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Index
Cover
Table of Contents
Part I: What Is Big Data?
Chapter 1: Industry Needs and Solutions
What's So Big About Big Data?
A Brief History of Hadoop
What Is Hadoop?
Summary
Chapter 2: Microsoft's Approach to Big Data
A Story of “Better Together”
Competition in the Ecosystem
Deploying Hadoop
Summary
Part II: Setting Up for Big Data with Microsoft
Chapter 3: Configuring Your First Big Data Environment
Getting Started
Getting the Install
Running the Installation
Validating Your New Cluster
Common Post-setup Tasks
Summary
Part III: Storing and Managing Big Data
Chapter 4: HDFS, Hive, HBase, and HCatalog
Exploring the Hadoop Distributed File System
Exploring Hive: The Hadoop Data Warehouse Platform
Exploring HCatalog: HDFS Table and Metadata Management
Exploring HBase: An HDFS Column-oriented Database
Summary
Chapter 5: Storing and Managing Data in HDFS
Understanding the Fundamentals of HDFS
Using Common Commands to Interact with HDFS
Moving and Organizing Data in HDFS
Summary
Chapter 6: Adding Structure with Hive
Understanding Hive's Purpose and Role
Creating and Querying Basic Tables
Using Advanced Data Structures with Hive
Summary
Chapter 7: Expanding Your Capability with HBase and HCatalog
Using HBase
Managing Data with HCatalog
Creating Partitions
Integrating HCatalog with Pig and Hive
Using HBase or Hive as a Data Warehouse
Summary
Part IV: Working with Your Big Data
Chapter 8: Effective Big Data ETL with SSIS, Pig, and Sqoop
Combining Big Data and SQL Server Tools for Better Solutions
Working with SSIS and Hive
Configuring Your Packages
Transferring Data with Sqoop
Using Pig for Data Movement
Choosing the Right Tool
Summary
Chapter 9: Data Research and Advanced Data Cleansing with Pig and Hive
Getting to Know Pig
Using Hive
Summary
Part V: Big Data and SQL Server Together
Chapter 10: Data Warehouses and Hadoop Integration
State of the Union
Challenges Faced by Traditional Data Warehouse Architectures
Hadoop's Impact on the Data Warehouse Market
Introducing Parallel Data Warehouse (PDW)
Project Polybase
Summary
Chapter 11: Visualizing Big Data with Microsoft BI
An Ecosystem of Tools
Self-service Big Data with PowerPivot
Rapid Big Data Exploration with Power View
Spatial Exploration with Power Map
Summary
Chapter 12: Big Data Analytics
Data Science, Data Mining, and Predictive Analytics
Introduction to Mahout
Building a Recommendation Engine
Summary
Chapter 13: Big Data and the Cloud
Defining the Cloud
Exploring Big Data Cloud Providers
Setting Up a Big Data Sandbox in the Cloud
Storing Your Data in the Cloud
Summary
Chapter 14: Big Data in the Real World
Common Industry Analytics
Operational Analytics
Summary
Part VI: Moving Your Big Data Forward
Chapter 15: Building and Executing Your Big Data Plan
Gaining Sponsor and Stakeholder Buy-in
Identifying Technical Challenges
Identifying Operational Challenges
Going Forward
Summary
Chapter 16: Operational Big Data Management
Ongoing Data Integration with Cloud and On-premise Solutions
Integration Thoughts for Big Data
Backups and High Availability in Your Big Data Environment
Big Data Solution Governance
Creating Operational Analytics
Summary
Introduction
Our Team
All Kidding Aside
Who Is This Book For?
What You Need to Use This Book
Chapter Overview
Features Used in This Book
End User License Agreement
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