And what does it tell us?
BigQuery is a fully managed, petabyte-scale analytics data warehouse that enables businesses to analyze all their data very quickly. It is a cloud-based service that offers fast performance, scalability, and flexibility. BigQuery is easy to use and can be integrated with other Google Cloud Platform services.
Pro tip: now you can use BigQuery Studio to run notebooks and try out SQL in this blog post directly within BigQuery.
Using the data loader
Now that we’ve climbed the “Hello world!” mountain, let’s learn how to use the document loader. We’ll use data from a fictional eCommerce clothing site called TheLook, available as a BigQuery public dataset.
Let’s say we’re starting from scratch with a bunch of tables we don’t know well. And our marketing team is about to start a campaign in Japan, oh my! Can we ask the LLM to identify our target customers?
The first step to understanding our data is loading it. Let’s query the schema from this dataset to extract the data definition language (DDL). DDL is used to create and modify tables, and can tell us about each column and its type.
As a prerequisite, let’s make sure we have the BigQuery client library installed:
