Articles liés à Google BigQuery Analytics
Synopsis
How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addition to the mechanics of BigQuery, the book also covers the architecture of the underlying Dremel query engine, providing a thorough understanding that leads to better query results. Features a companion website that includes all code and data sets from the book Uses real-world examples to explain everything analysts need to know to effectively use BigQuery Includes web application examples coded in Python
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Quatrième de couverture
Run complex queries and write code with BigQuery If youre a data analyst, developer, or data scientist, BigQuery can save you big time, allowing you to run complex queries over billions of recordsand get answers in seconds. In Google BigQuery Analytics, youll learn how to use BigQuery effectively, avoid common pitfalls, and execute sophisticated queries against complex data sets. Explaining the hows and whys of BigQuery, this book gives expert advice to help you get your data in, get it out, and gain the most actionable insights from your analysis. Explains the details of authentication and communication with the BigQuery API Shows you how to get your data in and out of the service Demonstrates how to compose powerful queries from simple pieces Covers using the service from the Google Cloud Platform and from third–party tools Offers real–world examples that demonstrate current best practices and techniques Includes web application examples coded in Python, a popular language for big data analytics Features a companion website and public datasets that are used in the book
Présentation de l'éditeur
How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addition to the mechanics of BigQuery, the book also covers the architecture of the underlying Dremel query engine, providing a thorough understanding that leads to better query results. Features a companion website that includes all code and data sets from the book Uses real-world examples to explain everything analysts need to know to effectively use BigQuery Includes web application examples coded in Python
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
