Meeting Title: MatterMore | internal Standup Date: 2025-07-02 Meeting participants: Luke Daque, Amber Lin


WEBVTT

1 00:00:46.300 00:00:47.899 Amber Lin: Hello! Again.

2 00:00:49.540 00:00:50.430 Luke Daque: Hi amber.

3 00:00:53.770 00:00:57.920 Amber Lin: Okay, yeah. Let’s just be quick. It’s just 2, the 2 of us.

4 00:00:59.420 00:01:01.930 Amber Lin: How is your day going.

5 00:01:02.800 00:01:05.279 Luke Daque: Yeah, everything’s going well, so far.

6 00:01:06.170 00:01:08.040 Amber Lin: Okay, good to hear.

7 00:01:08.210 00:01:10.339 Amber Lin: I know that. Oh.

8 00:01:11.530 00:01:18.420 Amber Lin: now you’re also on ABC, and then this. And I know also Utop bringing you on for like data platform stuff.

9 00:01:18.880 00:01:19.680 Luke Daque: Yeah.

10 00:01:20.000 00:01:22.048 Amber Lin: Yeah, so getting busier.

11 00:01:22.560 00:01:24.390 Luke Daque: There’s a couple of stuff. There’s.

12 00:01:25.670 00:01:26.610 Luke Daque: Going on.

13 00:01:33.610 00:01:35.780 Amber Lin: Okay? So

14 00:01:37.530 00:01:44.420 Amber Lin: oh, I guess for the I don’t see the other ticket. I assume that was that was done. So we have the data.

15 00:01:44.420 00:01:44.930 Luke Daque: Okay.

16 00:01:45.120 00:01:45.550 Amber Lin: Right? Now.

17 00:01:45.550 00:01:45.920 Amber Lin: Oh, yeah.

18 00:01:46.390 00:01:47.530 Amber Lin: Oh, yeah.

19 00:01:47.530 00:01:50.590 Luke Daque: Should be. Oh, yeah, the other one’s done like the missing.

20 00:01:50.960 00:01:55.110 Luke Daque: With the unknown fields and stuff like that. That’s done.

21 00:01:55.370 00:01:59.459 Luke Daque: But I haven’t started with the power bi one yet.

22 00:01:59.770 00:02:01.159 Amber Lin: Okay. Okay. No. Worries.

23 00:02:01.160 00:02:02.140 Luke Daque: Yeah, yeah.

24 00:02:02.140 00:02:21.060 Amber Lin: No worries. Let me see if they responded. They keep ignoring me so there’s nothing I asked them about what they want. They just didn’t respond. I don’t know what we can do probably ask to talk to them, but at least, for now we have this ticket, so we’ll do this one

25 00:02:21.653 00:02:26.609 Amber Lin: that will take today. And that’s it. Does. Does this make sense?

26 00:02:27.000 00:02:30.770 Amber Lin: I kinda wanted to meet with you to make sure that things make sense.

27 00:02:30.770 00:02:36.679 Luke Daque: Yeah, that I understand the request. I just haven’t like started it yet. I think I’m not sure how

28 00:02:37.130 00:02:45.730 Luke Daque: how easy or complicated it might be, considering. There’s a lot like

29 00:02:47.920 00:02:51.009 Luke Daque: like we do have different fields, right like.

30 00:02:51.560 00:02:58.109 Luke Daque: for example, that one that you’re what would be the clustered

31 00:02:59.230 00:03:01.780 Luke Daque: field. Then would it be the Geo.

32 00:03:02.180 00:03:06.039 Luke Daque: Or the division depending on the dimension selected.

33 00:03:06.040 00:03:16.749 Amber Lin: Yeah, I think that that’s the point of say, we have this. It’s you we select. Let’s say, we want to look at. Actually, this is not.

34 00:03:17.190 00:03:21.590 Amber Lin: This is not the S. 1, 2 edit.

35 00:03:21.930 00:03:24.580 Amber Lin: How do I go back?

36 00:03:25.330 00:03:31.420 Amber Lin: Oh, oh dear, anyways, so if it was, for

37 00:03:32.230 00:03:37.940 Amber Lin: let’s say it was for the day of week.

38 00:03:38.350 00:03:42.420 Amber Lin: and then we selected something that we wanna look at.

39 00:03:43.180 00:03:47.629 Amber Lin: Maybe down here we wanted to look at department.

40 00:03:48.210 00:03:57.440 Amber Lin: or let’s say it’s day a week, and then we want to compare departments. I guess we’ll have a selector. We’ll say departments, and then we’ll select

41 00:03:57.930 00:03:59.900 Amber Lin: the different ones.

42 00:04:00.500 00:04:02.769 Amber Lin: Let’s see what it is clustered.

43 00:04:04.510 00:04:06.370 Luke Daque: I don’t know what the difference is.

44 00:04:07.160 00:04:13.290 Luke Daque: We might need a different selector, for of that right, something like.

45 00:04:14.310 00:04:19.800 Amber Lin: Yeah. So if we have that like.

