Optimizing BigQuery for Cost and Performance v1 5

Overview
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 focuses on how to architect a data warehouse for query performance. In this lab, you will compare a traditional relational schema with joins against a denormalized schema. You will also use BigQuery's Query Execution Plan to quantifiably assess performance trade-offs.

What you'll do
In this lab, you will learn how to perform these tasks:
- Load a comma-separated value (CSV) file into a BigQuery table using the web UI.
- Load a JavaScript® Object Notation (JSON) file into a BigQuery table using the command-line interface (CLI).
- Transform data and join tables using the web UI.
- Store query results in a destination table.
- Query a destination table using the web UI to confirm your data was transformed and loaded correctly.
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