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Learning Google BigQuery

Learning Google BigQuery

By : Berlyant, Haridass, Brown
3.3 (4)
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Learning Google BigQuery

Learning Google BigQuery

3.3 (4)
By: Berlyant, Haridass, 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)
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1
Google Cloud and Google BigQuery

Partition tables

Partition tables are special tables that store data at a daily level in separate internal tables. This helps to improve the query performance and also reduces billing by querying data using a specified date range. The following steps outline how to create the partition table for your projects using a GUI and Google Cloud SDK.

Creating a partition table using a GUI

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