46 00:04:20.649 00:04:26.139 Amber Lin: if we have, say, example would be, the bottom is.

47 00:04:26.140 00:04:26.770 Luke Daque: Okay.

48 00:04:27.160 00:04:29.099 Amber Lin: Day, of week.

49 00:04:29.510 00:04:30.390 Luke Daque: Yeah.

50 00:04:30.390 00:04:34.150 Amber Lin: Let’s say, Oh.

51 00:04:37.520 00:04:46.009 Amber Lin: let’s say that’s day of week, and then for y access I don’t know like

52 00:04:46.700 00:04:54.020 Amber Lin: that. And then for legend, let’s say it’s

53 00:04:58.755 00:04:59.460 Amber Lin: Wait.

54 00:04:59.460 00:05:00.600 Luke Daque: Geographical tribe.

55 00:05:01.235 00:05:01.870 Amber Lin: Okay.

56 00:05:02.660 00:05:06.349 Amber Lin: Oh, does that work?

57 00:05:07.000 00:05:08.170 Amber Lin: We’ll see.

58 00:05:11.040 00:05:15.220 Luke Daque: Try putting geography to the X-axis as well. I think.

59 00:05:20.890 00:05:22.239 Amber Lin: with that, too.

60 00:05:22.550 00:05:28.650 Amber Lin: Maybe geography doesn’t have all the hmm.

61 00:05:29.040 00:05:31.140 Amber Lin: Oh, dear!

62 00:05:31.420 00:05:39.969 Amber Lin: So I guess it did cluster. And then I guess we you would just have it. In.

63 00:05:40.630 00:05:42.600 Amber Lin: What does legend mean?

64 00:05:43.420 00:05:45.220 Luke Daque: I think that’s just like the

65 00:05:49.570 00:05:52.190 Luke Daque: I don’t know I can’t. I don’t know how to explain.

66 00:05:55.220 00:05:57.380 Amber Lin: See if I also add it. Oh.

67 00:05:57.380 00:05:58.439 Luke Daque: There you go. Yeah.

68 00:05:58.440 00:06:04.610 Amber Lin: There we go. Yeah, I think that’s what they that’s what I want to see is to compare like.

69 00:06:07.140 00:06:12.929 Amber Lin: So if we get to compare for Friday. Okay, we see

70 00:06:13.450 00:06:20.589 Amber Lin: this compared. We can compare these 2. And then, oh, let’s look at Monday. Oh, let’s compare how they went.

71 00:06:21.030 00:06:24.050 Amber Lin: So I guess. The point they want is to

72 00:06:24.450 00:06:29.280 Amber Lin: be able to select what goes in this one.

73 00:06:29.500 00:06:38.079 Amber Lin: Right? So it could be geography. It could be function. I just don’t know how we are going to enable.

74 00:06:38.830 00:06:39.520 Luke Daque: Yeah.

75 00:06:40.710 00:06:43.280 Amber Lin: But I think overall, I think this is a

76 00:06:43.490 00:06:46.410 Amber Lin: like a place to start. Does that mean?

77 00:06:46.650 00:06:50.389 Amber Lin: Yeah, I think we’ll we’ll use these so that they can cross. Compare.

78 00:06:50.520 00:06:58.749 Amber Lin: But I think what what you would need to figure out is how we allow them to select essentially, they also wanna, they want to have

79 00:06:58.930 00:07:02.510 Amber Lin: essentially replace this with these like.

80 00:07:03.650 00:07:13.770 Amber Lin: compare Comparison charts. Essentially. So they want to be able to select. Okay, I want this, or I want to compare. I want to put

81 00:07:15.920 00:07:24.610 Amber Lin: marketing specialist also on the x-axis, and I want to select and want to compare 2 of these, or I want to compare 3 of these.

82 00:07:24.750 00:07:28.289 Amber Lin: So they I guess they want to have a multi select.

83 00:07:28.740 00:07:29.600 Luke Daque: Yeah.

84 00:07:30.130 00:07:30.670 Amber Lin: Yeah.

85 00:07:30.670 00:07:31.700 Luke Daque: Make sense.

86 00:07:33.160 00:07:34.060 Luke Daque: Okay.

87 00:07:34.270 00:07:41.080 Amber Lin: Yeah, alright, hopefully, that was a bit more clear. I also had a lot of problem figuring out what that meant.

88 00:07:42.000 00:07:52.459 Amber Lin: So we can do this today. I think that’s enough for today. I’ll I’m trying to meet Matthew to get his requirements for the next step, so he hasn’t replied yet.

89 00:07:53.810 00:07:55.769 Luke Daque: Sounds good. Okay.

90 00:07:56.050 00:07:56.530 Luke Daque: Cool.

91 00:07:56.530 00:07:58.260 Amber Lin: Awesome. Thank you so much.

92 00:07:58.550 00:07:59.650 Luke Daque: Thanks, amber.

93 00:07:59.860 00:08:01.480 Amber Lin: Alright, bye-bye.