Data Virtualization for Business Intelligence Systems Revolutionizing Data Integration for Data Warehouses

ISBN-10: 0123944252

ISBN-13: 9780123944252

Edition: 2012

Buy it from $62.75
eBook available
This item qualifies for FREE shipping

*A minimum purchase of $35 is required. Shipping is provided via FedEx SmartPost® and FedEx Express Saver®. Average delivery time is 1 – 5 business days, but is not guaranteed in that timeframe. Also allow 1 - 2 days for processing. Free shipping is eligible only in the continental United States and excludes Hawaii, Alaska and Puerto Rico. FedEx service marks used by permission."Marketplace" orders are not eligible for free or discounted shipping.

30 day, 100% satisfaction guarantee

If an item you ordered from TextbookRush does not meet your expectations due to an error on our part, simply fill out a return request and then return it by mail within 30 days of ordering it for a full refund of item cost.

Learn more about our returns policy

Description: Data virtualization can help you accomplish your goals with more flexibility and agility. Learn what it is and how and why it should be used with Data Virtualization for Business Intelligence Systems. In this book, expert author Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. You'll learn the difference is between this new form of data integration and older forms, such as ETL and replication, and gain a clear understanding of how data virtualization really works. Data Virtualization for Business Intelligence Systems outlines the advantages and disadvantages of data virtualization and illustrates how data virtualization should be applied in data warehouse environments. You'll come away with a comprehensive understanding of how data virtualization will make data warehouse environments more flexible and how it make developing operational BI applications easier. Van der Lans also describes the relationship between data virtualization and related topics, such as master data management, governance, and information management, so you come away with a big-picture understanding as well as all the practical know-how you need to virtualize your data.First independent book on data virtualization that explains in a product-independent way how data virtualization technology works.Illustrates concepts using examples developed with commercially available products.Shows you how to solve common data integration challenges such as data quality, system interference, and overall performance by following practical guidelines on using data virtualization.Apply data virtualization right away with three chapters full of practical implementation guidance.Understand the big picture of data virtualization and its relationship with data governance and information management.

New Starting from $69.60
eBooks Starting from $59.95
Buy eBooks
what's this?
Rush Rewards U
Members Receive:
coins
coins
You have reached 400 XP and carrot coins. That is the daily max!

Study Briefs

Limited time offer: Get the first one free! (?)

All the information you need in one place! Each Study Brief is a summary of one specific subject; facts, figures, and explanations to help you learn faster.

Add to cart
Study Briefs
Periodic Table Online content $4.95 $1.99
Add to cart
Study Briefs
SQL Online content $4.95 $1.99
Add to cart
Study Briefs
MS Excel® 2010 Online content $4.95 $1.99
Add to cart
Study Briefs
MS Word® 2010 Online content $4.95 $1.99

Customers also bought

Loading
Loading
Loading
Loading
Loading
Loading
Loading
Loading
Loading
Loading

Book details

Copyright year: 2012
Publisher: Elsevier Science & Technology Books
Publication date: 7/25/2012
Binding: Paperback
Pages: 296
Size: 7.50" wide x 9.25" long x 0.75" tall
Weight: 1.386
Language: English

