Meeting Title: ABC Database Design Sync Date: 2025-08-27 Meeting participants: Casie Aviles, Mustafa Raja, Amber Lin
WEBVTT
1 00:00:11.450 ⇒ 00:00:12.890 Mustafa Raja: Hey, Casey.
2 00:00:14.480 ⇒ 00:00:15.610 Mustafa Raja: Hello again.
3 00:00:16.120 ⇒ 00:00:17.540 Casie Aviles: Ayy.
4 00:00:22.630 ⇒ 00:00:27.040 Casie Aviles: Yeah, let’s see, let’s wait if… More people will come.
5 00:00:27.040 ⇒ 00:00:27.810 Mustafa Raja: Yeah.
6 00:01:02.910 ⇒ 00:01:03.930 Amber Lin: Hi there.
7 00:01:05.540 ⇒ 00:01:06.380 Casie Aviles: A….
8 00:01:07.120 ⇒ 00:01:09.360 Amber Lin: Do you guys know if Sam’s gonna come?
9 00:01:11.100 ⇒ 00:01:18.339 Casie Aviles: Hmm, he wasn’t in our… stand up earlier, so I think it might be unlikely for him to come.
10 00:01:19.040 ⇒ 00:01:20.000 Amber Lin: Hmm.
11 00:01:25.950 ⇒ 00:01:29.919 Amber Lin: I see. Let’s check…
12 00:01:38.440 ⇒ 00:01:39.460 Amber Lin: Okay.
13 00:01:39.660 ⇒ 00:01:46.320 Amber Lin: Well… We can spend a little bit of time talking about how we want to….
14 00:01:47.010 ⇒ 00:01:53.960 Casie Aviles: Yeah, I think, yeah, let’s just move forward with, I think, with some things to get.
15 00:01:54.820 ⇒ 00:02:00.339 Casie Aviles: to get some progress, I guess, at least, so it doesn’t get blocked by review.
16 00:02:01.150 ⇒ 00:02:01.910 Amber Lin: Okay.
17 00:02:02.860 ⇒ 00:02:06.349 Casie Aviles: I’ll just share my screen quickly, if I sold it.
18 00:02:06.490 ⇒ 00:02:07.410 Casie Aviles: Well, this…
19 00:02:13.110 ⇒ 00:02:15.439 Casie Aviles: I’m just gonna share this, so…
20 00:02:15.570 ⇒ 00:02:19.809 Casie Aviles: I already went through the rest, so I just added these.
21 00:02:19.960 ⇒ 00:02:21.200 Casie Aviles: For today.
22 00:02:23.440 ⇒ 00:02:29.910 Casie Aviles: This is the one that I was trying to show from the Loom video, so I just added it here, so it’s much easier to….
23 00:02:30.440 ⇒ 00:02:31.070 Amber Lin: Go ahead.
24 00:02:31.710 ⇒ 00:02:38.739 Casie Aviles: Basically, I think what we were talking about yesterday was with the design of the database, so…
25 00:02:39.120 ⇒ 00:02:44.559 Casie Aviles: I tried two approaches, so we have the relational design here.
26 00:02:44.740 ⇒ 00:02:48.450 Casie Aviles: As you can see, like, we have 3 tables split.
27 00:02:48.610 ⇒ 00:02:53.110 Casie Aviles: So, if we have, like, the master inspector sheet, ….
28 00:02:53.620 ⇒ 00:02:54.080 Amber Lin: It’s good.
29 00:02:54.080 ⇒ 00:02:57.960 Casie Aviles: To be split into different tables, and….
30 00:02:58.990 ⇒ 00:03:03.069 Casie Aviles: The other approach is the flat design, which is currently what it is right now.
31 00:03:03.500 ⇒ 00:03:07.349 Casie Aviles: As you can see, there’s, like, lots of columns over here.
