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Introduction to BigQuery

Lab Details:

  1. This lab walks you through Cloud BigQuery.

  2. You will be creating a BigQuery Dataset and loading the CSV data.

  3. Region: us-central1

  4. Duration: 60 minutes

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What is BigQuery?

  • BigQuery is a fully managed big data tool for companies that need a cloud-based interactive query service for massive datasets. 

  • BigQuery is not a database, it's a query service. 

  • BigQuery supports SQL queries, which makes it quite user-friendly. It can be accessed from Console, CLI, or using SDK. You can query billions of rows, it only takes seconds to write, and seconds to return.

  • You can use its REST APIs and get your work done by sending a JSON request.

  • Let’s understand with help of an example, Suppose you are a data analyst and you need to analyze tons of data. If you choose a tool like traditional MySQL, you need to have an infrastructure ready, that can store this huge data.

  • You can focus on analysis rather than working on infrastructure. Hardware is completely abstracted.

  • Designing this infrastructure itself will be a difficult task because you will have to figure out RAM size, CPU type, or any other configurations.

  • BigQuery is mainly for Big Data. You shouldn’t confuse it with OLTP (Online Transaction Processing) database. 

Terms related to BigQuery:

  • Datasets: Datasets hold one or more tables of data.

  • Tables: Tables are row-column structures that hold actual data

  • Jobs: Operations that you perform on the data, such as loading data, running queries, or exporting data.

Lab Tasks:

  1. Login into the GCP Console.

  2. Creating a BigQuery Dataset.

  3. Create a Table.

  4. Loading the data through an external CSV.

  5. Reading data through the Table using SQL Query.



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