13:31.060 ⇒ 00:13:41.960 Mustafa Raja: I I believe the sheet is from them. The the links in sop, Doc from notion. Were
134 00:13:41.960 ⇒ 00:13:44.070 Mustafa Raja: protected by Microsoft soft.
135 00:13:44.310 ⇒ 00:13:49.110 Mustafa Raja: Yeah, they are Microsoft. So do we need Google credentials? Or
136 00:13:49.110 ⇒ 00:13:55.760 Mustafa Raja: I believe I believe those the login would take us to the Google Sheet. Right?
137 00:13:57.120 ⇒ 00:14:00.330 Amber Lin: Wait. What Google Sheet, are you talking about?
138 00:14:01.890 ⇒ 00:14:04.270 Mustafa Raja: Is it not Google Sheet? I thought it was Google Sheet.
139 00:14:05.060 ⇒ 00:14:06.710 Amber Lin: Oh, I see!
140 00:14:06.710 ⇒ 00:14:07.960 Mustafa Raja: Performance, yeah.
141 00:14:08.210 ⇒ 00:14:09.490 Amber Lin: Marketing, performance.
142 00:14:09.490 ⇒ 00:14:11.340 Mustafa Raja: Oh, it’s excel! Oh, sorry!
143 00:14:11.340 ⇒ 00:14:16.450 Amber Lin: Yeah, it’s it’s yeah all good. This is Microsoft. Excel, my.
144 00:14:16.450 ⇒ 00:14:20.489 Mustafa Raja: Yeah, yeah, we just need access to this. We need access to this.
145 00:14:20.490 ⇒ 00:14:22.859 Amber Lin: Excel credentials.
146 00:14:23.732 ⇒ 00:14:40.030 Mustafa Raja: Yeah, maybe maybe Casey needs to look into how we can connect to this sheet to update this. So we can provide context to Robert on how? What needs to be asked.
147 00:14:41.325 ⇒ 00:14:49.230 Amber Lin: There’s also an option. Why is the wish? A wish is here, too. Well, I mean, we’re pulling data from.
148 00:14:49.350 ⇒ 00:14:53.090 Amber Lin: Let’s talk about brace. First, st right? Braze is a
149 00:14:53.686 ⇒ 00:15:01.419 Amber Lin: we have the Api there. We could create our own spreadsheet like we can create our own Google sheet
150 00:15:01.550 ⇒ 00:15:10.477 Amber Lin: and then pull it into like, pull it into here like at the end of the day. We still we will still need to.
151 00:15:11.360 ⇒ 00:15:18.570 Amber Lin: We’ll still need Microsoft access. But we don’t have to. I don’t know, do we? I don’t know if we have to put it here.
152 00:15:19.930 ⇒ 00:15:23.999 Amber Lin: but if Microsoft is a blocker, I I will go. Ask that.
153 00:15:24.160 ⇒ 00:15:26.610 Mustafa Raja: Yeah, I just thought that
154 00:15:26.930 ⇒ 00:15:34.649 Mustafa Raja: the other sheet, the second sheet that needs to be populated depended on this marketing performance tracker sheet.
155 00:15:34.830 ⇒ 00:15:42.999 Mustafa Raja: So maybe if we populated marketing performance tracker, we can craft a formula for the other sheet.
156 00:15:44.050 ⇒ 00:15:44.740 Amber Lin: Oh!
157 00:15:45.670 ⇒ 00:15:47.360 Mustafa Raja: That was my thinking.
158 00:15:48.261 ⇒ 00:15:49.719 Amber Lin: Which one do you think?
159 00:15:51.890 ⇒ 00:15:56.500 Awaish Kumar: Yeah. 1st of all, like that excel sheet. I’m seeing.
160 00:15:56.830 ⇒ 00:15:59.049 Amber Lin: Is that shared between.
161 00:16:00.910 ⇒ 00:16:01.850 Awaish Kumar: The Kazoo?
162 00:16:02.360 ⇒ 00:16:05.929 Awaish Kumar: Or is it a like local version of it?
163 00:16:07.730 ⇒ 00:16:09.430 Amber Lin: This is, this is shared.
164 00:16:10.570 ⇒ 00:16:14.810 Awaish Kumar: Okay. So like, multiple people can come and edit this right?
165 00:16:15.090 ⇒ 00:16:15.670 Amber Lin: Yep.
166 00:16:16.220 ⇒ 00:16:20.290 Awaish Kumar: So there must be some way to to get in programmatically.
167 00:16:20.780 ⇒ 00:16:27.510 Awaish Kumar: So yeah, like, Casey can have a spike on how we can program programmatically access this.
168 00:16:30.520 ⇒ 00:16:31.070 Mustafa Raja: Yeah.
169 00:16:31.330 ⇒ 00:16:37.379 Mustafa Raja: And and the second sheet is it totally totally based on this one.
170 00:16:39.755 ⇒ 00:16:42.329 Amber Lin: I am logged out again.
171 00:16:43.310 ⇒ 00:16:50.230 Amber Lin: So let’s look at here. Right? So we have to fill in a few sections.
172 00:16:50.940 ⇒ 00:17:10.079 Amber Lin: This this sheet that comes from brace that has email and push. It goes into this section. So the sum of the 2 push Ios and push Android goes here. And the email goes here so that she fills in like this box.
173 00:17:10.424 ⇒ 00:17:11.429 Awaish Kumar: Get the data.
174 00:17:12.670 ⇒ 00:17:13.200 Amber Lin: Hmm!
175 00:17:15.270 ⇒ 00:17:16.020 Amber Lin: I’m sorry.
176 00:17:16.020 ⇒ 00:17:18.730 Awaish Kumar: Is it for a day or aggregated data, or.
177 00:17:19.963 ⇒ 00:17:26.679 Amber Lin: So it’s for a date. So every morning it’s a morning snapshot of the free previous day. Essentially.