32 00:03:08.740 ⇒ 00:03:12.479 Casie Aviles: So those are just the two… designs that I…
33 00:03:12.790 ⇒ 00:03:22.090 Casie Aviles: tried, and I would say that, ideally, this is the one we should go for, because this is what most.
34 00:03:22.090 ⇒ 00:03:23.420 Amber Lin: Yeah, I agree.
35 00:03:23.420 ⇒ 00:03:27.270 Casie Aviles: Implementations used for production use cases, and…
36 00:03:27.990 ⇒ 00:03:31.140 Casie Aviles: This one is more for a spreadsheet style.
37 00:03:31.240 ⇒ 00:03:33.109 Casie Aviles: This works for a spreadsheet.
38 00:03:33.420 ⇒ 00:03:35.859 Casie Aviles: But this one is ideal for…
39 00:03:35.980 ⇒ 00:03:40.139 Casie Aviles: databases, so I’m, like, confident here.
40 00:03:40.710 ⇒ 00:03:52.619 Amber Lin: Yeah, I agree, because, especially if they want to have, say, Austin North, Austin South, and then use that to find the backup persons, I think that’s what we’ll need to do.
41 00:03:53.160 ⇒ 00:04:03.060 Casie Aviles: Yeah, that’s right. And we could base… we could essentially just add that data, the quadrant thing, here in the locations table, so it’s gonna look…
42 00:04:03.400 ⇒ 00:04:07.640 Casie Aviles: Sort of… this is just an example data, but it’s gonna look like this, right?
43 00:04:09.420 ⇒ 00:04:09.950 Amber Lin: Yeah.
44 00:04:09.950 ⇒ 00:04:14.299 Casie Aviles: We have, like, the south, the north branch, something. This is not the exact one from there.
45 00:04:14.790 ⇒ 00:04:17.949 Casie Aviles: data, but we could definitely do it like this.
46 00:04:20.060 ⇒ 00:04:23.209 Casie Aviles: So, yeah, I think I can start…
47 00:04:23.310 ⇒ 00:04:31.690 Casie Aviles: With just getting the inspector sheet, and then converting it into This relational table here.
48 00:04:32.280 ⇒ 00:04:33.270 Amber Lin: Mmm.
49 00:04:33.270 ⇒ 00:04:36.429 Casie Aviles: So, at least we have something in progress.
50 00:04:37.460 ⇒ 00:04:41.259 Amber Lin: Yeah, on the assignments table, what fields are there?
51 00:04:42.050 ⇒ 00:04:46.330 Casie Aviles: Not sure, let me… good. Oh, yeah, okay, let’s just…
52 00:04:47.540 ⇒ 00:04:50.729 Casie Aviles: Check here, yeah. We have, …
53 00:04:50.920 ⇒ 00:04:55.480 Casie Aviles: This is, like, a… it’s not the same data, but it’s, like, a recreation of it.
54 00:04:55.840 ⇒ 00:04:56.870 Casie Aviles: ….
55 00:04:56.870 ⇒ 00:04:58.300 Amber Lin: So we have a zip.
56 00:04:58.500 ⇒ 00:05:03.770 Casie Aviles: And then we have a person ID, which links back to someone from the people
57 00:05:03.950 ⇒ 00:05:06.180 Casie Aviles: Table, so we have the name.
58 00:05:06.680 ⇒ 00:05:12.010 Casie Aviles: And then we have their ID. So we could even add other columns here, like, if needed.
59 00:05:12.910 ⇒ 00:05:18.259 Casie Aviles: And then we have the role over here as another column.
60 00:05:18.700 ⇒ 00:05:21.680 Casie Aviles: And we can also check people that we have.
61 00:05:21.680 ⇒ 00:05:22.520 Amber Lin: I see.
62 00:05:23.270 ⇒ 00:05:27.400 Amber Lin: What’s the primary key on the assignments table?
63 00:05:29.550 ⇒ 00:05:31.870 Casie Aviles: I think it’s… it has its own….
