Over last three decades, the computing industry is moving in a definite direction. Big and centralized systems such as mainframes have been replaced by small virtual systems in cloud.

Instead of using computer hardware and software within a firm's own network or data-center (or an individual's laptop), the same computing power is available as a service and these services are offered by specialist companies. This computing power can be accessed over the internet seamlessly.

Personal devices such as tablets, PCs, and mobiles generate tens of trillions of data points. If someone can analyze such a volume of data then this offers countless possibilities to use such a data for larger good of the society which include ease in governance or businesses. Businesses make use of it for commercial gains. Cloud is the best and the most economical platform to introspect and comprehend such large volumes of data we all generate every minute these days.

However, analyzing such a large volume of data requires a huge cache of computing power which is expensive and capital intensive. One of the quick solutions is to utilize the on-demand and managed computing services in cloud which can be scaled within no time, put to use and discarded at the end of specific analysis. In fact, most cloud vendors offer specialized services which can be better described as analytics as a service.

It is not easy to foray into this technical domain. It involves learning the cloud, internals of cloud, hardware, software, virtualization and hundreds of services each cloud vendor offers.

This book simplifies complex topics such as cloud, types of cloud, their offerings and compares major cloud platforms such as Amazon AWS, Microsoft Azure and Google GCP for quick learning. Chapters in the book are dedicated to Google Cloud Platform specifically for analytics purpose and describes in great detail how to use the Google platform for such analytics.

This book not only demonstrates a detailed understanding of complex suite of tools offered by GCP for analytics, but also describes similar tools from other cloud vendors. This book dedicates many chapters to how to move data to GCP, ingest, analyze, visualize, and is inclusive of the use of artificial intelligence and machine learning techniques. Most importantly, the theoretical description is complemented by detailed discussion of use cases. Besides analytics, this book also describes the value of cloud certification and the required know-how for GCP Architect certification.

-Anand Vemula

Expert in AWS with 19 years of experience in software engineering and is the Vice President for world’s leading bank firm.