What is the reason behind Google’s investment in geospatial analysis?
Javier de la Torre: Hey Chad! It’s great having you here today. We’re very impressed by the work that Google is doing, with everything around you, especially around BigQuery. We wanted to come and ask you first, how has the adoption been? And what is the reasoning behind this investment by Google on geospatial?
Chad W. Jennings: Well, first off, thanks for having us out. The event you put on here is really impressive, and the energy in the room, it’s really fun to be a part of it. But to answer your question, the investment that we’re making in geospatial analysis inside of BigQuery is, basically, we want to bring very big data infrastructure to geospatial analysis. Folks had been constrained by the hardware that they’ve been able to use and by the software that they’ve been able to use and putting BigQuery and GIS together into the same thing basically takes the brakes off. And folks are noticing it, right? The adoption that we’ve seen, like the number of new projects, the number of new bytes processed every month, has been climbing very gratifyingly.
What problem is CARTO solving for Google BigQuery?
Javier de la Torre: This is great. I think BigQuery represents an incredible milestone, in terms of architecture for spatial data infrastructures. We are impressed by the performance in terms of scalability, but also things like the public data collect partnership that we are publishing in the sense of having geospatial data already built-in. We think it’s fantastic. So, I think it’s a key part of a project.
Chad W. Jennings: No, I totally agree. When we were designing the public datasets program… And for those who don’t know, there are a whole bunch of data sets inside of BigQuery that Google hosts because they’re just useful or they’re interesting. But we did a bunch of research and found out which ones folks were using the most with their own data. And we found out it was kind of all the boring ones, like administrative tasks and things that folks just… like a table that they need for reference. And so when we learned that, we doubled down on that. So administrative boundaries, zip code polygons and the stuff that we’re doing with you: it’s just all of that data that’s tough to find or annoying to put together into one shape. Now it’s just going to be there. To use your expression, the batteries are included in this gift. It’s just ready to run.
What is the main benefit for your users?
Javier de la Torre: Big time. And this is why we are so excited with the data observatory, to have actually collaborated with you. We think it is an incredible platform. It’s going to change the way that people access location data. And we cannot wait to see this evolving and getting more usage.
Chad W. Jennings: Yeah, folks aren’t going to have to spend 80% of their time getting their data in. They’re just going to sit down and be like, “Oh, I can get to work, now.” Yeah. We’re very, very excited to see what people do, so let us know.
Javier de la Torre: Thank you very much, Chad.
Chad W. Jennings: It was my pleasure. Thank you.