Book Image

Cloud Analytics with Google Cloud Platform

By : Sanket Thodge
Book Image

Cloud Analytics with Google Cloud Platform

By: Sanket Thodge

Overview of this book

With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation
Table of Contents (16 chapters)
Title Page
Packt Upsell
Foreword
Contributors
Preface
Index

Cloud BigTable


Cloud BigTable is a high-performance NoSQL database service for large analytical and operational workloads. BigTable is a sparse, distributed, persistent, and multi-dimensional sorted map. The map is indexed by a row key, column key, and a timestamp.

When to use it

Cloud BigTable is used mainly for large-scale, low-latency applications; throughput-intensive data processing; and analytics.

We can also use Cloud BigTable to store very large amounts of single-keyed data with very low latency.

Special features

Cloud BigTable is designed to handle massive workloads at consistent low latency and high read-write throughput. For IoT, user analytics, and financial data analysis, it is also a great choice for operational and analytical application.

It is a petabyte-scale service and can be easily integrated with Hadoop, GCP Dataflow, and GCP Dataproc. Apache HBase and Cloud BigTable support open-source industry standard HBase API.

Encryption of data is done in both ways: in flight and at rest...