64 00:05:32.670 ⇒ 00:05:34.110 Amber Lin: Oh, it has its own, like.
65 00:05:34.110 ⇒ 00:05:35.169 Casie Aviles: IDs, yeah.
66 00:05:35.170 ⇒ 00:05:36.239 Amber Lin: Let’s see, okay.
67 00:05:36.240 ⇒ 00:05:36.860 Casie Aviles: Yeah.
68 00:05:37.020 ⇒ 00:05:38.799 Casie Aviles: It’s like assignment ID.
69 00:05:38.990 ⇒ 00:05:45.590 Amber Lin: Also, there… there would be multiple rows for zip code, say, 1.
70 00:05:46.620 ⇒ 00:05:48.060 Casie Aviles: Yes.
71 00:05:48.060 ⇒ 00:05:48.570 Amber Lin: Okay.
72 00:05:48.570 ⇒ 00:05:49.780 Casie Aviles: We have to do.
73 00:05:50.620 ⇒ 00:05:52.950 Amber Lin: Yeah, okay. That makes sense to me.
74 00:05:54.320 ⇒ 00:05:55.790 Amber Lin: ….
75 00:05:56.270 ⇒ 00:05:59.849 Mustafa Raja: I guess we can make the role, into an array.
76 00:06:01.840 ⇒ 00:06:02.310 Casie Aviles: Probably so.
77 00:06:02.310 ⇒ 00:06:10.630 Mustafa Raja: because I see the… I think that, a particular person … Can have multiple roles.
78 00:06:10.630 ⇒ 00:06:11.500 Amber Lin: Mmm….
79 00:06:11.500 ⇒ 00:06:16.770 Mustafa Raja: If that would be the case, maybe, maybe, an array of text would be better.
80 00:06:17.340 ⇒ 00:06:20.580 Casie Aviles: Yeah, yeah, that’s good. We could do that, we could do that, yeah.
81 00:06:20.580 ⇒ 00:06:23.229 Mustafa Raja: Yeah, but this looks pretty promising.
82 00:06:26.570 ⇒ 00:06:27.310 Casie Aviles: Okay.
83 00:06:27.670 ⇒ 00:06:31.960 Mustafa Raja: Yeah, I like the… foreign keys on Japan.
84 00:06:32.480 ⇒ 00:06:48.909 Amber Lin: I think… I think my question is… is… is just if we want to do it… which order we want to do it. Right now, I think we want to have it, say, person 1, and then an area of rows they are taking. I think in our current spreadsheet, we have…
85 00:06:49.000 ⇒ 00:06:56.249 Amber Lin: a role, and then an area of person IDs. So I guess, which way do we want to go with that?
86 00:06:58.940 ⇒ 00:07:08.679 Mustafa Raja: I guess, for a zip, how many people are working on those zips and the roles assigned to them?
87 00:07:08.930 ⇒ 00:07:19.989 Mustafa Raja: I mean, which is pretty good, pretty much, the table of assignments that Casey has laid out. I think this, this works good, but if you want to change it, we can, though, right?
88 00:07:23.190 ⇒ 00:07:26.020 Casie Aviles: Yeah, … Yeah, I think it’s…
89 00:07:26.280 ⇒ 00:07:33.920 Casie Aviles: like, I think what Amber’s… if I understand correctly, like, for a particular zip, we want to get, like, multiple people.
90 00:07:35.890 ⇒ 00:07:41.190 Casie Aviles: And yeah, we have that. We can see the zips here, so we would just probably query…
91 00:07:41.910 ⇒ 00:07:47.720 Casie Aviles: Based on the zip, and then it’s gonna return 1, 2, like, the people there.
92 00:07:47.930 ⇒ 00:07:48.440 Mustafa Raja: Yeah.
93 00:07:48.440 ⇒ 00:07:49.670 Amber Lin: Mmm.
