Meeting Title: MatterMore | internal Standup Date: 2025-04-29 Meeting participants: Annie Yu, Luke Daque, Uttam Kumaran, Amber Lin
WEBVTT
1 00:02:53.130 ⇒ 00:02:54.250 Annie Yu: Hello, Luke!
2 00:02:56.620 ⇒ 00:02:57.840 Luke Daque: Hello! Hello!
3 00:02:58.335 ⇒ 00:02:59.250 Luke Daque: How’s it going?
4 00:02:59.810 ⇒ 00:03:01.490 Annie Yu: How’s your Internet?
5 00:03:02.050 ⇒ 00:03:05.079 Luke Daque: It’s it’s back now. So yeah, it should be better.
6 00:03:05.580 ⇒ 00:03:06.846 Annie Yu: Nice. Nice.
7 00:03:07.870 ⇒ 00:03:15.439 Annie Yu: Yeah. So Kyle was saying, there’s there was like a outage in Europe, too.
8 00:03:15.590 ⇒ 00:03:19.940 Luke Daque: Yeah, like the whole whole Europe, or something like that. That’s weird.
9 00:03:20.280 ⇒ 00:03:20.900 Annie Yu: Yeah.
10 00:03:23.970 ⇒ 00:03:25.350 Amber Lin: Hi.
11 00:03:26.010 ⇒ 00:03:27.120 Annie Yu: Hello. Ember.
12 00:03:29.750 ⇒ 00:03:31.189 Amber Lin: I’m so dead.
13 00:03:32.700 ⇒ 00:03:34.616 Luke Daque: Meeting, after meeting, after meeting.
14 00:03:35.120 ⇒ 00:03:41.990 Amber Lin: Oh, no, I have not had a break since 6 30, and there is like 2 more hours to go.
15 00:03:43.540 ⇒ 00:03:48.560 Amber Lin: I don’t know how Utam does this cool.
16 00:03:49.570 ⇒ 00:03:54.910 Luke Daque: Yeah, like, context, switching is, really, I mean.
17 00:03:54.910 ⇒ 00:03:59.089 Amber Lin: I think. Mostly it’s just like I’m stuck in a meeting.
18 00:04:00.690 ⇒ 00:04:05.910 Amber Lin: I have do it versus. This is my own work. I’m like, Okay, I’ll do it later.
19 00:04:09.650 ⇒ 00:04:14.820 Amber Lin: Yeah, okay, I’ll keep it quick. I know all of you have also been in meetings.
20 00:04:17.040 ⇒ 00:04:18.790 Amber Lin: How’s progress?
21 00:04:19.010 ⇒ 00:04:21.090 Amber Lin: Let me pull up their linear.
22 00:04:22.990 ⇒ 00:04:28.349 Amber Lin: I know you guys had us in the data center yesterday. I saw that it was awesome.
23 00:04:31.490 ⇒ 00:04:43.989 Annie Yu: Yeah, we are meeting again tomorrow. No, not tomorrow. Today. Because, yeah, we figure out how to do the synthetic data. But we realized, we need to need to feed assumptions
24 00:04:44.710 ⇒ 00:04:51.590 Annie Yu: for those for the data to be, I guess, as accurate as it could be in real life.
25 00:04:52.620 ⇒ 00:05:00.030 Annie Yu: So we added those assumptions, and we are meeting again today to to to get it done.
26 00:05:00.660 ⇒ 00:05:06.159 Amber Lin: Oh, do we need any like assumptions from the matter? More team like? Do we need help from them?
27 00:05:10.500 ⇒ 00:05:19.460 Annie Yu: I don’t think so for the Microsoft Graph, which is what we are gonna focus on working on today. But
28 00:05:20.230 ⇒ 00:05:28.230 Annie Yu: I will have Trevor to review any assumptions for success. Factors.
29 00:05:28.740 ⇒ 00:05:29.790 Amber Lin: Which is oh.
