Google BigQuery: The Definitive Guide

Regular price €65.99
A01=Jordan Tigani
A01=Valliappa Lakshmanan
Author_Jordan Tigani
Author_Valliappa Lakshmanan
Category=UN
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
google bigquery data warehouse big data data storage data analytics sql machine learning distributed queries geospatial data query engine

Product details

  • ISBN 9781492044468
  • Dimensions: 178 x 233mm
  • Publication Date: 29 Nov 2019
  • Publisher: O'Reilly Media
  • Publication City/Country: US
  • Product Form: Paperback
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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.
Valliappa (Lak) Lakshmanan is a Tech Lead for Big Data and Machine Learning Professional Services on Google Cloud Platform. His mission is to democratize machine learning so that it can be done by anyone anywhere using Google's amazing infrastructure (i.e., without deep knowledge of statistics or programming or ownership of lots of hardware). Jordan is engineering director for the core BigQuery team. He was one of the founding engineers on BigQuery, and helped grow it to be one of the most successful products in Google's Cloud Platform. He wrote the first book on BigQuery, and has also spoken widely on the subject. Jordan has twenty years of software development experience, ranging from Microsoft Research to Machine Learning startups.