Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale
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Work with petabyte-scale datasets while building a collaborative, agile workplace in the process. This practical book is the canonical reference to Google BigQuery, the query engine that lets you conduct interactive analysis of large datasets. BigQuery enables enterprises to efficiently store, query, ingest, and learn from their data in a convenient framework. With this book, you’ll examine how to analyze data at scale to derive insights from large datasets efficiently.
Valliappa Lakshmanan, tech lead for Google Cloud Platform, and Jordan Tigani, engineering director for the BigQuery team, provide best practices for modern data warehousing within an autoscaled, serverless public cloud. Whether you want to explore parts of BigQuery you’re not familiar with or prefer to focus on specific tasks, this reference is indispensable.
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Publisher : O’Reilly Media; 1st edition (December 3, 2019)
Language : English
Paperback : 519 pages
ISBN-10 : 1492044466
ISBN-13 : 978-1492044468
Item Weight : 1.81 pounds
Dimensions : 7 x 1.05 x 9.19 inches
From the Preface
Enterprises are becoming increasingly data driven, and a key component of any enterprise’s data strategy is a data warehouse—a central repository of integrated data from all across the company. Traditionally, the data warehouse was used by data analysts to create analytical reports. But now it is also increasingly used to populate real-time dashboards, to make ad hoc queries, and to provide decision-making guidance through predictive analytics. Because of these business requirements for advanced analytics and a trend toward cost control, agility, and self-service data access, many organizations are moving to cloud-based data warehouses such as Google BigQuery.
In this book, we provide a thorough tour of BigQuery, a serverless, highly scalable, low-cost enterprise data warehouse that is available on Google Cloud. Because there is no infrastructure to manage, enterprises can focus on analyzing data to find meaningful insights using familiar SQL.
Our goal with BigQuery has been to build a data platform that provides leading-edge capabilities, takes advantage of the many great technologies that are now available in cloud environments, and supports tried-and-true data technologies that are still relevant today. For example, on the leading edge, Google’s BigQuery is a serverless compute architecture that decouples compute and storage
This enables diverse layers of the architecture to perform and scale independently, and it gives data developers flexibility in design and deployment. Somewhat uniquely, BigQuery supports native machine learning and geospatial analysis. With Cloud Pub/Sub, Cloud Dataflow, Cloud Bigtable, Cloud AI Platform, and many third-party integrations, BigQuery interoperates with both traditional and modern systems, at a wide range of desired throughput and latency. And on the tried-and-true front, BigQuery supports ANSI-standard SQL, columnar optimization, and federated queries, which are key to the self-service ad hoc data exploration that many users demand.
Who Is This Book For?
This book is for data analysts, data engineers, and data scientists who want to use BigQuery to derive insights from large datasets. Data analysts can interact with BigQuery through SQL and via dashboarding tools like Looker, Data Studio, and Tableau.
Data engineers can integrate BigQuery with data pipelines written in Python or Java and using frameworks such as Apache Spark and Apache Beam. Data scientists can build machine learning models in BigQuery, run TensorFlow models on data in BigQuery, and delegate distributed, large-scale operations to BigQuery from within a Jupyter notebook.
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11 reviews for Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale
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Iroh Aso –
Detailed and practical
This is exactly what I need. Thank you, Valliappa and Jordan.
MO CONVERY –
Great book that makes up for the official documentation’s shortcomings
Clearly written, great examples, still useful even though it’s now a few years old.Used copy arrived quickly and in fantastic condition.
Yannick Pouliot –
Excellent coverage of BigQuwry
Everything I need to know about BQ seems to be covered in this great book, concisely written. Just what I needed as a beginner to BQ, though note that the book goes far beyond beginner topics!
Wayne –
High Quality Book and examples
Exactly kind of quality I expect from this author. Bought several books and very impressed. Quality of work and examples are some of the best
HockeyCanMan –
The missing manual
Comprehensive, detailed and written with excellent examples. Up to date on the new feature set. Required reading.
Larry H –
Knowledge is Power
Excellent info for learning.
Anonymous –
Absolutely ridiculous!
Laura –
Pelo preço, a impressão deveria ser colorida. A compreensão, em diversas partes do livro, fica compreometida. Gráficos e tabelas impressos em preto e branco perdem resolução e ficam claros demais para leitura e aproveitamento. Não recomendo a versão impressa.
Kevs –
Un poco desactualizado aunque hay un repo de github con enlaces a las nuevas funcionalidades que no cubre el libro, aún asi creo que es algo caro
Cliente Amazon –
Libro consigliatissimo
Client d’Amazon –
Bonjour,Je dois modifier mon premier commentaire hâtif que j’avais fait basé sur le seul chapitre qui m’intéressait à l’époque de la commande, à savoir l’architecture, et qui n’est pas le meilleur chapitre du livre à mon goût. Mais passé ce chapitre qui est tout de même intéressant si on lit toute la documentation proposée en annexe, tous les autres chapitres sont bien expliqués. Il y a un talent de vulgarisation évident de l’auteur tout en restant technique et donc assez clair. Il y a une volonté d’exhaustivité sans bâcler les chapitres ; les principaux sujets sont abordés, machine learning, sql, performance, intégration dans l’écosystème GCP, etc … et donc la partie architecture. L’auteur est après tout un ingénieur qui a traité des sujets au sein de Google (je reprend un des passages du livre)Cordialement.