30 00:05:30.590 ⇒ 00:05:34.770 Annie Yu: Also, I think, ready for him to review, so I’ll I’ll add him.
31 00:05:35.000 ⇒ 00:05:46.990 Amber Lin: I see. So can you guys run me through? What are the different things we need to do? Because I know there’s like Microsoft teams. And then there’s a success. Factors. Is that all the components?
32 00:05:47.170 ⇒ 00:05:51.499 Amber Lin: Because I don’t think our tickets are don’t cover. I don’t think they cover everything.
33 00:05:53.277 ⇒ 00:05:59.680 Annie Yu: I think just Microsoft Graphs and that include like calendar teams.
34 00:05:59.960 ⇒ 00:06:03.260 Annie Yu: outlook. And then there’s success factors.
35 00:06:04.010 ⇒ 00:06:05.060 Amber Lin: Oh.
36 00:06:08.500 ⇒ 00:06:12.059 Amber Lin: so this is not just success factors, documentation.
37 00:06:12.690 ⇒ 00:06:16.110 Amber Lin: It’s like just documentation, total.
38 00:06:17.063 ⇒ 00:06:18.999 Annie Yu: There are 2 main.
39 00:06:19.390 ⇒ 00:06:29.980 Annie Yu: I guess, Apis, that will leverage. So one is Microsoft Graphs, and one is success factors. And we we do have documentation for both.
40 00:06:37.170 ⇒ 00:06:45.020 Amber Lin: So if you guys can see my screen, I guess on here, here are the all the different components.
41 00:06:45.630 ⇒ 00:06:49.939 Amber Lin: and we sort of do them by Api. Right so.
42 00:06:50.940 ⇒ 00:06:51.680 Annie Yu: Should I?
43 00:06:51.680 ⇒ 00:06:57.570 Amber Lin: Make different tickets for each of these. How does it work.
44 00:07:00.960 ⇒ 00:07:06.290 Luke Daque: I think we already no tickets for those. Let me check.
45 00:07:09.340 ⇒ 00:07:16.589 Annie Yu: Yeah, maybe if we want, we can have separate just because they are at different stage. Now, Microsoft Graphs is ready for
46 00:07:17.420 ⇒ 00:07:19.080 Annie Yu: the data which we are
47 00:07:19.863 ⇒ 00:07:27.309 Annie Yu: and success factors. I think it’s almost ready to. But we just need another review from from Trevor.
48 00:07:30.190 ⇒ 00:07:35.369 Amber Lin: So I’ll create this.
49 00:07:38.560 ⇒ 00:07:43.090 Amber Lin: So I would say, the Microsoft Graphs documentation. Is that done?
50 00:07:44.460 ⇒ 00:07:45.120 Annie Yu: Yeah.
51 00:07:45.550 ⇒ 00:07:48.360 Amber Lin: Okay, awesome. That that’s helpful.
52 00:07:48.740 ⇒ 00:07:54.690 Amber Lin: So we’ll have that this is kind of like around.
53 00:07:55.450 ⇒ 00:08:00.169 Amber Lin: is it in? Is this still in progress like, or or does it just need a review.
54 00:08:01.760 ⇒ 00:08:03.956 Annie Yu: Which ticket is that is, that for
55 00:08:04.270 ⇒ 00:08:06.319 Amber Lin: Success Factors, Profit Addiction.
56 00:08:06.788 ⇒ 00:08:08.660 Annie Yu: I would say review.
57 00:08:08.880 ⇒ 00:08:14.679 Annie Yu: and that should be really quick, too. But let me in the meantime, at Trevor.
58 00:08:15.140 ⇒ 00:08:15.780 Amber Lin: Hmm.
59 00:08:24.570 ⇒ 00:08:31.390 Amber Lin: so synthetic data. This would be like, Microsoft glass.
60 00:08:56.630 ⇒ 00:09:08.150 Amber Lin: Okay, so let me create a ticket for success factors. Synthetic synthetic data set.
