Cloud Analytics with Google Cloud Platform

Cloud analytics brings two big ideas together: on-demand computing and the work of turning data into useful insight. Sanket Thodge’s guide starts with the decisions behind cloud adoption, then turns to Google Cloud Platform (GCP) and the services that can be assembled into an analytics pipeline. It’s a practical-minded introduction for readers who want to understand both the architecture choices and the tools involved.

Start with the cloud, not just the tools

Before focusing on GCP, the book lays out cloud-computing fundamentals, including public, private, and hybrid deployments and the differences between IaaS, PaaS, and SaaS. It also considers security, migration, infrastructure, and business requirements—useful context for understanding why a service might fit one organization’s needs better than another’s.

See how GCP services fit together

The GCP-focused material surveys services across compute, storage, databases, and networking, then connects those building blocks to data work. Readers encounter topics such as data ingestion, processing, analysis, and visualization, with services including Cloud Pub/Sub, BigQuery, and Cloud Dataproc appearing in the book’s discussion.

Follow the analytics pipeline

Rather than treating analytics as a single tool, the book considers the stages involved in moving data through a cloud environment. Its end-to-end perspective helps readers think about how service choices relate to one another, from bringing data in to processing it and drawing insights from it. Practical use cases accompany the technical explanations.

Broader cloud context, too

GCP is the central focus, but comparisons with other major cloud platforms give readers a wider frame for evaluating alternatives. The guide also introduces machine learning and artificial intelligence applications in analytics, extending the discussion beyond storage and data processing.

Who may find it useful

This book is aimed at technology leaders, analytics professionals, and data practitioners exploring cloud-based analytics. Readers new to GCP can use the early material to build context; some familiarity with a development language is helpful, while SQL and Unix skills are relevant to certain services.

For readers planning or learning an analytics workflow on Google Cloud, Thodge’s book offers a route from cloud fundamentals to the components and considerations behind a more complete data pipeline.