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Google Cloud Big Data and Machine Learning Fundamentals

Exploring a BigQuery Public Dataset​

Storing and querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure. Simply move your data into BigQuery and let it handle the hard work. You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.

You access BigQuery through the Cloud Console, the command-line tool, or by making calls to the BigQuery REST API using a variety of client libraries such as Java, .NET, or Python. There are also a variety of third-party tools that you can use to interact with BigQuery, such as visualizing the data or loading the data. In this lab, you access BigQuery using the web UI.

You can use the BigQuery web UI in the Cloud Console as a visual interface to complete tasks like running queries, loading data, and exporting data. This hands-on lab shows you how to query tables in a public dataset and how to load sample data into BigQuery through the Cloud Console.

Objectives​

In this lab, you learn how to perform the following tasks:

  • Query a public dataset: In this task, you load a public dataset, USA Names, into BigQuery, then query the dataset to determine the most common names in the US between 1910 and 2013.
  • Create a custom table
  • Load data into a table
  • Query a table