94 00:07:49.670 ⇒ 00:07:51.189 Casie Aviles: And then it’s gonna return….
95 00:07:51.480 ⇒ 00:07:52.760 Mustafa Raja: Yeah.
96 00:07:52.760 ⇒ 00:07:53.630 Casie Aviles: Sir, Bob Smith.
97 00:07:53.700 ⇒ 00:08:01.540 Mustafa Raja: Yeah, and we might also be able to, query, on Zip and the role we want to find, right?
98 00:08:01.930 ⇒ 00:08:02.790 Casie Aviles: Yeah.
99 00:08:02.790 ⇒ 00:08:12.890 Mustafa Raja: Yeah, and so for, zero… for the first zip code, we want to get all the people that are residential pests. We should be able to do that with the query.
100 00:08:14.980 ⇒ 00:08:15.870 Casie Aviles: Yes.
101 00:08:17.950 ⇒ 00:08:18.700 Amber Lin: Okay.
102 00:08:19.180 ⇒ 00:08:25.480 Amber Lin: How long would it take to build a… MVP.
103 00:08:26.840 ⇒ 00:08:30.860 Casie Aviles: For just, this inspector sheet table?
104 00:08:31.050 ⇒ 00:08:36.939 Casie Aviles: I mean, yeah, the tables just for the inspector sheets? Or do we want, like, all the sheets now?
105 00:08:38.490 ⇒ 00:08:41.099 Amber Lin: Inspector sheet, I would say.
106 00:08:43.710 ⇒ 00:08:51.380 Casie Aviles: I think I’ll… I can give it, like, one day of work within that, probably, I can…
107 00:08:51.870 ⇒ 00:08:53.030 Casie Aviles: Set that up.
108 00:08:54.380 ⇒ 00:08:55.620 Amber Lin: Hmm, okay.
109 00:08:55.870 ⇒ 00:09:02.379 Amber Lin: … I think I would like Sam to help with this, or do you think, …
110 00:09:02.580 ⇒ 00:09:06.210 Amber Lin: Is Awash more helpful here, or is Sam more helpful here?
111 00:09:08.130 ⇒ 00:09:15.120 Casie Aviles: I’m… to be honest, I’m not super sure how much Sam knows about…
112 00:09:16.170 ⇒ 00:09:20.260 Casie Aviles: How much input he can give with this setup?
113 00:09:21.640 ⇒ 00:09:24.370 Casie Aviles: On the other hand, Awish…
114 00:09:24.480 ⇒ 00:09:35.770 Casie Aviles: maybe he can, I’m not sure either, like, if he’s worked extensively with databases, like, me also, like, I’m not super very well-versed
115 00:09:35.900 ⇒ 00:09:42.429 Casie Aviles: With databases, but this is… Mostly based on my test, as well, from the spike.
116 00:09:43.190 ⇒ 00:09:44.310 Amber Lin: Hmm, okay.
117 00:09:44.560 ⇒ 00:09:45.510 Amber Lin: …
118 00:09:45.880 ⇒ 00:09:56.150 Amber Lin: I guess my last question is, when we have the inspector sheet, and then we have, the skills and zips, and also the area codes, how are we gonna…
119 00:09:56.760 ⇒ 00:10:04.149 Amber Lin: deal with all those fields. Are they gonna go into assignments, or are they gonna be a different table of assignments?
120 00:10:05.910 ⇒ 00:10:07.350 Casie Aviles: The area codes.
121 00:10:08.220 ⇒ 00:10:12.519 Amber Lin: Yeah, if we want to add skills and zips after this, how would.
122 00:10:12.520 ⇒ 00:10:14.179 Casie Aviles: Oh, skeleton zips.
123 00:10:15.580 ⇒ 00:10:21.060 Casie Aviles: I think we… we might be… we might do a similar setup, right? Because…
124 00:10:21.860 ⇒ 00:10:27.420 Casie Aviles: It’s… it’s like… it’s also zip-based, and then there’s also another person.
