Big Data For Dummies - Hurwitz, Judith S

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Auteur(s) : Hurwitz, Judith S - Nugent, Alan - Halper, Fern - Kaufman, Marcia

Editeur : John Wiley & Sons

Langue : Anglais

Parution : 01/04/2013

Format : Moyen, de 350g à 1kg

Nombre de pages : 336

Expédition : 633

Dimensions : 23.5 x 19.1 x 1.9

ISBN : 1118504224

Résumé :

Find the right big data solution for your business or organization

Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work.

• Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals
• Authors are experts in information management, big data, and a variety of solutions
• Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more
• Provides essential information in a no-nonsense, easy-to-understand style that is empowering

Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.

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Biographie:

Judith Hurwitz is an expert in cloud computing, information management, and business strategy.

Alan Nugent has extensive experience in cloud-based big data solutions.

Dr. Fern Halper specializes in big data and analytics.

Marcia Kaufman specializes in cloud infrastructure, information management, and analytics.

Sommaire:

Introduction 1

About This Book 2

Foolish Assumptions 2

How This Book Is Organized 3

Part I: Getting Started with Big Data 3

Part II: Technology Foundations for Big Data 3

Part III: Big Data Management 3

Part IV: Analytics and Big Data 4

Part V: Big Data Implementation 4

Part VI: Big Data Solutions in the Real World 4

Part VII: The Part of Tens 4

Glossary 4

Icons Used in This Book 5

Where to Go from Here 5

Part I: Getting Started with Big Data 7

Chapter 1: Grasping the Fundamentals of Big Data 9

The Evolution of Data Management 10

Understanding the Waves of Managing Data 11

Wave 1: Creating manageable data structures 11

Wave 2: Web and content management 13

Wave 3: Managing big data 14

Defining Big Data 15

Building a Successful Big Data Management Architecture 16

Beginning with capture, organize, integrate, analyze, and act 16

Setting the architectural foundation 17

Performance matters 20

Traditional and advanced analytics 22

The Big Data Journey 23

Chapter 2: Examining Big Data Types 25

Defining Structured Data 26

Exploring sources of big structured data 26

Understanding the role of relational databases in big data 27

Defining Unstructured Data 29

Exploring sources of unstructured data 29

Understanding the role of a CMS in big data management 31

Looking at Real-Time and Non-Real-Time Requirements 32

Putting Big Data Together 33

Managing different data types 33

Integrating data types into a big data environment 34

Chapter 3: Old Meets New: Distributed Computing 37

A Brief History of Distributed Computing 37

Giving thanks to DARPA 38

The value of a consistent model 39

Understanding the Basics of Distributed Computing 40

Why we need distributed computing for big data 40

The changing economics of computing 40

The problem with latency 41

Demand meets solutions 41

Getting Performance Right 42

Part II: Technology Foundations for Big Data 45

Chapter 4: Digging into Big Data Technology Components 47

Exploring the Big Data Stack 48

Layer 0: Redundant Physical Infrastructure 49

Physical redundant networks 51

Managing hardware: Storage and servers 51

Infrastructure operations 51

Layer 1: Security Infrastructure 52

Interfaces and Feeds to and from Applications and the Internet 53

Layer 2: Operational Databases 54

Layer 3: Organizing Data Services and Tools 56

Layer 4: Analytical Data Warehouses 56

Big Data Analytics 58

Big Data Applications 58

Chapter 5: Virtualization and How It Supports Distributed Computing 61

Understanding the Basics of Virtualization 61

The importance of virtualization to big data 63

Server virtualization 64

Application virtualization 65

Network virtualization 66

Processor and memory virtualization 66

Data and storage virtualization 67

Managing Virtualization with the Hypervisor 68

Abstraction and Virtualization 69

Implementing Virtualization to Work with Big Data 69

Chapter 6: Examining the Cloud and Big Data 71

Defining the Cloud in the Context of Big Data 71

Understanding Cloud Deployment and Delivery Models 72

Cloud deployment models 73

Cloud delivery models 74

The Cloud as an Imperative for Big Data 75

Making Use of the Cloud for Big Data 77

Providers in the Big Data Cloud Market 78

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