Meeting Title: FireGroups Analytics Data Query Sync Date: 2025-11-26 Meeting participants: Amber Lin, Casie Aviles
WEBVTT
1 00:00:13.670 ⇒ 00:00:14.780 Amber Lin: Hi, Casey.
2 00:00:16.470 ⇒ 00:00:16.970 Amber Lin: Okay.
3 00:00:17.320 ⇒ 00:00:18.130 Casie Aviles: Do you have that?
4 00:00:18.130 ⇒ 00:00:20.709 Amber Lin: Notion doc, we can write things down.
5 00:00:21.530 ⇒ 00:00:25.810 Casie Aviles: Yeah, sure, we can use the spike motion, though.
6 00:00:26.210 ⇒ 00:00:28.350 Casie Aviles: Let me just… Send it.
7 00:00:29.910 ⇒ 00:00:37.860 Amber Lin: Does SQL to… the text to SQL query, is it mostly for farm moms, or is it for…
8 00:00:38.200 ⇒ 00:00:42.269 Amber Lin: Other areas. So, what type of questions shall I look for?
9 00:00:43.690 ⇒ 00:00:52.419 Casie Aviles: Oh, I’m not sure exactly, but the kinds of questions that I tested out with are…
10 00:00:53.330 ⇒ 00:00:56.649 Casie Aviles: Wait, let me, let me share my screen so you can also see.
11 00:00:57.410 ⇒ 00:01:01.500 Casie Aviles: Alright, okay.
12 00:01:01.890 ⇒ 00:01:06.799 Casie Aviles: I’m not sure what kinds of questions these are, if they’re farm-ups or not, but…
13 00:01:07.050 ⇒ 00:01:12.949 Casie Aviles: This… it’s just revenue questions and week… over-week comparisons and discounts, so that’s, like, the…
14 00:01:12.950 ⇒ 00:01:25.109 Amber Lin: I see. Okay. So these are mainly the finance and sales ones. Let’s go grab a few farmhouse ones, because that’s the main ones they tell us to, hey, can you grab data for us? Okay. That’s…
15 00:01:26.190 ⇒ 00:01:29.969 Amber Lin: I think it’s in FireGroups Analytics.
16 00:01:30.930 ⇒ 00:01:34.389 Amber Lin: Here, are you in this channel?
17 00:01:34.890 ⇒ 00:01:36.289 Amber Lin: Let me add you.
18 00:01:37.350 ⇒ 00:01:38.760 Amber Lin: Okay, see…
19 00:01:43.610 ⇒ 00:01:44.290 Amber Lin: Cool.
20 00:01:49.680 ⇒ 00:01:54.940 Amber Lin: Alright, I just added you to the channel, so let’s go…
21 00:02:06.300 ⇒ 00:02:07.630 Casie Aviles: Oh. -Oh.
22 00:02:07.850 ⇒ 00:02:09.559 Casie Aviles: Not sure if I saw it…
23 00:02:10.030 ⇒ 00:02:17.170 Amber Lin: Check activities… Huh, maybe search, just search, I don’t know, farm lofts.
24 00:02:19.390 ⇒ 00:02:20.250 Casie Aviles: That one.
25 00:02:21.130 ⇒ 00:02:27.850 Amber Lin: So you can see, like, Sarah, we build a dashboard for Sarah, but a lot of times they ask…
26 00:02:27.980 ⇒ 00:02:38.919 Amber Lin: like, that question, or the question above it, if you scroll up, like, they mostly just drop a question here and say, hey, can we get this, can we get that?
27 00:02:41.110 ⇒ 00:02:42.669 Amber Lin: Let’s see…
28 00:02:42.990 ⇒ 00:02:55.560 Amber Lin: So, maybe in September, let’s scroll up a little bit, because I… we want something that the data team has responded with, so that one that Awash has responded to, maybe we can try that.
29 00:02:57.440 ⇒ 00:02:58.319 Casie Aviles: Alright, this one.
30 00:02:58.320 ⇒ 00:03:04.920 Amber Lin: Yeah, let’s try that. Let’s copy the link, and then I’ll put it… I’ll put it in a doc. You can go try the query.
31 00:03:14.680 ⇒ 00:03:15.460 Casie Aviles: Okay.
32 00:03:18.360 ⇒ 00:03:24.149 Casie Aviles: I’m just curious, like, what… Data we need to draw from, because…
33 00:03:24.290 ⇒ 00:03:30.440 Casie Aviles: Alright, I might not… it might not be… I’m just using the fact transactions table, so…
34 00:03:31.700 ⇒ 00:03:34.020 Casie Aviles: Maybe that’s not enough, I’m not sure.
35 00:03:34.020 ⇒ 00:03:36.000 Amber Lin: I see.
36 00:03:39.290 ⇒ 00:03:39.880 Amber Lin: seat.
37 00:03:39.880 ⇒ 00:03:40.380 Casie Aviles: Okay.
38 00:03:40.380 ⇒ 00:03:43.180 Amber Lin: Where did Luis pull this from?
39 00:03:43.460 ⇒ 00:03:47.150 Amber Lin: Yeah, let me check OASIS… Stairs fee.