125 00:10:27.960 ⇒ 00:10:30.369 Casie Aviles: And then there’s also their role.
126 00:10:30.530 ⇒ 00:10:36.500 Casie Aviles: So I think this is… it’s going to be more or less a similar setup with inspectors.
127 00:10:37.040 ⇒ 00:10:43.559 Amber Lin: Okay, I think the zip codes I asked are all the same, so it sounds like we’re gonna add another, like.
128 00:10:43.960 ⇒ 00:10:55.800 Amber Lin: people table, and then add another… maybe extend, or add another people table, and then… add a…
129 00:10:56.150 ⇒ 00:11:00.739 Amber Lin: Assignments table for skills and tips.
130 00:11:02.560 ⇒ 00:11:03.789 Casie Aviles: Okay. Yeah, yeah.
131 00:11:03.790 ⇒ 00:11:06.899 Amber Lin: I don’t know, because we can also combine it in there.
132 00:11:07.630 ⇒ 00:11:09.429 Casie Aviles: So, we can have just one….
133 00:11:11.380 ⇒ 00:11:12.330 Amber Lin: Why? Yeah.
134 00:11:12.340 ⇒ 00:11:13.080 Casie Aviles: We’ll just keep.
135 00:11:13.080 ⇒ 00:11:17.610 Amber Lin: Going into techs, but it might get confusing.
136 00:11:17.860 ⇒ 00:11:26.200 Amber Lin: … They… so, the main three spreadsheets are the inspectors, the techs, and then the…
137 00:11:26.450 ⇒ 00:11:31.640 Amber Lin: Area codes of, oh, do they service this area or not?
138 00:11:31.790 ⇒ 00:11:36.740 Amber Lin: I do think that one’s pretty important, and ideally, we want to…
139 00:11:37.200 ⇒ 00:11:45.470 Amber Lin: Answered the question, do they even service here first before we assign any texts or, ….
140 00:11:45.870 ⇒ 00:11:49.620 Casie Aviles: Assigning tech for inspectors. How are we gonna add that one?
141 00:11:51.190 ⇒ 00:11:56.479 Casie Aviles: My best guess for that is we will have, like, another column, probably.
142 00:11:56.960 ⇒ 00:11:57.570 Casie Aviles: Where….
143 00:11:57.570 ⇒ 00:11:58.200 Amber Lin: Hmm.
144 00:11:58.750 ⇒ 00:12:01.259 Casie Aviles: We would attach it to this zip.
145 00:12:01.430 ⇒ 00:12:05.630 Casie Aviles: Two locations, and then maybe we add, like, …
146 00:12:06.140 ⇒ 00:12:11.929 Casie Aviles: do we… like, another column where… do we service this or not? And then it’s going to be a Boolean.
147 00:12:12.090 ⇒ 00:12:13.729 Casie Aviles: Like a true or false.
148 00:12:15.110 ⇒ 00:12:16.020 Casie Aviles: Column.
149 00:12:16.020 ⇒ 00:12:20.409 Amber Lin: I think the problem is that the surveys, …
150 00:12:20.800 ⇒ 00:12:23.579 Amber Lin: Yes or no is based on which service.
151 00:12:24.250 ⇒ 00:12:27.599 Casie Aviles: Oh, okay, so there’s going to be a lot of services.
152 00:12:28.020 ⇒ 00:12:33.370 Amber Lin: Yeah, so I’m worried that if we add it to the locations, it’ll get really big.
153 00:12:34.790 ⇒ 00:12:42.250 Amber Lin: But then we might end up with the same amount of current tables they have. But maybe it’s better? I don’t know.
154 00:12:43.590 ⇒ 00:12:44.430 Casie Aviles: Yeah, no.
155 00:12:44.430 ⇒ 00:12:45.120 Amber Lin: everyone.
156 00:12:45.430 ⇒ 00:12:49.630 Amber Lin: These tables to relate with each other based on the zip codes.