178 00:17:27.260 ⇒ 00:17:28.020 Awaish Kumar: Okay.
179 00:17:30.840 ⇒ 00:17:38.960 Amber Lin: Yeah. And so that’s for this one’s for braze. And then we also have the Google App, maybe
180 00:17:39.230 ⇒ 00:17:41.120 Amber Lin: face of Meta. Let’s go here.
181 00:17:42.500 ⇒ 00:17:48.749 Mustafa Raja: Maybe we should do another spike to see if we can craft a formula for this, because
182 00:17:49.326 ⇒ 00:17:55.900 Mustafa Raja: if you want to automate this part, too. I don’t think there’s any other way than crafting a formula.
183 00:17:57.640 ⇒ 00:17:57.970 Amber Lin: Okay.
184 00:17:58.247 ⇒ 00:18:00.189 Mustafa Raja: Gissi, what do you think about this.
185 00:18:00.990 ⇒ 00:18:07.430 Casie Aviles: Yeah, yeah, we could definitely look into a way to to make this more dynamic and automatic.
186 00:18:07.430 ⇒ 00:18:08.150 Mustafa Raja: Yeah.
187 00:18:08.580 ⇒ 00:18:09.020 Casie Aviles: Gross.
188 00:18:09.020 ⇒ 00:18:09.600 Amber Lin: Yeah.
189 00:18:09.600 ⇒ 00:18:13.870 Casie Aviles: That’s often causes a problem when we have to manually sync 2 things.
190 00:18:14.390 ⇒ 00:18:15.310 Amber Lin: Yeah, yeah.
191 00:18:15.310 ⇒ 00:18:26.880 Amber Lin: This sheet also is a little bit funky because it it’s it just goes in this way. And then it goes another layer here. So it’s essentially
192 00:18:27.050 ⇒ 00:18:34.329 Amber Lin: update. It’s like a calendar format. Almost. So I don’t know how you’re gonna find what cell we need to be in.
193 00:18:37.682 ⇒ 00:18:41.060 Mustafa Raja: Yeah, this, this definitely is a problem.
194 00:18:42.940 ⇒ 00:18:48.499 Mustafa Raja: Maybe I still believe a spike might help us.
195 00:18:49.230 ⇒ 00:18:58.550 Amber Lin: Yeah, totally. Can you help me title this spike? I’ll leave this credentials as is because we need that either way. But I’m gonna
196 00:18:58.870 ⇒ 00:19:05.929 Amber Lin: say, sprays Spike, what do we do.
197 00:19:06.520 ⇒ 00:19:07.520 Mustafa Raja: Hmm,
198 00:19:12.270 ⇒ 00:19:21.399 Mustafa Raja: yeah. So the purpose of this would be to see if based on marketing sheet, we can craft a formula to populate
199 00:19:21.920 ⇒ 00:19:29.509 Mustafa Raja: email Android. And Ios, it was those columns, right? Email Android. And Ios, yeah.
200 00:19:30.220 ⇒ 00:19:32.220 Amber Lin: Own marketing.
201 00:19:32.650 ⇒ 00:19:36.900 Amber Lin: So email push, which includes.
202 00:19:38.798 ⇒ 00:19:43.480 Awaish Kumar: Mean by formula like, Yeah, it’s coming to quickly from Braze.
203 00:19:45.271 ⇒ 00:19:53.709 Mustafa Raja: Yeah, the the values are coming from brace, but but the but those values will be used to populate another sheet. The marketing sheet.
204 00:19:54.670 ⇒ 00:19:57.212 Awaish Kumar: Are not this.
205 00:19:58.595 ⇒ 00:20:01.490 Mustafa Raja: Yeah, yeah, yeah, yeah, yeah, yeah.
206 00:20:02.160 ⇒ 00:20:03.710 Awaish Kumar: Yeah, it’s just okay
207 00:20:03.710 ⇒ 00:20:10.579 Awaish Kumar: of another sheet, right where we, these values are being just copied over. It’s not. There’s no like calculation.
208 00:20:11.220 ⇒ 00:20:24.899 Mustafa Raja: Yeah, but but we still. But but we still need need a way to figure out the cells that need to be filled out now, because we see that the sheet is formulated in very calendar. Like manner.
209 00:20:26.650 ⇒ 00:20:34.060 Awaish Kumar: Yeah, yeah. But I understand that, like, it’s in some format right now. And we need to find a way to
210 00:20:34.160 ⇒ 00:20:39.990 Awaish Kumar: update that sheet. But like it’s just copying the values which are coming from praise right.
211 00:20:40.860 ⇒ 00:20:53.410 Amber Lin: Yeah, the only calculation here is to sum up. So to add the Ios and android. So we add, these 2 up
212 00:20:53.900 ⇒ 00:20:55.910 Amber Lin: and the email just email.
213 00:20:56.930 ⇒ 00:21:01.369 Mustafa Raja: Okay? And the SMS. One is, we are we? We are not concerned with it right?
214 00:21:02.230 ⇒ 00:21:03.190 Amber Lin: I’m sorry.
215 00:21:03.380 ⇒ 00:21:08.809 Mustafa Raja: On the other sheet. There’s an SMS raw between these email.
216 00:21:08.810 ⇒ 00:21:12.849 Amber Lin: Yeah, they’re not doing SMS. So we just don’t have the data. Now.
217 00:21:13.140 ⇒ 00:21:13.810 Mustafa Raja: Okay.
218 00:21:14.220 ⇒ 00:21:18.270 Amber Lin: Yeah, so let’s so there’s
219 00:21:18.690 ⇒ 00:21:26.350 Amber Lin: sounds like there’s more than one spike. So identify, why sell?
220 00:21:26.810 ⇒ 00:21:30.690 Amber Lin: And why?
