Learning Google BigQuery

By : Berlyant, Haridass, Brown

3.3 (4)

Buy this Book

Learning Google BigQuery

3.3 (4)

By: Berlyant, Haridass, Brown

Buy this Book

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.

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

Google Cloud and Google BigQuery

Getting started with Google Cloud

Summary

Google Cloud SDK

Installing Google Cloud SDK

gsutil for Google Cloud Storage

Using the bq utility for BigQuery

Using the gcloud utility

Connecting to Cloud SQL using gcloud

Deploying to Google App Engine

Summary

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

Making data visualization work for you

Here are a few tips for making actionable and efficient visualizations:

Consider your audience:
- Keep the decisions made by each of your audience in mind. A paid search analyst will want to look at the differences in ROI for different paid search campaigns, while a social media manager will want to know which posts drove the most visits. If you are unaware of the type of data desired by the end user, set some time to discuss the goals of the project.
Choose chart types wisely:
- Be mindful of scales for line and bar charts.
- Pie charts and 3D charts should be avoided. In most situations, pie charts can be replaced with bar charts.
Show only what is important:
- As initially stated, visualization's focus is to drive action. Do not confuse the viewer with overkill, either by too many charts or too many elements within a single chart...