This chapter explores advanced options in BigQuery SQL. It explains partition tables in BigQuery and how to query data from partition tables. Sharding of tables is explained as an option to store data across multiple tables to save on billing. Built-in functions are explained for various categories such as datetime, strings, numbers, and so on.
-
Book Overview & Buying
-
Table Of Contents
-
Feedback & Rating
Learning Google BigQuery
By :
Learning Google BigQuery
By:
Overview of this book
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.
Table of Contents (9 chapters)
Preface
Free Chapter
Google Cloud and Google BigQuery
Google Cloud SDK
Google BigQuery Data Types
BigQuery SQL Basic
BigQuery SQL Advanced
Google BigQuery API
Visualizing BigQuery Data
Customer Reviews