221 00:21:32.900 ⇒ 00:21:36.549 Amber Lin: So there’s we need to identify the cell. Who’s gonna do that?
222 00:21:38.300 ⇒ 00:21:46.290 Awaish Kumar: But like we that’s like hard, like the structure, the excel structure is fixed
223 00:21:46.430 ⇒ 00:22:00.979 Awaish Kumar: right? There’s we know where which sale is that? What row and column. So that’s not a problem. It’s just writing a python script. And then defining that like sale number, for example, row number 27,
224 00:22:01.350 ⇒ 00:22:11.260 Awaish Kumar: B, CD, for example, is going to be value from this or that, like, it’s like hard coding. These things like to have the same structure.
225 00:22:12.010 ⇒ 00:22:14.810 Amber Lin: Okay, code.
226 00:22:15.330 ⇒ 00:22:15.800 Awaish Kumar: Yeah, right.
227 00:22:15.800 ⇒ 00:22:22.320 Mustafa Raja: So amber. Do we know? Do we know that they create a new table for every day
228 00:22:22.450 ⇒ 00:22:23.290 Mustafa Raja: in the sheet.
229 00:22:23.745 ⇒ 00:22:29.670 Amber Lin: I think. Say, this is August. I think they created all the August
230 00:22:30.000 ⇒ 00:22:36.669 Amber Lin: days. Let me check. Yeah. They created everything for August. So this should be fixed.
231 00:22:37.120 ⇒ 00:22:47.019 Amber Lin: and then let’s check, I think, for July. They also did this, so I think they copy it over.
232 00:22:50.400 ⇒ 00:22:51.080 Mustafa Raja: Okay.
233 00:22:51.670 ⇒ 00:22:52.830 Amber Lin: Yeah, so.
234 00:22:52.830 ⇒ 00:22:53.440 Mustafa Raja: Thank you.
235 00:23:01.820 ⇒ 00:23:06.460 Amber Lin: Okay, so I’m gonna copy that here.
236 00:23:10.480 ⇒ 00:23:12.240 Amber Lin: So what are this?
237 00:23:13.720 ⇒ 00:23:16.829 Amber Lin: So what are some other things we need to figure out
238 00:23:20.970 ⇒ 00:23:23.350 Amber Lin: how to get? Do we know how to get.
239 00:23:23.350 ⇒ 00:23:25.879 Awaish Kumar: 1st of all, how to connect with this sheet program.
240 00:23:25.880 ⇒ 00:23:28.370 Mustafa Raja: Yeah, that one.
241 00:23:29.130 ⇒ 00:23:29.920 Amber Lin: Okay.
242 00:23:35.760 ⇒ 00:23:38.530 Amber Lin: how to connect with.
243 00:23:39.790 ⇒ 00:23:40.270 Awaish Kumar: Indeed.
244 00:23:44.420 ⇒ 00:23:50.470 Amber Lin: I have a question, do we have to use this sheet? Are we gonna use this sheet as our intermediate
245 00:23:50.860 ⇒ 00:23:56.380 Amber Lin: layer, or are we gonna directly. Put it into here.
246 00:23:58.150 ⇒ 00:24:02.590 Mustafa Raja: I mean, we are going to get that. It’s essentially the same data.
247 00:24:04.490 ⇒ 00:24:06.079 Mustafa Raja: So do we need the sheet.
248 00:24:07.900 ⇒ 00:24:11.909 Mustafa Raja: Are they going to use this or not. If they are going to use this, then maybe we should
249 00:24:12.240 ⇒ 00:24:14.139 Mustafa Raja: keep going with this, else we can.
250 00:24:15.130 ⇒ 00:24:17.630 Amber Lin: Okay? Good point. Let me check.
251 00:24:18.670 ⇒ 00:24:27.910 Amber Lin: So cause when we say connect to daily impact scorecard, I think it’s
252 00:24:28.060 ⇒ 00:24:35.050 Amber Lin: if we’re going from one excel sheet to a different excel sheet. It’s a excel formula.
253 00:24:35.500 ⇒ 00:24:36.499 Mustafa Raja: Yeah, yeah, yeah.
254 00:24:36.500 ⇒ 00:24:42.700 Amber Lin: If we’re going to brace to excel, we need to figure out how to go from brace to excel. And we have to do that.
255 00:24:44.890 ⇒ 00:24:45.570 Mustafa Raja: Yeah.
256 00:24:46.556 ⇒ 00:24:54.049 Amber Lin: Raise student. So just gonna do this. And I’m gonna add a ticket to clarify if we need
257 00:24:54.870 ⇒ 00:24:56.050 Amber Lin: worries.
258 00:24:56.630 ⇒ 00:25:01.190 Amber Lin: Do stakeholders use?
259 00:25:01.590 ⇒ 00:25:02.410 Amber Lin: Oh.
260 00:25:07.080 ⇒ 00:25:08.550 Amber Lin: they use this?
261 00:25:22.510 ⇒ 00:25:26.930 Amber Lin: Okay? Who’s going to spike on connecting Brace to excel.
262 00:25:28.290 ⇒ 00:25:31.259 Casie Aviles: So yeah, I can and assign that to me.
263 00:25:34.600 ⇒ 00:25:41.740 Amber Lin: Oh, I forgot to add you here. Are you blocked on the Excel access credentials.
264 00:25:43.820 ⇒ 00:25:45.850 Casie Aviles: Let me check. I haven’t checked it yet.
265 00:25:46.550 ⇒ 00:25:47.230 Amber Lin: I see
266 00:25:48.581 ⇒ 00:25:59.639 Amber Lin: I mean, as in the I don’t know if it’s Apis or credentials to be able to write into that document from Braze. I don’t know how it works.
267 00:26:00.320 ⇒ 00:26:03.309 Casie Aviles: Oh, so you’re writing from raise to excel.
268 00:26:03.600 ⇒ 00:26:04.350 Amber Lin: Yeah.