157 00:12:51.500 ⇒ 00:12:55.080 Casie Aviles: Okay, yeah, that part I haven’t thought as far.
158 00:13:00.460 ⇒ 00:13:01.750 Amber Lin: ….
159 00:13:07.870 ⇒ 00:13:13.400 Casie Aviles: So, I guess what we have to focus on for now is… the…
160 00:13:14.360 ⇒ 00:13:18.020 Casie Aviles: the service areas, right? That’s what we want to start with.
161 00:13:19.800 ⇒ 00:13:23.279 Amber Lin: Mmm… Let’s check that sheet.
162 00:13:37.670 ⇒ 00:13:40.320 Amber Lin: I think it’s at the bottom.
163 00:13:40.550 ⇒ 00:13:41.720 Amber Lin: Yeah.
164 00:13:45.520 ⇒ 00:13:53.560 Amber Lin: And, as you can see, it doesn’t directly relate To the inspector sheet.
165 00:13:53.960 ⇒ 00:13:55.720 Amber Lin: services.
166 00:13:56.660 ⇒ 00:14:03.120 Amber Lin: So… I just feel like it’s getting more and more complex, and we might have to…
167 00:14:03.450 ⇒ 00:14:06.010 Amber Lin: Map the different services?
168 00:14:06.380 ⇒ 00:14:17.720 Amber Lin: to say… I feel like… Residential pests and termite covers WDIs, covers regular… Presidential Pest.
169 00:14:18.350 ⇒ 00:14:19.590 Amber Lin: …
170 00:14:26.260 ⇒ 00:14:27.260 Amber Lin: And….
171 00:14:48.740 ⇒ 00:14:51.970 Casie Aviles: Yeah, okay, … Take a look.
172 00:14:53.510 ⇒ 00:14:55.840 Casie Aviles: That’s the problem here, I think, at the point.
173 00:14:55.840 ⇒ 00:14:56.230 Amber Lin: Maxine.
174 00:14:56.230 ⇒ 00:15:01.590 Casie Aviles: There’s, like, a lot of… That we want to account for.
175 00:15:01.890 ⇒ 00:15:10.709 Amber Lin: Yeah, … at least the zip codes are the same. … like, worst case, we can copy over.
176 00:15:11.010 ⇒ 00:15:15.550 Amber Lin: These… Yeah. And….
177 00:15:15.730 ⇒ 00:15:20.549 Casie Aviles: I think we could definitely start with at least this table here.
178 00:15:20.550 ⇒ 00:15:21.220 Amber Lin: Yeah.
179 00:15:21.600 ⇒ 00:15:22.870 Amber Lin: Yeah, totally.
180 00:15:24.110 ⇒ 00:15:24.840 Casie Aviles: Okay.
181 00:15:25.710 ⇒ 00:15:32.620 Amber Lin: Yeah, that one, … Let’s see… Mmm…
182 00:15:33.190 ⇒ 00:15:36.589 Amber Lin: That one doesn’t give you the…
183 00:15:37.560 ⇒ 00:15:43.389 Amber Lin: say, quadrant groups. If you click on the original inspector sheets.
184 00:15:43.910 ⇒ 00:15:51.960 Amber Lin: Or even the skills and zip sheet. You can see that some parts of Austin… …
185 00:15:57.170 ⇒ 00:16:05.689 Amber Lin: Yeah, that, for example, yeah, these are under Northwest, and they also want those quadrants.
186 00:16:06.260 ⇒ 00:16:07.010 Casie Aviles: Hmm.
187 00:16:07.390 ⇒ 00:16:08.620 Amber Lin: So… Yup.
188 00:16:10.490 ⇒ 00:16:11.840 Casie Aviles: You can add that here, yard.
189 00:16:12.240 ⇒ 00:16:23.499 Amber Lin: Okay, so we have town name, area, and then branch. I don’t know. Branch would be Austin, and then Quadrant would be, say, Austin North.
