Troubleshooting Common SQL Errors with 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 you can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
A newly available ecommerce dataset that has millions of Google Analytics records for the Google Merchandise Store has been loaded into BigQuery. You have a copy of that dataset for this lab and will explore the available fields and row for insights.
This lab steps you through the logic of troubleshooting queries. It provides activities within the context of a real-world scenario. Throughout the lab, imagine you're working with a new data analyst on your team, and they've provided you with their queries below to answer some questions on your ecommerce dataset. Use the answers to fix their queries to get a meaningful result.
What you'll do
In this lab, learn how to perform the following tasks:
Query the data-to-insights public dataset
Use the BigQuery Query editor to troubleshoot common SQL errors
Use the Query Validator
Troubleshoot syntax and logical SQL errors
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Find the total number of customers went through checkout
List the cities with the most transactions with your ecommerce site
Find the total number of products in each product category