269 00:26:05.820 ⇒ 00:26:09.540 Casie Aviles: Hmm, I’ll yeah. I’ll check first, st because I think
270 00:26:10.000 ⇒ 00:26:12.950 Casie Aviles: I’ll need like a service account for stuff like that.
271 00:26:14.160 ⇒ 00:26:14.850 Amber Lin: I’ve seen.
272 00:26:15.300 ⇒ 00:26:18.699 Amber Lin: Okay. That one we need to confirm on.
273 00:26:19.280 ⇒ 00:26:19.910 Amber Lin: Oh.
274 00:26:19.910 ⇒ 00:26:26.499 Casie Aviles: I I just need to check first.st If I if I can use our service account, or if the I need, we need it from the client.
275 00:26:26.960 ⇒ 00:26:27.966 Amber Lin: I see?
276 00:26:29.150 ⇒ 00:26:30.760 Amber Lin: Yeah, go ahead.
277 00:26:31.890 ⇒ 00:26:41.789 Awaish Kumar: Like to read from Bras like, we have some Api endpoints to it. So like, what we need is Api key, basically to get the data
278 00:26:42.030 ⇒ 00:26:43.099 Awaish Kumar: and then to the right.
279 00:26:43.100 ⇒ 00:26:43.650 Casie Aviles: Nice.
280 00:26:44.370 ⇒ 00:26:45.610 Awaish Kumar: Yeah, like,
281 00:26:46.530 ⇒ 00:26:47.630 Awaish Kumar: If I
282 00:26:49.654 ⇒ 00:26:52.889 Mustafa Raja: Can we open up the document? Spike document?
283 00:26:52.890 ⇒ 00:26:58.219 Awaish Kumar: Senior spike it. It is like hitting some Api endpoints. So do we have the Api.
284 00:26:59.340 ⇒ 00:27:00.490 Amber Lin: Okay? Bye.
285 00:27:00.490 ⇒ 00:27:00.930 Mustafa Raja: As well.
286 00:27:00.930 ⇒ 00:27:01.570 Amber Lin: Bye,
287 00:27:04.633 ⇒ 00:27:06.400 Mustafa Raja: Down, down, down, down, down.
288 00:27:07.980 ⇒ 00:27:11.779 Mustafa Raja: More, more. Let’s open up in the notion.
289 00:27:18.990 ⇒ 00:27:22.920 Mustafa Raja: Yeah. So we have these 2 endpoints in the research
290 00:27:23.100 ⇒ 00:27:35.779 Mustafa Raja: approach. The 1st one gives us all the campaigns, and the second one gives us the data for the campaigns, and the second one gives us everything that we need to fill up the sheets.
291 00:27:36.810 ⇒ 00:27:40.160 Mustafa Raja: The 1st one we need to identify the campaign that we need to fill up.
292 00:27:40.920 ⇒ 00:27:45.140 Awaish Kumar: Okay. But but the question is like, do we have the Api key from the client? Or do we have to ask.
293 00:27:45.946 ⇒ 00:27:47.559 Mustafa Raja: I did create one.
294 00:27:48.700 ⇒ 00:27:50.040 Awaish Kumar: Okay, you have created Api key.
295 00:27:50.040 ⇒ 00:28:00.069 Mustafa Raja: Yeah, yeah, we can. We can. We can create one. The the account that that has been given us from them of brace lets us create api keys.
296 00:28:00.700 ⇒ 00:28:03.319 Awaish Kumar: And same, for, like excel.
297 00:28:03.320 ⇒ 00:28:04.400 Mustafa Raja: No, no, not for x.
298 00:28:04.400 ⇒ 00:28:04.890 Awaish Kumar: So.
299 00:28:04.890 ⇒ 00:28:05.560 Mustafa Raja: Only for break.
300 00:28:05.560 ⇒ 00:28:12.370 Awaish Kumar: It’s an it’s another question like for excel like they are on sharepoint. All the excel files or somewhere else.
301 00:28:12.700 ⇒ 00:28:13.514 Mustafa Raja: Yeah,
302 00:28:15.700 ⇒ 00:28:18.300 Awaish Kumar: They are on sharepoint endpoint account.
303 00:28:20.170 ⇒ 00:28:21.860 Awaish Kumar: Are you able to create.
304 00:28:23.160 ⇒ 00:28:23.610 Mustafa Raja: You saw.
305 00:28:23.610 ⇒ 00:28:29.356 Mustafa Raja: So yeah, yeah. So what happened was, I tried to log in into this
306 00:28:30.612 ⇒ 00:28:41.579 Mustafa Raja: sheet, but they didn’t. Let me log in it said they said it. It was something because of my location or something like that, so I wasn’t able to log in.
307 00:28:41.940 ⇒ 00:28:43.519 Mustafa Raja: But we have the credentials.
308 00:28:43.520 ⇒ 00:28:46.129 Awaish Kumar: But we are able to log in using robots right?
309 00:28:46.130 ⇒ 00:28:46.699 Mustafa Raja: Yeah, yeah.
310 00:28:46.700 ⇒ 00:28:51.690 Awaish Kumar: Maybe we can find there, like some way to create a service user service account.
311 00:28:52.060 ⇒ 00:28:52.640 Mustafa Raja: Yeah.
312 00:28:54.370 ⇒ 00:28:55.030 Amber Lin: Okay.
313 00:28:55.220 ⇒ 00:28:59.390 Awaish Kumar: So so is this. Is this credentials shared in one pass.
314 00:28:59.390 ⇒ 00:29:01.073 Amber Lin: Yeah. It’s in one pass
315 00:29:01.410 ⇒ 00:29:02.740 Awaish Kumar: Okay, then like.
316 00:29:02.740 ⇒ 00:29:04.589 Amber Lin: Is there a call in case you can hold?
