Book Image

Learning Google BigQuery

By : Thirukkumaran Haridass, Mikhail Berlyant, Eric Brown
Book Image

Learning Google BigQuery

By: Thirukkumaran Haridass, Mikhail Berlyant, Eric Brown

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)
Free Chapter
Google Cloud and Google BigQuery

Using the gcloud utility

The gcloud utility is used to interact with the rest of the services on the Google Cloud Platform, other than BigQuery and Google Cloud Storage. The commands in the gcloud utility are grouped for each service. The following are the service groups for some of the services on the Google Cloud Platform:

Service group

Google Cloud service


App Engine standard and flexible environment


Compute Engine to manage virtual machines


Container Engine to manage containers and clusters


Manage Cloud Dataflow services for ETL and data processing


Manage Cloud Dataproc service which consists of Apache Hadoop, Spark, Pig, and Hive


Manage Cloud Datastore service which creates entities on a NoSQL database


Manage Cloud SQL service which consists of MySQL or PostgreSQL databases...