Working with JSON, Arrays, and Structs in BigQuery
BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
This lab is an in-depth walkthrough of working with semi-structured data (ingesting JSON, Array data types) inside of BigQuery. Denormalizing your schema into a single table with nested and repeated fields can yield performance improvements, but the SQL syntax for working with array data can be tricky. You will practice loading, querying, troubleshooting, and unnesting various semi-structured datasets.
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Create a new dataset and table to store the data
Execute the query to see how many unique products were viewed
Execute the query to use the UNNEST() on array field
Create a dataset and a table to ingest JSON data
Execute the query to COUNT how many racers were there in total
Execute the query that will list the total race time for racers whose names begin with R
Execute the query to see which runner ran fastest lap time