317 00:29:04.700 ⇒ 00:29:09.960 Amber Lin: Yeah, if you’re not in the vault, we can ask Rico to add you so.
318 00:29:09.960 ⇒ 00:29:23.249 Awaish Kumar: I’m not in there. But, like Casey, you can log into sharepoint, using robots credential which are available in one pass and fit and can spike like if you can create a service account to connect, to excel sheet.
319 00:29:24.300 ⇒ 00:29:26.939 Awaish Kumar: Yes, yes, that’s what I plan to do.
320 00:29:28.670 ⇒ 00:29:33.220 Amber Lin: Okay, okay, awesome. So that’s for brace.
321 00:29:35.370 ⇒ 00:29:40.590 Amber Lin: I think we already did that right. Do we have that?
322 00:29:42.120 ⇒ 00:29:46.580 Amber Lin: No, that’s the ticket you created?
323 00:29:47.333 ⇒ 00:29:49.500 Amber Lin: Do we still need this.
324 00:29:50.660 ⇒ 00:29:55.050 Mustafa Raja: Build Api. No, I don’t think so. We need this.
325 00:29:55.420 ⇒ 00:29:56.030 Amber Lin: Okay.
326 00:29:58.790 ⇒ 00:29:59.840 Amber Lin: Oh.
327 00:30:03.683 ⇒ 00:30:10.505 Mustafa Raja: And I guess I understand can be deleted, too, because
328 00:30:12.890 ⇒ 00:30:30.550 Amber Lin: Alright. So we get check on Microsoft. I’ll check if they use the marketing one, so we can tell if we need an intermediary or not. And then we write it after we get access to both. I just want, I have a question on Google and
329 00:30:31.210 ⇒ 00:30:40.379 Amber Lin: Meta, so for Google, let me pull up the and you know.
330 00:30:45.000 ⇒ 00:30:45.800 Amber Lin: So
331 00:30:56.460 ⇒ 00:30:58.710 Amber Lin: no, oh, whatever.
332 00:30:58.890 ⇒ 00:31:11.760 Amber Lin: So so for Google, right now we pull from this dashboard and we add the costs in.
333 00:31:13.720 ⇒ 00:31:18.700 Amber Lin: So Google fills in. Say, this shell of this, this cell.
334 00:31:20.630 ⇒ 00:31:29.729 Amber Lin: So we take, we open up their dashboard. We copy that number, and we put it here
335 00:31:30.110 ⇒ 00:31:32.919 Amber Lin: is, how can we automate that.
336 00:31:35.740 ⇒ 00:31:44.850 Awaish Kumar: It’s like similar to braze like we need to for get some Api keys to connect to Google ads and Meta ads. And
337 00:31:45.510 ⇒ 00:31:49.506 Awaish Kumar: bring that data from there to a Google, an Excel sheet.
338 00:31:50.010 ⇒ 00:31:56.670 Awaish Kumar: And yeah, those fields can be filled out the similar way we are. We will be doing for a place.
339 00:31:59.560 ⇒ 00:32:01.200 Amber Lin: Okay. So
340 00:32:02.950 ⇒ 00:32:12.580 Amber Lin: on the Google side, I know Google and Meta will have Apis. I just don’t know if we have access to them. So.
341 00:32:14.130 ⇒ 00:32:17.789 Awaish Kumar: So. And just a suggestion. I don’t know like what data
342 00:32:18.040 ⇒ 00:32:23.050 Awaish Kumar: we are looking for, or do we want to create some
343 00:32:23.370 ⇒ 00:32:30.659 Awaish Kumar: like hit some Api endpoints a big, but we also have a like polyatomic brain forge, instance.
344 00:32:30.870 ⇒ 00:32:38.279 Awaish Kumar: which basically can help us given Api key can help us get the data from Google and Meta to
345 00:32:38.490 ⇒ 00:32:42.690 Awaish Kumar: to some sheets or somewhere.
346 00:32:43.500 ⇒ 00:32:44.330 Amber Lin: Yeah.
347 00:32:44.840 ⇒ 00:33:00.620 Amber Lin: So I think, let me find where it says, so we fill in Google. And Meta.
348 00:33:01.570 ⇒ 00:33:04.749 Awaish Kumar: Yeah, we fill in costs, and we fill in revenue.
349 00:33:09.040 ⇒ 00:33:10.880 Amber Lin: That’s his calculation.
350 00:33:11.200 ⇒ 00:33:15.500 Amber Lin: Yeah, these 2 we have to fill in, which is probably
351 00:33:18.070 ⇒ 00:33:19.410 Amber Lin: Where is it?
352 00:33:23.370 ⇒ 00:33:28.660 Amber Lin: Probably cost. And maybe this is value.
353 00:33:29.160 ⇒ 00:33:31.230 Amber Lin: Or maybe this is revenue.
354 00:33:31.370 ⇒ 00:33:34.520 Amber Lin: So I think that’s what we’re trying to fill in.
355 00:33:37.370 ⇒ 00:33:38.010 Awaish Kumar: Okay.
356 00:33:38.594 ⇒ 00:33:40.790 Amber Lin: So what are the tickets that we need.
357 00:33:42.790 ⇒ 00:33:43.450 Mustafa Raja: Hmm.
358 00:33:44.670 ⇒ 00:33:45.830 Awaish Kumar: It’s the same right like.
359 00:33:45.830 ⇒ 00:33:46.540 Mustafa Raja: Yeah.
360 00:33:46.860 ⇒ 00:33:49.283 Awaish Kumar: Getting the Api key
361 00:33:49.890 ⇒ 00:33:53.000 Mustafa Raja: Yeah, do we have access to something
362 00:33:53.130 ⇒ 00:33:57.669 Mustafa Raja: that we can that can be source of source of truth. For this data.
363 00:34:00.169 ⇒ 00:34:01.369 Amber Lin: You mean the Ap.
