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Information Management

Book Description

Information Management: Gaining a Competitive Advantage with Data is about making smart decisions to make the most of company information. Expert author William McKnight develops the value proposition for information in the enterprise and succinctly outlines the numerous forms of data storage. Information Management will enlighten you, challenge your preconceived notions, and help activate information in the enterprise. Get the big picture on managing data so that your team can make smart decisions by understanding how everything from workload allocation to data stores fits together.

The practical, hands-on guidance in this book includes:

  • Part 1: The importance of information management and analytics to business, and how data warehouses are used
  • Part 2: The technologies and data that advance an organization, and extend data warehouses and related functionality
  • Part 3: Big Data and NoSQL, and how technologies like Hadoop enable management of new forms of data
  • Part 4: Pulls it all together, while addressing topics of agile development, modern business intelligence, and organizational change management

Read the book cover-to-cover, or keep it within reach for a quick and useful resource. Either way, this book will enable you to master all of the possibilities for data or the broadest view across the enterprise.

  • Balances business and technology, with non-product-specific technical detail
  • Shows how to leverage data to deliver ROI for a business
  • Engaging and approachable, with practical advice on the pros and cons of each domain, so that you learn how information fits together into a complete architecture
  • Provides a path for the data warehouse professional into the new normal of heterogeneity, including NoSQL solutions

Table of Contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Foreword
  6. In praise of Information Management
  7. Preface
  8. Chapter One. You’re in the Business of Information
    1. An Architecture for Information Success
    2. The Glue is Architecture
    3. Workload Success
    4. Information in Action
    5. Judgment Still Necessary
  9. Chapter Two. Relational Theory In Practice
    1. Relational Theory
    2. Multidimensional Databases
    3. RDBMS Platforms
    4. Action Plan
  10. Chapter Three. You’re in the Business of Analytics
    1. What Distinguishes Analytics?
    2. Predictive Analytics
    3. Building Predictive Analytic Models
    4. Analytics and Information Architecture
    5. Analytics Requires Analysts
    6. Action Plan
  11. Chapter Four. Data Quality: Passing the Standard
    1. Data Quality Defect Categories
    2. Sources of Poor Data Quality
    3. Cures for Poor Data Quality
    4. Action Plan
  12. Chapter Five. Columnar Databases
    1. Columnar Operation
    2. Compression
    3. Workloads
    4. Workload Examples
    5. Columnar Conclusions
    6. Action Plan
  13. Chapter Six. Data Warehouses and Appliances
    1. Data Warehousing
    2. The Data Warehouse Appliance
    3. Data Appliances and the Use of Memory
    4. Action Plan
  14. Chapter Seven. Master Data Management: One Chapter Here, but Ramifications Everywhere
    1. MDM Justification
    2. A Subject-Area Culture
    3. Mastering Data
    4. The Architecture of MDM
    5. MDM Governance
    6. Data Quality and MDM
    7. MDM Roles and Responsibilities
    8. MDM Technology
    9. Action Items
  15. Chapter Eight. Data Stream Processing: When Storing the Data Happens Later
    1. Uses of Data Stream Processing
    2. Data Stream Processing Brings Power
    3. Stream SQL Extensions
    4. In Conclusion
    5. Action Plan
    6. References
  16. Chapter Nine. Data Virtualization: The Perpetual Short-Term Solution
    1. The History of Data Virtualization
    2. Controlling Your Information Asset
    3. Action Plan
    4. Reference
  17. Chapter Ten. Operational Big Data: Key-Value, Document, and Column Stores: Hash Tables Reborn
    1. When to Yes NoSQL
    2. NoSQL Attributes
    3. NoSQL Categorization
    4. Key-Value Stores
    5. Document Stores
    6. Column Stores
    7. NoSQL Solution Checklist
    8. Action Plan
  18. Chapter Eleven. Analytical Big Data: Hadoop: Analytics at Scale
    1. Big Data for Hadoop
    2. Hadoop Defined
    3. Hadoop Distributed File System
    4. MapReduce for Hadoop
    5. Failover
    6. Hadoop Distributions
    7. Supporting Tools
    8. Hadoop Challenges
    9. Hadoop is Not
    10. Summary
    11. Action Plan
  19. Chapter Twelve. Graph Databases: When Relationships are the Data
    1. Terms
    2. Structure
    3. Centrality Analysis
    4. Cypher, a Graph Database Language
    5. Graph Database Models
    6. Action Plan
  20. Chapter Thirteen. Cloud Computing: On-Demand Elasticity
    1. Defining Cloud Computing
    2. Benefits of the Cloud
    3. Challenges with the Cloud
    4. Cloud Deployment Models
    5. Information Management in the Cloud
    6. Action Plan
  21. Chapter Fourteen. An Elegant Architecture Where Information Flows
    1. The Starting Point
    2. Plenty of Work to be Done
    3. Information Management Maturity
    4. Leadership
    5. Action Plan
  22. Chapter Fifteen. Modern Business Intelligence—Collaboration, Mobile, and Self-Service: Organizing the Discussion and Tethering the User to Information
    1. The Mobile Revolution
    2. Mobile Business Intelligence
    3. Self-Service Business Intelligence
    4. Collaborative Business Intelligence
    5. Action Plan
  23. Chapter Sixteen. Agile Practices for Information Management
    1. Traditional Waterfall Methodology
    2. Agile Approaches
    3. SCRUM
    4. SCRUM and Methodology Themes
    5. Action Plan
  24. Chapter Seventeen. Organizational Change Management: The Soft Stuff is the Hard Stuff
    1. Organizational Change Management Work Products
    2. Organization Change Management is Essential to Project Success
    3. Action Plan
  25. Index