190 00:16:24.020 ⇒ 00:16:27.129 Casie Aviles: Yeah, something like this. Then we just added.
191 00:16:29.580 ⇒ 00:16:30.690 Amber Lin: Mmm….
192 00:16:33.630 ⇒ 00:16:35.149 Casie Aviles: Yeah, but something like that.
193 00:16:36.110 ⇒ 00:16:36.550 Amber Lin: I see.
194 00:16:36.550 ⇒ 00:16:38.060 Casie Aviles: That’s another column.
195 00:16:38.230 ⇒ 00:16:41.589 Casie Aviles: And then this will be, yeah, Austin, Georgetown….
196 00:16:42.190 ⇒ 00:16:43.010 Amber Lin: Okay.
197 00:16:47.040 ⇒ 00:16:49.950 Casie Aviles: Yeah, I can definitely start with at least that.
198 00:16:50.300 ⇒ 00:16:51.010 Amber Lin: Yeah.
199 00:16:52.200 ⇒ 00:16:53.260 Amber Lin: That’s good.
200 00:16:53.420 ⇒ 00:17:00.099 Amber Lin: And then… I think Utam probably will be the best person, …
201 00:17:00.410 ⇒ 00:17:08.640 Amber Lin: I think I’m in your doc as well, so probably we’ll ask them the question of, okay, we have…
202 00:17:09.589 ⇒ 00:17:13.610 Amber Lin: a few tables. How did you make that diagram?
203 00:17:14.140 ⇒ 00:17:15.669 Casie Aviles: Oh, it’s, it’s….
204 00:17:15.670 ⇒ 00:17:18.089 Amber Lin: part of Supabase, so you can just….
205 00:17:18.170 ⇒ 00:17:19.260 Casie Aviles: directly.
206 00:17:20.460 ⇒ 00:17:23.300 Casie Aviles: It generates it for us, so I just screenshotted this.
207 00:17:23.300 ⇒ 00:17:26.880 Amber Lin: Oh… I see.
208 00:17:30.240 ⇒ 00:17:30.980 Amber Lin: Okay.
209 00:17:31.520 ⇒ 00:17:34.799 Amber Lin: I think what we need, other than this, is a…
210 00:17:35.480 ⇒ 00:17:39.280 Amber Lin: Service area code, and after we add that, we might…
211 00:17:40.060 ⇒ 00:17:45.060 Amber Lin: End up having to map services to the different area codes.
212 00:17:45.790 ⇒ 00:17:50.360 Amber Lin: … Or we can just expand it, I don’t know.
213 00:17:50.520 ⇒ 00:17:51.060 Amber Lin: Who knows?
214 00:17:51.060 ⇒ 00:17:51.740 Casie Aviles: Yes.
215 00:17:56.610 ⇒ 00:18:00.879 Amber Lin: Yeah, because we can expand residential paths to include all the different…
216 00:18:01.070 ⇒ 00:18:06.250 Amber Lin: columns. Or we can just create a mapping of their different services.
217 00:18:07.700 ⇒ 00:18:08.829 Casie Aviles: Hmm, yeah, yeah.
218 00:18:09.710 ⇒ 00:18:10.510 Amber Lin: Yeah.
219 00:18:16.790 ⇒ 00:18:28.440 Amber Lin: Okay. What happens when they ask about residential pests, but it’s a different spelling as what we have it in there? Will it recognize us?
220 00:18:30.090 ⇒ 00:18:33.019 Casie Aviles: Oh, for incorrect spellings, I…
221 00:18:33.920 ⇒ 00:18:36.289 Casie Aviles: Actually, I haven’t tested that out with the….
222 00:18:38.110 ⇒ 00:18:38.890 Amber Lin: Hmm.
223 00:18:39.490 ⇒ 00:18:44.899 Casie Aviles: But I think that the query engine that is powering this is also AI.