364 00:34:01.370 ⇒ 00:34:03.460 Mustafa Raja: Yeah, apa, or something. Yeah.
365 00:34:07.880 ⇒ 00:34:08.440 Amber Lin: Sure.
366 00:34:09.849 ⇒ 00:34:14.149 Mustafa Raja: Right away. We need some. We need some Api key to look into this right.
367 00:34:17.120 ⇒ 00:34:18.080 Awaish Kumar: Yes, yes.
368 00:34:19.719 ⇒ 00:34:26.979 Amber Lin: Okay, so I can confirm. I don’t know if Robert said, if we have it or not,
369 00:34:29.239 ⇒ 00:34:38.639 Amber Lin: could we log in because one of you log into the Google account to verify if we can create one. I don’t know how to, but we do have access to this.
370 00:34:43.139 ⇒ 00:34:47.779 Awaish Kumar: Yeah, like, someone can log in using Robert’s credentials and figure out.
371 00:34:48.320 ⇒ 00:34:49.010 Amber Lin: Okay?
372 00:34:50.219 ⇒ 00:34:52.279 Amber Lin: Who is going to do that?
373 00:34:55.760 ⇒ 00:34:56.969 Mustafa Raja: I can do that.
374 00:34:57.830 ⇒ 00:35:01.419 Amber Lin: Oh, okay, so I’ll assign it to you.
375 00:35:02.270 ⇒ 00:35:07.450 Amber Lin: And then same with Api docs to see what they provide.
376 00:35:08.310 ⇒ 00:35:10.370 Amber Lin: Can I also assign this to you.
377 00:35:11.692 ⇒ 00:35:17.640 Mustafa Raja: This is for the this is related to the Google Api right.
378 00:35:18.100 ⇒ 00:35:19.540 Amber Lin: Yeah. Oh, okay.
379 00:35:19.860 ⇒ 00:35:24.630 Amber Lin: So I’ll I will copy this.
380 00:35:25.500 ⇒ 00:35:27.060 Amber Lin: And for him.
381 00:35:28.960 ⇒ 00:35:36.500 Amber Lin: Okay, I’m gonna delete that one meta side so far.
382 00:35:36.840 ⇒ 00:35:44.000 Awaish Kumar: So if we have data in one excel file in sharepoint to.
383 00:35:44.140 ⇒ 00:35:50.540 Awaish Kumar: is it easy, like, is there any formula to link data from other Google. Excel sheet.
384 00:35:50.730 ⇒ 00:35:53.619 Mustafa Raja: Yeah, that that we will have to figure out.
385 00:35:55.193 ⇒ 00:36:02.160 Mustafa Raja: because it makes sense to put all the data in in one sheet and then route it to the other one.
386 00:36:02.833 ⇒ 00:36:07.539 Mustafa Raja: Because there, there are a lot of different sources. The data is coming from right.
387 00:36:08.770 ⇒ 00:36:35.540 Awaish Kumar: Yeah, my question is more like, like, we have a Excel file where data from brace coming in, and we might need few more where the data from Google ads and Meta is going to come in. Then, like we have to build something to bring all that into the scorecard excel file? Or is there already in sharepoint? There is some like built in way to do that.
388 00:36:36.540 ⇒ 00:36:44.800 Amber Lin: No, they’re all scattered across different different things. They manually pull in all these, all of these cells.
389 00:36:46.120 ⇒ 00:36:46.850 Awaish Kumar: Okay.
390 00:36:47.300 ⇒ 00:36:51.640 Amber Lin: Yeah, Meta, we’re still blocked. Can’t log in
391 00:36:54.490 ⇒ 00:37:02.785 Amber Lin: There’s 1 thing, I think. Now we have uber access. So probably need someone to spike on that as well.
392 00:37:03.790 ⇒ 00:37:09.090 Amber Lin: I have one question about this daily scorecard, so let me
393 00:37:10.510 ⇒ 00:37:20.020 Amber Lin: show this as well. So this is a little bit different. We’re automate. They send an excel via email each morning.
394 00:37:20.210 ⇒ 00:37:21.500 Amber Lin: And then.
395 00:37:22.800 ⇒ 00:37:33.580 Amber Lin: so we’re trying to fill in also on the daily impact sheet. So on here, it’s on the bottom here, just a summary of revenue and
396 00:37:34.100 ⇒ 00:37:36.710 Amber Lin: LY. For revenue, which I don’t know what that is.
397 00:37:36.840 ⇒ 00:37:41.640 Amber Lin: So they send us an email. They send Robert an email and then
398 00:37:41.860 ⇒ 00:37:45.490 Amber Lin: has a fall in it. That we download
399 00:37:45.690 ⇒ 00:37:49.699 Amber Lin: is an Excel sheet. And then we essentially copy over
400 00:37:50.776 ⇒ 00:37:57.070 Amber Lin: these 3 cells. And then these the other
401 00:38:00.400 ⇒ 00:38:07.290 Amber Lin: so the top, these 6 cells, and then copy and paste them there. How can we automate this.
402 00:38:07.650 ⇒ 00:38:08.160 Casie Aviles: Okay.
403 00:38:13.298 ⇒ 00:38:17.210 Mustafa Raja: so so this is. This would also be related to the date. Right.
404 00:38:19.580 ⇒ 00:38:20.200 Amber Lin: Sorry.
405 00:38:20.480 ⇒ 00:38:25.139 Mustafa Raja: This would also be related to the date of that particular table. Right?
406 00:38:25.460 ⇒ 00:38:26.910 Amber Lin: Yeah, so they will.
407 00:38:26.910 ⇒ 00:38:27.600 Mustafa Raja: So, maybe.
408 00:38:27.600 ⇒ 00:38:29.070 Amber Lin: What title.
