Google BigQuery Analytics

✍ Scribed by Naidu, Siddartha; Tigani, Jordan

• Publisher: John Wiley & Sons, Inc
• Year: 2014
• Tongue: English
• Leaves: 530
• Edition: 1
• Category: Library

✦ 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

✦ Table of Contents

Content: Part I: BigQuery Fundamentals
In This Part
Chapter 1: The Story of Big Data at Google
Big Data Stack 1.0
Big Data Stack 2.0 (and Beyond)
Open Source Stack
Google Cloud Platform
Problem Statement
Summary
Chapter 2: BigQuery Fundamentals
What Is BigQuery?
BigQuery Sensors Application
Summary
Chapter 3: Getting Started with BigQuery
Creating a Project
Running Your First Query
Using the Command-Line Client
Setting Up Google Cloud Storage
Development Environment
Summary
Chapter 4: Understanding the BigQuery Object Model
Projects
BigQuery Data
Jobs BigQuery Billing and QuotasData Model for End-to-End Application
Summary
Part II: Basic BigQuery
In This Part
Chapter 5: Talking to the BigQuery API
Introduction to Google APIs
BigQuery REST Collections
Summary
Chapter 6: Loading Data
Bulk Loads
Streaming Inserts
Summary
Chapter 7: Running Queries
BigQuery Query API
BigQuery Query Language
Summary
Chapter 8: Putting It Together
A Quick Tour
Mobile Client
Log Collection Service
Dashboard
Summary
Part III: Advanced BigQuery
In This Part
Chapter 9: Understanding Query Execution
Background
Storage Architecture Query ProcessingArchitecture Comparisons
Summary
Chapter 10: Advanced Queries
Advanced SQL
BigQuery SQL Extensions
Query Errors
Recipes
Summary
Chapter 11: Managing Data Stored in BigQuery
Query Caching
Result Caching
Table Snapshots
AppEngine Datastore Integration
Metatables and Table Sharding
Summary
Part IV: BigQuery Applications
In This Part
Chapter 12: External Data Processing
Getting Data Out of BigQuery
AppEngine MapReduce
Querying BigQuery from a Spreadsheet
Summary
Chapter 13: Using BigQuery from Third-Party Tools
BigQuery Adapters Scientific Data Processing Tools in BigQueryVisualizing Data in BigQuery
Summary
Chapter 14: Querying Google Data Sources
Google Analytics
Google AdSense
Google Cloud Storage
Summary
Introduction
Overview of the Book and Technology
How This Book Is Organized
How to Read This Book
Tools You Need
Supplemental Materials and Information
End User License Agreement

✦ Subjects

Google Analytics.;Google BigQuery.;Web usage mining.;COMPUTERS;General.