But that's just a bunch of words. What does it mean in practice? So here I am on the BigQuery console. BigQuery is a data warehouse. And here I'm basically gonna be querying a public data set of Medicare claims, and I'm looking at Medicare claims in 2014. This is an ad hoc query, so I did not create indices. I did not prepare the database to make this query efficient or anything like that. This is an ad hoc query. I'm just gonna be running it on this particular data set, grouping it by state and ordering it by the total claim count. So what you're gonna find out is which states in the U.S. had the most number of claims. So let's go ahead and run this query. And we just processed 276 megs of data, and that's because BigQuery's a columnar database and we just processed a couple of columns. And about 3 seconds later, we get back that California had the maximum number of claims, and Florida had the next higher amount of claims. Notice the claim amounts-- they're in the millions. This particular table-- Let's go ahead and look at it. It's in BigQuery public data. So, in BigQuery public data, it's in Medicare. And part D, prescriber 2014. This particular data set has about 24 million rows. So we were able to do an ad hoc query on a data set that's about 24 million rows in a matter of seconds. And we were able to do this without provisioning any virtual machines, installing any software. We just ran the query. This is what we mean when we say "third wave cloud." We're talking about fully managed services that autoscale for you, that all that you need to do is to write some code and have it be executed by managed infrastructure.