Book description
Get a fundamental understanding of how Google BigQuery works by analyzing and querying large datasets
About This Book
- Get started with BigQuery API and write custom applications using it
- Learn how BigQuery API can be used for storing, managing, and query massive datasets with ease
- A practical guide with examples and use-cases to teach you everything you need to know about Google BigQuery
Who This Book Is For
If you are a developer, data analyst, or a data scientist looking to run complex queries over thousands of records in seconds, this book will help you. No prior experience of working with BigQuery is assumed.
What You Will Learn
- Get a hands-on introduction to Google Cloud Platform and its services
- Understand the different data types supported by Google BigQuery
- Migrate your enterprise data to BigQuery and query it using the legacy and standard SQL techniques
- Use partition tables in your project and query external data sources and wild card tables
- Create tables and data sets dynamically using the BigQuery API
- Perform real-time inserting of records for analytics using Python and C#
- Visualize your BigQuery data by connecting it to third party tools such as Tableau and R
- Master the Google Cloud Pub/Sub for implementing real-time reporting and analytics of your Big Data
In Detail
Google BigQuery is a popular cloud data warehouse for large-scale data analytics. This book will serve as a comprehensive guide to mastering BigQuery, and how you can utilize it to quickly and efficiently get useful insights from your Big Data.
You will begin with getting a quick overview of the Google Cloud Platform and the various services it supports. Then, you will be introduced to the Google BigQuery API and how it fits within in the framework of GCP. The book covers useful techniques to migrate your existing data from your enterprise to Google BigQuery, as well as readying and optimizing it for analysis. You will perform basic as well as advanced data querying using BigQuery, and connect the results to various third party tools for reporting and visualization purposes such as R and Tableau. If you're looking to implement real-time reporting of your streaming data running in your enterprise, this book will also help you.
This book also provides tips, best practices and mistakes to avoid while working with Google BigQuery and services that interact with it. By the time you're done with it, you will have set a solid foundation in working with BigQuery to solve even the trickiest of data problems.
Style and Approach
This book follows a step-by-step approach to teach readers the concepts of Google BigQuery using SQL. To explain various data querying processes, large-scale datasets are used wherever required.
Table of contents
- Preface
- Google Cloud and Google BigQuery
- Google Cloud SDK
-
Google BigQuery Data Types
- Supported data types
- Data type considerations
- Converting data
- Sanitizing data
- When to transform your data? Before or after loading to BigQuery?
- Arithmetic Operators
- Comparison Operators
- Date Time Functions
- String Functions
- Regular Expression Functions
- Functions for transformation
- Mastering transformation with User-Defined Functions
- Summary
- Further Reading
- BigQuery SQL Basic
- BigQuery SQL Advanced
-
Google BigQuery API
- Accessing Google BigQuery
-
Programming with BigQuery API in C# .NET
- Authenticating the service account
- Listing all datasets and all tables in the project
- Creating a new dataset in the project
- Creating a new table within a dataset
- Loading data from a file in Google Cloud Storage to a BigQuery table
- Executing a query and displaying the result
- Executing the query and saving the result in a new table
- Streaming insert of rows
-
Programming with BigQuery API in Python
- Listing all datasets and all tables in the project
- Creating a new dataset in the project
- Creating a new table within a dataset
- Importing data from a file in Google Cloud Storage to a BigQuery table
- Executing a query and displaying the result
- Execute query and copy results to a new table
- Streaming insert of rows
- Roles and permissions
- Summary
-
Visualizing BigQuery Data
- Why is data visualization important?
- The danger of summary statistics
- Making data visualization work for you
- Three tools for visualizing BigQuery data
- Summary
- Google Cloud Pub/Sub
Product information
- Title: Learning Google BigQuery
- Author(s):
- Release date: December 2017
- Publisher(s): Packt Publishing
- ISBN: 9781787288591
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