Learning Google Bigquery
Download Learning Google Bigquery PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Learning Google Bigquery book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Google BigQuery: The Definitive Guide
Author: Valliappa Lakshmanan
language: en
Publisher: O'Reilly Media
Release Date: 2019-10-23
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.
Learning Google BigQuery
Get a fundamental understanding of how Google BigQuery works by analyzing and querying large datasets Key Features Get started with BigQuery API and write custom applications using it Learn how BigQuery API can be used for storing, managing, and query massive datasets with ease A practical guide with examples and use-cases to teach you everything you need to know about Google BigQuery Book Description Google BigQuery is a popular cloud data warehouse for large-scale data analytics. This book will serve as a comprehensive guide to mastering BigQuery, and how you can utilize it to quickly and efficiently get useful insights from your Big Data. You will begin with getting a quick overview of the Google Cloud Platform and the various services it supports. Then, you will be introduced to the Google BigQuery API and how it fits within in the framework of GCP. The book covers useful techniques to migrate your existing data from your enterprise to Google BigQuery, as well as readying and optimizing it for analysis. You will perform basic as well as advanced data querying using BigQuery, and connect the results to various third party tools for reporting and visualization purposes such as R and Tableau. If you're looking to implement real-time reporting of your streaming data running in your enterprise, this book will also help you. This book also provides tips, best practices and mistakes to avoid while working with Google BigQuery and services that interact with it. By the time you're done with it, you will have set a solid foundation in working with BigQuery to solve even the trickiest of data problems. What you will learn Get a hands-on introduction to Google Cloud Platform and its services Understand the different data types supported by Google BigQuery Migrate your enterprise data to BigQuery and query it using the legacy and standard SQL techniques Use partition tables in your project and query external data sources and wild card tables Create tables and data sets dynamically using the BigQuery API Perform real-time inserting of records for analytics using Python and C# Visualize your BigQuery data by connecting it to third party tools such as Tableau and R Master the Google Cloud Pub/Sub for implementing real-time reporting and analytics of your Big Data Who this book is for If you are a developer, data analyst, or a data scientist looking to run complex queries over thousands of records in seconds, this book will help you. No prior experience of working with BigQuery is assumed.
Learn Google Bigquery
Author: Diego Rodrigues
language: en
Publisher: Independently Published
Release Date: 2025-10-06
LEARN GOOGLE BIGQUERY Master Serverless Data Warehouse and Production-Scale Analytics This book is intended for data students and professionals seeking to master large-scale data analysis, integration, and automation using Google BigQuery in the most demanding market scenarios. Structured for immediate application, the content covers everything from cloud environment setup, efficient data ingestion, partitioned table modeling, and clustering to advanced SQL for analytical processing, integration with Dataflow, Data Studio, Looker, and automation of BI and machine learning workflows. You will execute: - Provisioning Google Cloud projects and datasets - Ingesting, partitioning, and clustering large volumes - Analytical modeling with SQL optimized for BigQuery - Integrating with Dataflow, Data Studio, and Looker pipelines - Automating ETL routines and data governance - Orchestrating jobs, monitoring, and performance tuning - Applying native machine learning and integrating external APIs By the end, you will be able to implement professional solutions for data analysis, BI, automation, and machine learning, aligned with the needs of modern organizations and scalable projects. bigquery, google cloud, data analysis, advanced sql, bi, dataflow, etl, clustering, machine learning, governance