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
1
Google Cloud and Google BigQuery

Visualizing BigQuery Data

"The purpose of visualization is insight, not pictures."

―Ben Shneiderman

Access to data ensures that we have a part of the story. We use this data to learn about some intricacies with respect to the performance of a website, marketing campaign, CRM program, or whatever we have data warehoused for. With that said, data itself can only answer some of the questions that most analysts will have. Most of the time, an analyst will need additional help to find the answers they are looking for (or at least to efficiently find those answers). Every analyst dealing with data should strongly consider adding data visualization to their arsenal of tools.