40 00:03:47.660 ⇒ 00:03:50.070 Amber Lin: Maybe that tells us something?
41 00:03:55.140 ⇒ 00:03:56.010 Casie Aviles: Okay.
42 00:03:59.430 ⇒ 00:04:02.449 Casie Aviles: I mean… I think I can just…
43 00:04:02.450 ⇒ 00:04:04.140 Amber Lin: Like, the shipping?
44 00:04:04.780 ⇒ 00:04:11.450 Amber Lin: Shipping data… Yeah. I guess we can collect all of them.
45 00:04:11.800 ⇒ 00:04:12.450 Casie Aviles: Yeah, okay.
46 00:04:12.450 ⇒ 00:04:22.090 Amber Lin: In one place, and then we can ask a wish. Okay, cool, that’s one. So, I think Robert said we want at least 10. So, above that…
47 00:04:23.490 ⇒ 00:04:24.350 Amber Lin: Oops.
48 00:04:24.650 ⇒ 00:04:26.040 Amber Lin: What’s that?
49 00:04:31.140 ⇒ 00:04:35.230 Amber Lin: Okay, that’s new pricing, that’s a pricing adjustment.
50 00:04:36.390 ⇒ 00:04:40.769 Amber Lin: So… I think this is less of a query.
51 00:04:41.430 ⇒ 00:04:42.460 Casie Aviles: Hmm.
52 00:04:43.800 ⇒ 00:04:44.960 Amber Lin: I’ll put it…
53 00:05:17.130 ⇒ 00:05:22.230 Amber Lin: Okay, that one from Danny is also… Let’s see…
54 00:05:23.080 ⇒ 00:05:25.230 Amber Lin: So this one, again, from Katie.
55 00:05:27.630 ⇒ 00:05:30.110 Amber Lin: I think she’s requesting…
56 00:05:33.460 ⇒ 00:05:36.649 Amber Lin: Yeah, so that’s another request.
57 00:05:39.310 ⇒ 00:05:40.929 Amber Lin: I’ll copy the link.
58 00:06:09.430 ⇒ 00:06:18.640 Amber Lin: Cool, okay, let’s go up… Dashboard…
59 00:06:20.770 ⇒ 00:06:25.750 Amber Lin: Okay, so that… then it’s in August from Sarah.
60 00:06:37.270 ⇒ 00:06:37.970 Casie Aviles: Sworn.
61 00:06:41.800 ⇒ 00:06:42.410 Amber Lin: Cool.
62 00:06:42.560 ⇒ 00:06:47.880 Amber Lin: Do you wanna just ping Awash and ask him if he has time, or ask him what…
63 00:06:48.070 ⇒ 00:06:52.390 Amber Lin: Like, what type of data we should use for farm ops request.
64 00:06:53.290 ⇒ 00:06:54.370 Casie Aviles: Oh, yeah, yeah, sure, sure.
65 00:13:02.550 ⇒ 00:13:08.209 Amber Lin: I’ve found 10 questions. Can you look at them and let me know if that works?
66 00:13:09.420 ⇒ 00:13:09.980 Casie Aviles: Okay.
67 00:13:18.150 ⇒ 00:13:18.930 Casie Aviles: Nope.
68 00:13:19.860 ⇒ 00:13:22.259 Casie Aviles: Did you paste them somewhere?
69 00:13:22.260 ⇒ 00:13:24.960 Amber Lin: Yeah, I put it at the end of the notion doc.
70 00:13:24.960 ⇒ 00:13:25.790 Casie Aviles: Oh, okay.
71 00:13:32.320 ⇒ 00:13:33.279 Casie Aviles: I see.
72 00:13:34.720 ⇒ 00:13:36.480 Casie Aviles: Alright, yeah, these work.
73 00:13:38.290 ⇒ 00:13:40.259 Casie Aviles: Yeah, I think I… yeah, I’ll just work on…
74 00:13:42.060 ⇒ 00:13:44.519 Casie Aviles: doing the tests. This should be helpful.
75 00:13:45.550 ⇒ 00:13:50.970 Amber Lin: Cool, okay. Did I wish to get back to you on what… Marts you need?
76 00:13:51.610 ⇒ 00:13:52.740 Casie Aviles: Yes.
77 00:13:53.360 ⇒ 00:13:54.020 Amber Lin: Okay.
78 00:13:54.910 ⇒ 00:14:00.749 Amber Lin: Sounds good. Most of these should have answers in the link, I put them there as well, so…
79 00:14:00.750 ⇒ 00:14:01.380 Casie Aviles: I agree.
80 00:14:01.380 ⇒ 00:14:03.440 Amber Lin: If you want to look at that, it’d be good.
81 00:14:04.710 ⇒ 00:14:06.510 Casie Aviles: Okay, yeah, thank you.
82 00:14:07.370 ⇒ 00:14:08.150 Amber Lin: All good.
83 00:14:09.010 ⇒ 00:14:10.660 Amber Lin: Alright. Bye.
84 00:14:11.280 ⇒ 00:14:12.330 Casie Aviles: Thank you, bye-bye.