Foreword
Preface
About the Author
Introduction to Data Virtualization
Introduction
The World of Business Intelligence Is Changing
Introduction to Virtualization
What Is Data Virtualization?
Data Virtualization and Related Concepts
Data Virtualization versus Encapsulation and Information Hiding
Data Virtualization versus Abstraction
Data Virtualization versus Data Federation
Data Virtualization versus Data Integration
Data Virtualization versus Enterprise Information Integration
Definition of Data Virtualization
Technical Advantages of Data Virtualization
Different Implementations of Data Virtualization
Overview of Data Virtualization Servers
Open versus Closed Data Virtualization Servers
Other Forms of Data Integration
The Modules of a Data Virtualization Server
The History of Data Virtualization
The Sample Database: World Class Movies
Structure of This Book
Business Intelligence and Data Warehousing
Introduction
What Is Business Intelligence?
Management Levels and Decision Making
Business Intelligence Systems
The Data Stores of a Business Intelligence System
The Data Warehouse
The Data Marts
The Data Staging Area
The Operational Data Store
The Personal Data Stores
A Comparison of the Different Types of Data Stores
Normalized Schemas, Star Schemas, and Snowflake Schemas
Normalized Schemas
Denormalized Schemas
Star Schemas
Snowflake Schemas
Data Transformation with Extract Transform Load, Extract Load Transform, and Replication
Extract Transform Load
Extract Load Transform
Replication
Overview of Business Intelligence Architectures
New Forms of Reporting and Analytics
Operational Reporting and Analytics
Deep and Big Data Analytics
Self-Service Reporting and Analytics
Unrestricted Ad-Hoc Analysis
360-Degree Reporting
Exploratory Analysis
Text-Based Analysis
Disadvantages of Classic Business Intelligence Systems
Summary
Data Virtualization Server: The Building Blocks
Introduction
The High-Level Architecture of a Data Virtualization Server
Importing Source Tables and Defining Wrappers
Defining Virtual Tables and Mappings
Examples of Virtual Tables and Mappings
Virtual Tables and Data Modeling
Nesting Virtual Tables and Shared Specifications
Importing Nonrelational Data
XML and JSON Documents
Web Services
Spreadsheets
NoSQL Databases
Multidimensional Cubes and MDX
Semistructured Data
Unstructured Data
Publishing Virtual Tables
The Internal Data Model
Updatable Virtual Tables and Transaction Management
Data Virtualization Server: Management and Security
Introduction
Impact and Lineage Analysis
Synchronization of Source Tables, Wrapper Tables, and Virtual Tables
Security of Data: Authentication and Authorization
Monitoring, Management, and Administration
Data Virtualization Server: Caching of Virtual Tables
Introduction
The Cache of a Virtual Table
When to Use Caching
Caches versus Data Marts
Where Is the Cache Kept?
Refreshing Caches
Full Refreshing, Incremental Refreshing, and Live Refreshing
Online Refreshing and Offline Refreshing
Cache Replication
Data Virtualization Server: Query Optimization Techniques
Introduction
A Refresher Course on Query Optimization
The Ten Stages of Query Processing by a Data Virtualization Server
The Intelligence Level of the Data Stores
Optimization through Query Substitution
Optimization through Pushdown
Optimization through Query Expansion (Query Injection)
Optimization through Ship Joins
Optimization through Sort-Merge Joins
Optimization by Caching
Optimization and Statistical Data
Optimization through Hints
Optimization through SQL Override
Explaining the Processing Strategy
Deploying Data Virtualization in Business Intelligence Systems
Introduction
A Business Intelligence System Based on Data Virtualization
Advantages of Deploying Data Virtualization
Disadvantages of Deploying Data Virtualization
Strategies for Adopting Data Virtualization
Strategy 1: Introducing Data Virtualization in an Existing Business Intelligence System
Strategy 2: Developing a New Business Intelligence System with Data Virtualization
Strategy 3: Developing a New Business Intelligence System Combining Source and Transformed Data
Application Areas of Data Virtualization
Unified Data Access
Virtual Data Mart
Virtual Data Warehouse-Based on Data Marts
Virtual Data Warehouse-Based on Production Databases
Extended Data Warehouse
Operational Reporting and Analytics
Operational Data Warehouse
Virtual Corporate Data Warehouse
Self-Service Reporting and Analytics
Virtual Sandbox
Prototyping
Analyzing Semistructured and Unstructured Data
Disposable Reports
Extending Business Intelligence Systems with External Users
Myths on Data Virtualization
Design Guidelines for Data Virtualization
Introduction
Incorrect Data and Data Quality
Different Forms of Incorrect Data
Integrity Rules and Incorrect Data
Filtering, Flagging, and Restoring Incorrect Data
Examples of Filtering Incorrect Data
Examples of Flagging Incorrect Data
Examples of Restoring Misspelled Data
Complex and Irregular Data Structures
Codes without Names
Inconsistent Key Values
Repeating Groups
Recursive Data Structures
Implementing Transformations in Wrappers or Mappings
Analyzing Incorrect Data
Different Users and Different Definitions
Time Inconsistency of Data
Data Stores and Data Transmission
Retrieving Data from Production Systems
Joining Historical and Operational Data
Dealing with Organizational Changes
Archiving Data
Data Virtualization and Service-Oriented Architecture
Introduction
Service-Oriented Architectures in a Nutshell
Basic Services, Composite Services, Business Process Services, and Data Services
Developing Data Services with a Data Virtualization Server
Developing Composite Services with a Data Virtualization Server
Services and the Internal Data Model
Data Virtualization and Master Data Management
Introduction
Data Is a Critical Asset for Every Organization
The Need for a 360-Degree View of Business Objects
What Is Master Data?
What Is Master Data Management?
A Master Data Management System
Master Data Management for Integrating Data
Integrating Master Data Management and Data Virtualization
Data Virtualization, Information Management, and Data Governance
Introduction
Impact of Data Virtualization on Information Modeling and Database Design
Impact of Data Virtualization on Data Profiling
Impact of Data Virtualization on Data Cleansing
Impact of Data Virtualization on Data Governance
The Data Delivery Platform-A New Architecture for Business Intelligence Systems
Introduction
The Data Delivery Platform in a Nutshell
The Definition of the Data Delivery Platform
The Data Delivery Platform and Other Business Intelligence Architectures
The Requirements of the Data Delivery Platform
The Data Delivery Platform versus Data Virtualization
Explanation of the Name
A Personal Note
The Future of Data Virtualization
Introduction
The Future of Data Virtualization According to Rick F. van der Lans
New and Enhanced Query Optimization Techniques
Exploiting New Hardware Technology
Extending the Design Module
Data Quality Features
Support for the Push-Model for Data Access
Blending of Data Virtualization, Extract Transform Load, Extract Load Transform, and Replication
The Future of Data Virtualization According to David Besemer, CTO of Composite Software
The Empowered Consumer Gains Ubiquitous Data Access
IT's Back Office Becomes the Cloud
Data Virtualization of the Future Is a Global Data Fabric
Conclusion
The Future of Data Virtualization According to Alberto Pan, CTO of Denodo Technologies
The Future of Data Virtualization According to James Markarian, CTO of Informatica Corporation
How to Maximize Return on Data with Data Virtualization
Beyond Looking Under the Hood
Bibliography
Index
×
Free shipping on orders over $35*

*A minimum purchase of $35 is required. Shipping is provided via FedEx SmartPost® and FedEx Express Saver®. Average delivery time is 1 – 5 business days, but is not guaranteed in that timeframe. Also allow 1 - 2 days for processing. Free shipping is eligible only in the continental United States and excludes Hawaii, Alaska and Puerto Rico. FedEx service marks used by permission."Marketplace" orders are not eligible for free or discounted shipping.

Learn more about the TextbookRush Marketplace.

×