224 00:18:44.960 ⇒ 00:18:46.270 Amber Lin: And….
225 00:18:47.200 ⇒ 00:18:52.500 Casie Aviles: Basically, what it does is it also has… context on…
226 00:18:53.280 ⇒ 00:18:56.479 Casie Aviles: Not sure if I can run all of this right now.
227 00:18:59.530 ⇒ 00:19:04.159 Casie Aviles: But basically, it’s also AI, so it just converts our….
228 00:19:04.160 ⇒ 00:19:05.460 Amber Lin: Oh….
229 00:19:05.460 ⇒ 00:19:07.319 Casie Aviles: Our text, our input.
230 00:19:08.000 ⇒ 00:19:12.420 Casie Aviles: and converts it into a SQL query, and it also has context.
231 00:19:12.950 ⇒ 00:19:14.380 Casie Aviles: on the tables.
232 00:19:15.010 ⇒ 00:19:17.170 Amber Lin: Oh, I got it. Paint.
233 00:19:18.180 ⇒ 00:19:26.309 Casie Aviles: So I think it should be… should be doable, should be possible, like, the typos probably won’t be too big of a problem.
234 00:19:26.770 ⇒ 00:19:34.630 Amber Lin: Okay, I see. Sounds good. Let’s get started on this. … all…
235 00:19:35.270 ⇒ 00:19:43.420 Amber Lin: if you can send… I think the doc is already in the chat… in the channel. I’ll add my questions there, and then ask…
236 00:19:43.530 ⇒ 00:19:50.599 Amber Lin: While you build, I’ll probably… ask Sutton for some input, because the difficult sheet doesn’t influence anything else.
237 00:19:51.560 ⇒ 00:19:51.960 Casie Aviles: Okay.
238 00:19:51.960 ⇒ 00:19:58.420 Amber Lin: Yeah, and on the insomnia side, …
239 00:19:58.830 ⇒ 00:20:02.909 Amber Lin: Were you able to work on it yesterday, or were you working on internal stuff?
240 00:20:03.580 ⇒ 00:20:06.850 Casie Aviles: Yeah, it’s, yesterday I worked mostly on
241 00:20:07.160 ⇒ 00:20:11.730 Casie Aviles: The internal stuff, and then the manual… backfill stuff.
242 00:20:12.320 ⇒ 00:20:13.750 Amber Lin: For the daily.
243 00:20:14.370 ⇒ 00:20:15.380 Amber Lin: ….
244 00:20:15.380 ⇒ 00:20:21.490 Casie Aviles: I’ll have time to work on the… on FDA for Uber today.
245 00:20:21.640 ⇒ 00:20:22.690 Amber Lin: Okay.
246 00:20:24.110 ⇒ 00:20:26.290 Amber Lin: Awesome. …
247 00:20:28.230 ⇒ 00:20:38.660 Amber Lin: Yeah, that sounds good. I’ll cancel the stand-up. Feel free to push back the real dashboarding stuff for…
248 00:20:39.040 ⇒ 00:20:42.480 Amber Lin: What do you, for your data platform back.
249 00:20:42.890 ⇒ 00:20:45.209 Amber Lin: Okay. Yeah. Sounds good.
250 00:20:45.490 ⇒ 00:20:47.249 Amber Lin: That was all that I had.
251 00:20:47.960 ⇒ 00:20:53.150 Casie Aviles: Alright then, … I’ll go make a ticket for this one.
252 00:20:53.590 ⇒ 00:20:54.680 Amber Lin: Okay.
253 00:20:56.020 ⇒ 00:20:56.639 Amber Lin: Thank you.
254 00:20:57.320 ⇒ 00:20:58.580 Casie Aviles: Thank you, guys.
255 00:20:59.130 ⇒ 00:20:59.720 Amber Lin: Right.
256 00:20:59.980 ⇒ 00:21:00.970 Amber Lin: Bye!