61 00:09:08.610 ⇒ 00:09:09.480 Amber Lin: Oh.
62 00:09:12.790 ⇒ 00:09:18.700 Amber Lin: take there you go should be.
63 00:09:19.930 ⇒ 00:09:21.370 Amber Lin: I’ll just put it there.
64 00:09:31.670 ⇒ 00:09:41.420 Amber Lin: Okay, did you guys get were able to go into the big query that Trevor shared.
65 00:09:44.070 ⇒ 00:09:50.899 Luke Daque: No, we we were able to log into the account, but we don’t have access to bigquery.
66 00:09:51.350 ⇒ 00:09:52.629 Luke Daque: So I think, Trevor.
67 00:09:52.630 ⇒ 00:09:53.030 Amber Lin: Oh!
68 00:09:53.860 ⇒ 00:09:55.760 Luke Daque: I think we already sent
69 00:09:56.270 ⇒ 00:09:58.410 Luke Daque: and he already sent it in the chat.
70 00:09:58.580 ⇒ 00:09:59.240 Amber Lin: On the slide.
71 00:09:59.774 ⇒ 00:10:01.910 Amber Lin: Let me go. Check.
72 00:10:03.450 ⇒ 00:10:06.480 Amber Lin: Oh, sent.
73 00:10:07.630 ⇒ 00:10:08.340 Amber Lin: Okay.
74 00:10:08.340 ⇒ 00:10:09.270 Luke Daque: Yeah, yeah.
75 00:10:09.270 ⇒ 00:10:13.109 Amber Lin: Sounds good. Okay, I’ll mark it as we are.
76 00:10:16.610 ⇒ 00:10:18.539 Amber Lin: He’s blocked right now.
77 00:10:19.060 ⇒ 00:10:20.320 Amber Lin: Let’s say we’re blocked.
78 00:10:20.990 ⇒ 00:10:22.060 Amber Lin: Hmm.
79 00:10:22.510 ⇒ 00:10:23.520 Luke Daque: Yeah, and.
80 00:10:23.520 ⇒ 00:10:24.750 Amber Lin: This test
81 00:10:25.770 ⇒ 00:10:29.760 Luke Daque: I think we don’t have access to the repository as well. Yet right.
82 00:10:30.699 ⇒ 00:10:36.530 Amber Lin: Don’t think he has granted us that. Yes.
83 00:10:37.503 ⇒ 00:10:42.310 Amber Lin: can. Let’s ping him, if we need that, do we need that right now.
84 00:10:43.750 ⇒ 00:10:49.819 Luke Daque: Would be great if we can store the the synthetic data scripts. There.
85 00:10:49.820 ⇒ 00:10:50.979 Amber Lin: I see, I see.
86 00:10:50.980 ⇒ 00:10:51.740 Luke Daque: Sure.
87 00:10:52.237 ⇒ 00:10:53.729 Amber Lin: I’ll add him
88 00:11:06.070 ⇒ 00:11:06.860 Amber Lin: 1 min.
89 00:11:13.830 ⇒ 00:11:16.890 Amber Lin: Okay, lot of requests for him.
90 00:11:17.550 ⇒ 00:11:32.200 Amber Lin: but it’s Async, so he can do, but he can deal with them one by one. That awesome since synthetic data set. So we’ll get review from him on the success factors.
91 00:11:33.020 ⇒ 00:11:42.390 Amber Lin: And then I guess today we are improving the Microsoft Graphs. Synthetic data set right.
92 00:11:43.890 ⇒ 00:11:44.640 Annie Yu: Yes.
93 00:11:44.970 ⇒ 00:11:55.489 Amber Lin: Okay, awesome. Well, I’ll try to. We’ll try to get the success factors. Documentation reviewed.
94 00:11:59.380 ⇒ 00:12:05.299 Amber Lin: I guess we could. Do you think we can start on it, or should we wait for him to review it first? st
95 00:12:08.430 ⇒ 00:12:09.420 Luke Daque: What was that?