409 00:38:29.380 ⇒ 00:38:36.099 Mustafa Raja: Yes. So yes. So maybe so. This this sheet. This is also going to be a sheet right.
410 00:38:37.920 ⇒ 00:38:53.760 Mustafa Raja: So the I guess we can figure out the sales the same way. We would be figuring out the sales for email and push. The only thing we need to. I guess worry about is how are we going to automate this download.
411 00:38:54.190 ⇒ 00:38:55.550 Amber Lin: Yeah.
412 00:38:55.925 ⇒ 00:39:15.099 Amber Lin: maybe we can talk with Mark to see how he creates them. And then maybe instead of him downloading and emailing to us. We connect directly with the sheet that he creates, which I don’t know how he does it. Maybe that’s something we need to talk to Mark about.
413 00:39:15.730 ⇒ 00:39:16.370 Mustafa Raja: Yep.
414 00:39:16.840 ⇒ 00:39:18.857 Amber Lin: Okay. Sounds good.
415 00:39:21.440 ⇒ 00:39:27.990 Amber Lin: Ask mark how he creates the daily sales flash.
416 00:39:28.360 ⇒ 00:39:30.530 Amber Lin: We can’t connect.
417 00:39:31.500 ⇒ 00:39:32.410 Amber Lin: Okay?
418 00:39:32.720 ⇒ 00:39:40.100 Amber Lin: And then Uber, I think one last thing on the Uber side. Let me see if
419 00:39:41.260 ⇒ 00:39:43.979 Amber Lin: no wrong wrong place.
420 00:39:44.590 ⇒ 00:39:46.210 Amber Lin: Oh, we can reply it.
421 00:39:48.400 ⇒ 00:39:54.850 Amber Lin: Okay, okay. So Casey, real for next week. Ignore it for now.
422 00:39:55.970 ⇒ 00:39:58.459 Amber Lin: Anyways, insomnia cookies.
423 00:40:00.220 ⇒ 00:40:01.710 Amber Lin: We also.
424 00:40:05.510 ⇒ 00:40:11.019 Amber Lin: Oh, added Doordash, alright, so I’ll go check on Doordash stuff.
425 00:40:11.718 ⇒ 00:40:15.029 Amber Lin: and then we can talk about it as well.
426 00:40:16.510 ⇒ 00:40:16.940 Mustafa Raja: Yep.
427 00:40:16.940 ⇒ 00:40:23.359 Amber Lin: Alright. So the most important thing is the Microsoft thing, Microsoft. So on. Sorry.
428 00:40:24.860 ⇒ 00:40:29.759 Amber Lin: Microsoft, one on Casey. And then the spike on Google is on Mustafa.
429 00:40:30.130 ⇒ 00:40:30.670 Mustafa Raja: Okay.
430 00:40:30.970 ⇒ 00:40:32.140 Amber Lin: Alright. Thank you all.
431 00:40:32.522 ⇒ 00:40:38.640 Mustafa Raja: One thing can we talk about? I was assigned a ticket on ABC.
432 00:40:38.640 ⇒ 00:40:40.020 Amber Lin: Yes, yes.
433 00:40:40.415 ⇒ 00:40:42.785 Mustafa Raja: I want to talk about that.
434 00:40:47.258 ⇒ 00:40:49.209 Mustafa Raja: It’s 6, 1, 9.
435 00:40:52.760 ⇒ 00:40:54.250 Amber Lin: Oh yes!
436 00:40:54.530 ⇒ 00:40:55.020 Amber Lin: Oh.
437 00:40:55.740 ⇒ 00:40:56.969 Mustafa Raja: So they’ve been.
438 00:40:56.970 ⇒ 00:41:01.800 Amber Lin: They’ve asked me 2 times. There’s a
439 00:41:02.170 ⇒ 00:41:13.310 Amber Lin: item in the termite section that’s Column H, that they recently added, and I think when they asked about it. It’s not showing it’s not showing everything.
440 00:41:14.080 ⇒ 00:41:18.750 Amber Lin: so I don’t exactly remember what feedback
441 00:41:19.010 ⇒ 00:41:23.880 Amber Lin: it was related to. But let me see.
442 00:41:25.500 ⇒ 00:41:29.290 Casie Aviles: And I can give context to Mustafa on how we.
443 00:41:30.020 ⇒ 00:41:30.470 Mustafa Raja: Yeah.
444 00:41:30.470 ⇒ 00:41:34.689 Casie Aviles: From the inspector, like the technician should. Yeah.
445 00:41:34.810 ⇒ 00:41:36.460 Amber Lin: Okay, okay.
446 00:41:36.820 ⇒ 00:41:49.740 Amber Lin: sounds good. And you guys can decide who who needs to take that ticket. I just know that Casey is a bit swamped. I I just don’t know how much stuff you’re doing. You guys are doing for other clients.
447 00:41:50.320 ⇒ 00:41:50.615 Mustafa Raja: Okay.
448 00:41:51.540 ⇒ 00:41:53.960 Amber Lin: Yeah, all right.
449 00:41:54.190 ⇒ 00:41:59.560 Amber Lin: Sounds good. I will send stuff. I need from
450 00:42:03.540 ⇒ 00:42:04.220 Amber Lin: yeah.
451 00:42:05.131 ⇒ 00:42:08.658 Amber Lin: I think Casey and Mustafa feel free to hop.
452 00:42:09.840 ⇒ 00:42:15.619 Amber Lin: I wish. How can I create? What tickets should I create for Raj on the data modeling side?
453 00:42:15.960 ⇒ 00:42:18.189 Amber Lin: Can you give me just a few titles.
454 00:42:21.490 ⇒ 00:42:25.270 Awaish Kumar: Sorry. Yeah, what I was saying is that like we
455 00:42:25.790 ⇒ 00:42:29.630 Awaish Kumar: for the data modeling like he already created document was.
