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Data Strategy






By Sid Adelman, Larissa T. Moss, Majid Abai
...............................................
Publisher: Prentice Hall PTR
Pub Date: June 15, 2005
ISBN: 0-321-24099-5
Pages: 384



Table of Contents | Index


The definitive best-practices guide to enterprise data-management strategy.You can no longer manage enterprise data "piecemeal." To maximize the business value of your data assets, you must define a coherent, enterprise-wide data strategy that reflects all the ways you capture, store, manage, and use information.In this book, three renowned data management experts walk you through creating the optimal data strategy for your organization. Using their proven techniques, you can reduce hardware and maintenance costs, and rein in out-of-control data spending. You can build new systems with less risk, higher quality, and improve data access. Best of all, you can learn how to integrate new applications that support your key business objectives.Drawing on real enterprise case studies and proven best practices, the author team covers everything from goal-setting through managing security and performance. You'll learn how to: Identify the real risks and bottlenecks you face in delivering data—and the right solutions Integrate enterprise data and improve its quality, so it can be used more widely and effectively Systematically secure enterprise data and protect customer privacy Model data more effectively and take full advantage of metadata Choose the DBMS and data storage products that fit best into your overall plan Smoothly accommodate new Business Intelligence (BI) and unstructured data applications Improve the performance of your enterprise database applications Revamp your organization to streamline day-to-day data management and reduce cost Data Strategy is indispensable for everyone who needs to manage enterprise data more efficiently—from database architects to DBAs, technical staff to senior IT decision-makers. © Copyright Pearson Education. All rights reserved.

Table of Contents | Index

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Copyright
Acknowledgments
About the Authors
Foreword
Chapter 1. Introduction
Current Status in Contemporary Organizations
Why a Data strategy Is Needed
Vision and Goals of the Enterprise
Components of a Data Strategy
How Will You Develop and Implement a Data Strategy?
References
Chapter 2. Data Integration
Ineffective "Silver-Bullet" Technology Solutions
Gaining Management Support
Integrating Business Data
Deciding What Data Should Be Integrated
Consolidation and Federation
Getting Started
Conclusion
References
Chapter 3. Data Quality
Current State of Data Quality
Recognizing Dirty Data
Data Quality Rules
Data Quality Improvement Practices
Enterprise-Wide Data Quality Disciplines
Enterprise Architecture
Business Sponsorship
Conclusion
References
Chapter 4. Metadata
Why Metadata Is Critical to the Business
Metadata Categories
Metadata Sources
Metadata Repository
Developing a Metadata Repository
Managed Metadata Environment
Conclusion
References
Chapter 5. Data Modeling
Origins of Data Modeling
Significance of Data Modeling
Logical Data Modeling Concepts
Enterprise Logical Data Model
Physical Data Modeling Concepts
Physical Data Modeling Techniques
Dimensionality
Factors that Influence the Physical Data Model
Conclusion
References
Chapter 6. Organizational Roles and Responsibilities
Building the Teams Who Create and Maintain the Strategy
Resistance to Change
Optimal Organizational Structures
Training
Roles and Responsibilities
Data Ownership
Information Stewardship
Worst Practices
Agenda for Weekly Data Strategy Team Meeting
Conclusion
Chapter 7. Performance
Performance Requirements
Service Level Agreements
Capacity Planning: Performance Modeling
Capacity Planning: Benchmarks
Application Packages: Enterprise Resource Planning (ERPs)
Designing, Coding, and Implementing
Setting User Expectations
Monitoring (Measurement)
Tuning
Case Studies
Performance Tasks
Conclusion
References
Chapter 8. Security and Privacy of Data
Data Identification for Security and Privacy
Roles and Responsibilities
Regulatory Compliance
Auditing Procedures
Design Solutions
Impact of the Data Warehouse
Vendor Issues
Communicating and Selling Security
Best Practices and Worst Practices
Identify Your Own Sensitive Data Exercise
Conclusion
Chapter 9. DBMS Selection
Existing Environment
DBMS Choices
Why Standardize the DBMS?
Total Cost of Ownership
Application Packages and ERPs
Criteria for Selection
Selection Process
Reference Checking
RFPs for DBMSs
Response Format
Evaluating Vendors
Dealing with the Vendor
Exercise—How Well Are You Using Your DBMS?
Conclusion
References
Chapter 10. Business Intelligence
What Is Business Intelligence?
BI Components
Imprtant BI Tools and Processes
Emerging Trends and Technologies
BI Myths and Pitfalls
Conclusion
References
Chapter 11. Strategies for Managing Unstructured Data
What Is Unstructured Data?
A Unified Content Strategy for the Organization
Emerging Technologies
Conclusion
References
Chapter 12. Business Value of Data and ROI
The Business Value of Data
Align Data with Strategic Goals
The Cost of Developing a Data Strategy
Benefits of a Data Strategy
Conclusion
Reference
Appendix A. ROI Calculation Process, Cost Template, and Intangible Benefits Template
Cost of Capital
Risk
ROI Example
Cost Calculation Template
Intangible Benefits Calculation Template
Reference
Appendix B. Resources
Publications
Websites
Index

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