96 00:12:11.260 ⇒ 00:12:15.839 Amber Lin: So yeah, success factors, synthetic data.
97 00:12:17.420 ⇒ 00:12:44.140 Annie Yu: I I would I would say so. I just added him, and I also told him that we added some assumptions for graph fields. But my thinking is we can go ahead and continue generating data for graphs, because there are 4 data sets. And I did tell him, if there’s anything needs to be changed or highlighted. I think we can. We can
98 00:12:44.290 ⇒ 00:12:50.120 Annie Yu: fine tune that later. And for success factors, I think it’s
99 00:12:50.530 ⇒ 00:12:53.000 Annie Yu: we. We can. We can wait wait for him.
100 00:12:53.240 ⇒ 00:13:00.190 Amber Lin: Okay. Awesome. For the micrographs. What for? You said there was 4 areas.
101 00:13:01.562 ⇒ 00:13:02.560 Annie Yu: For your table.
102 00:13:02.560 ⇒ 00:13:05.459 Amber Lin: So you see it. Yeah, there’s list messages. Events
103 00:13:05.750 ⇒ 00:13:08.119 Amber Lin: get all messages. Is that those.
104 00:13:08.890 ⇒ 00:13:09.520 Annie Yu: Yeah.
105 00:13:09.810 ⇒ 00:13:13.589 Amber Lin: Okay, awesome, great. So that will be.
106 00:13:13.590 ⇒ 00:13:17.159 Annie Yu: For? Yeah, we should have 4 data sets. Today.
107 00:13:17.160 ⇒ 00:13:25.729 Amber Lin: Sounds good. I will mark that. As to today tomorrow today, well, yeah, we’ll talk about it tomorrow.
108 00:13:26.030 ⇒ 00:13:27.050 Amber Lin: So.
109 00:13:27.050 ⇒ 00:13:36.899 Luke Daque: Yeah, I guess the best we can do is save them as Csv files, because we don’t have access to bigquery. But once we get access to bigquery. Then we can save them as data sets.
110 00:13:37.640 ⇒ 00:13:38.200 Annie Yu: Good call.
111 00:13:45.530 ⇒ 00:13:49.430 Amber Lin: Let me see, good.
112 00:13:51.660 ⇒ 00:13:52.740 Amber Lin: Dave’s
113 00:13:53.310 ⇒ 00:13:59.309 Amber Lin: okay. Awesome, that’s all. I think that’s really good progress. And then we know what we’re gonna do today.
114 00:14:02.130 ⇒ 00:14:02.880 Luke Daque: Cool.
115 00:14:03.200 ⇒ 00:14:05.270 Amber Lin: Yeah, utam, any input from you.
116 00:14:05.911 ⇒ 00:14:13.249 Uttam Kumaran: That’s it, I would say, if you don’t hear from Trevor on feedback, just go ahead and do the synthetic work like, let’s just keep pushing, cause
117 00:14:13.530 ⇒ 00:14:16.110 Uttam Kumaran: worst case, they can give us feedback on that. So
118 00:14:16.474 ⇒ 00:14:19.050 Uttam Kumaran: yeah. And then just let me know if I can unblock anything.
119 00:14:20.360 ⇒ 00:14:21.150 Luke Daque: Awesome.
120 00:14:21.310 ⇒ 00:14:22.369 Annie Yu: Sounds good.
121 00:14:24.190 ⇒ 00:14:25.200 Uttam Kumaran: Okay.
122 00:14:25.730 ⇒ 00:14:26.780 Amber Lin: Okay. Thank you.
123 00:14:26.780 ⇒ 00:14:27.330 Uttam Kumaran: Thank you.
124 00:14:27.330 ⇒ 00:14:27.850 Luke Daque: Thanks, Larry.
125 00:14:29.505 ⇒ 00:14:30.920 Amber Lin: Bye.
126 00:14:31.550 ⇒ 00:14:32.180 Luke Daque: Bye.