456 00:42:30.340 ⇒ 00:42:38.679 Awaish Kumar: what data models we need. So we can just create tickets like, for that. Just a high.
457 00:42:39.530 ⇒ 00:42:40.309 Amber Lin: Can I find it?
458 00:42:52.580 ⇒ 00:42:54.120 Amber Lin: I don’t know where it is.
459 00:42:54.400 ⇒ 00:42:56.280 Amber Lin: And is it these?
460 00:42:57.400 ⇒ 00:43:04.890 Amber Lin: I think I these are AI generated from me, so I don’t know if these are correct.
461 00:43:05.310 ⇒ 00:43:09.299 Amber Lin: All of this is from AI. When I created this.
462 00:43:09.300 ⇒ 00:43:12.749 Awaish Kumar: Yeah, but there are some what they’ve created as well. Right?
463 00:43:12.920 ⇒ 00:43:13.460 Awaish Kumar: So.
464 00:43:14.350 ⇒ 00:43:14.800 Amber Lin: Of course.
465 00:43:14.800 ⇒ 00:43:15.200 Awaish Kumar: Yes.
466 00:43:15.200 ⇒ 00:43:16.130 Amber Lin: That.
467 00:43:16.330 ⇒ 00:43:18.050 Awaish Kumar: Where’s your document? Last name?
468 00:43:18.406 ⇒ 00:43:20.189 Vashdev Heerani: Go down. Yes, this one.
469 00:43:21.070 ⇒ 00:43:22.170 Vashdev Heerani: Yeah. This one.
470 00:43:24.880 ⇒ 00:43:30.490 Amber Lin: Yeah. Which ones are the tickets like, sorry. The models.
471 00:43:31.680 ⇒ 00:43:37.520 Awaish Kumar: So basically, the the headings are the models
472 00:43:37.670 ⇒ 00:43:41.470 Awaish Kumar: like, time tracking data. So this is talking about.
473 00:43:41.470 ⇒ 00:43:43.520 Amber Lin: No! Oh, so.
474 00:43:43.520 ⇒ 00:43:44.040 Awaish Kumar: Go ahead and get.
475 00:43:44.040 ⇒ 00:43:48.700 Amber Lin: Data for each gotcha. Okay, I understand now. So I’m just gonna
476 00:43:49.800 ⇒ 00:43:56.729 Amber Lin: slack messages. Linear tickets has tool costs, channel project costs. Okay?
477 00:43:57.280 ⇒ 00:43:58.829 Amber Lin: I can do that.
478 00:43:59.990 ⇒ 00:44:01.030 Amber Lin: So.
479 00:44:01.030 ⇒ 00:44:05.090 Awaish Kumar: So basically, he’s going to create something. Right?
480 00:44:05.350 ⇒ 00:44:13.679 Awaish Kumar: I’ll it’s time data where it’s going to connect some sources and create a flare table
481 00:44:14.260 ⇒ 00:44:17.489 Awaish Kumar: with all the relevant data, and then
482 00:44:18.360 ⇒ 00:44:21.889 Awaish Kumar: Casey can build something on top of it. And then we
483 00:44:22.510 ⇒ 00:44:26.880 Awaish Kumar: are going to give our feedback like we need this, we need this filter.
484 00:44:27.140 ⇒ 00:44:30.039 Awaish Kumar: more data, more columns, things like that.
485 00:44:32.010 ⇒ 00:44:34.969 Amber Lin: Okay, yeah, that’s that’s all I needed to know
486 00:44:35.180 ⇒ 00:44:39.379 Amber Lin: sounds good. I will create these and assign it to our chef.
487 00:44:39.840 ⇒ 00:44:43.150 Amber Lin: are we going to work on this this week.
488 00:44:48.350 ⇒ 00:44:50.219 Awaish Kumar: Maybe we can take one.
489 00:44:51.040 ⇒ 00:44:51.610 Amber Lin: Okay.
490 00:44:51.860 ⇒ 00:44:52.420 Awaish Kumar: One, yeah.
491 00:44:52.420 ⇒ 00:44:54.690 Amber Lin: I agree, which one’s the most important.
492 00:44:56.210 ⇒ 00:44:58.050 Awaish Kumar: I think time tracking data is.
493 00:45:00.960 ⇒ 00:45:01.660 Amber Lin: Okay.
494 00:45:02.170 ⇒ 00:45:04.969 Amber Lin: So let me push
495 00:45:09.290 ⇒ 00:45:11.779 Amber Lin: status cycle.
496 00:45:13.300 ⇒ 00:45:21.920 Amber Lin: And then time tracking data to do time for the assigned questions.
497 00:45:22.710 ⇒ 00:45:28.330 Amber Lin: Okay, alright.
498 00:45:35.410 ⇒ 00:45:36.270 Amber Lin: Okay.
499 00:45:37.192 ⇒ 00:45:39.910 Amber Lin: I know Utam, send a message about Dlt hub.
500 00:45:39.910 ⇒ 00:45:46.839 Awaish Kumar: But I’m not sure we need it right now, because Dlt Hub is is a
501 00:45:47.070 ⇒ 00:45:50.149 Awaish Kumar: utham, pointed out this one to move the data.
502 00:45:50.320 ⇒ 00:45:53.920 Awaish Kumar: but we already wrote some scripts, and we already have.
503 00:45:54.190 ⇒ 00:46:01.679 Awaish Kumar: We have already done data ingestion. So right now, I don’t think we need it. So whenever we have a new source. Then we can
504 00:46:01.920 ⇒ 00:46:03.440 Awaish Kumar: think about Dlt, Hub.
505 00:46:03.960 ⇒ 00:46:12.759 Amber Lin: Okay, yeah. Sounds good. I’ll move it to back clock, that’s all. I’m going to pop to Eden.
506 00:46:13.060 ⇒ 00:46:14.410 Amber Lin: Thanks, everyone.