Paulraj Ponniah
Data Warehousing Fundamentals for It Professionals
Paulraj Ponniah
Data Warehousing Fundamentals for It Professionals
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Since the first edition of Data Warehousing Fundamentals, there has been an increase in enterprises either already having or in the process of obtaining the data warehousing programs. Data Warehousing Fundamentals not only explores important topics, like planning requirements, architecture, infrastructure, data preparation, and information delivery, but also the most up-to-date research on areas of technological improvements since the first edition. Additionally, Information Technologists will find expert advice, review questions, exercises, as well as an answer section are all included in this revised text.…mehr
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Since the first edition of Data Warehousing Fundamentals, there has been an increase in enterprises either already having or in the process of obtaining the data warehousing programs. Data Warehousing Fundamentals not only explores important topics, like planning requirements, architecture, infrastructure, data preparation, and information delivery, but also the most up-to-date research on areas of technological improvements since the first edition. Additionally, Information Technologists will find expert advice, review questions, exercises, as well as an answer section are all included in this revised text.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Fundamentals for IT Professionals
- Verlag: Wiley & Sons
- Artikelnr. des Verlages: 14546207000
- 2. Aufl.
- Seitenzahl: 608
- Erscheinungstermin: 24. Mai 2010
- Englisch
- Abmessung: 260mm x 183mm x 36mm
- Gewicht: 1160g
- ISBN-13: 9780470462072
- ISBN-10: 0470462078
- Artikelnr.: 28164960
- Fundamentals for IT Professionals
- Verlag: Wiley & Sons
- Artikelnr. des Verlages: 14546207000
- 2. Aufl.
- Seitenzahl: 608
- Erscheinungstermin: 24. Mai 2010
- Englisch
- Abmessung: 260mm x 183mm x 36mm
- Gewicht: 1160g
- ISBN-13: 9780470462072
- ISBN-10: 0470462078
- Artikelnr.: 28164960
PAULRAJ PONNIAH, PHD, with over thirty years of experience as an IT consultant, has worked with such organizations as Texaco, Sotheby's, Blue Cross/Blue Shield, NA Philips, New York-Presbyterian Hospital, Panasonic, and Bantam Doubleday Dell. He specializes in the design and implementation of data warehouse and database systems. Dr. Ponniah has published three successful books and, as Adjunct Professor, continues to teach college courses in data warehousing and database design.
Preface. Part 1 OVERVIEW AND CONCEPTS. 1 The Compelling Need for Data
Warehousing. Chapter Objectives. Escalating Need for Strategic Information.
Failures of Past Decision Support Systems. Operational Versus
Decision-Support Systems. Data Warehousing--The Only Viable Solution. Data
Warehouse Defined. The Data Warehousing Movement. Evolution of Business
Intelligence. Chapter Summary. Review Questions. Exercises. 2 Data
Warehouse: The Building Blocks. Chapter Objectives. Defining Features. Data
Warehouses and Data Marts. Architectural Types. Overview of Components.
Metadata in the Data Warehouse. Chapter Summary. Review Questions.
Exercises. 3 Trends in Data Warehousing. Chapter Objectives. Continued
Growth in Data Warehousing. Vendor Solutions and Products. Significant
Trends. Emergence of Standards. Web-Enabled Data Warehouse. Chapter
Summary. Review Questions. Exercises. Part 2 PLANNING AND REQUIREMENTS. 4
Planning and Project Management. Chapter Objectives. Planning Your Data
Warehouse. The Data Warehouse Project. The Project Team. Project Management
Considerations. Chapter Summary. Review Questions. Exercises. 5 Defining
the Business Requirements. Chapter Objectives. Dimensional Analysis.
Information Packages--A Useful Concept. Requirements Gathering Methods.
Requirements Definition: Scope and Content. Chapter Summary. Review
Questions. Exercises. 6 Requirements as the Driving Force for Data
Warehousing. Chapter Objectives. Data Design. The Architectural Plan. Data
Storage Specifications. Information Delivery Strategy. Chapter Summary.
Review Questions. Exercises. Part 3 ARCHITECTURE AND INFRASTRUCTURE. 7 The
Architectural Components. Chapter Objectives. Understanding Data Warehouse
Architecture. Distinguishing Characteristics. Architectural Framework.
Technical Architecture. Architectural Types. Chapter Summary. Review
Questions. Exercises. 8 Infrastructure as the Foundation for Data
Warehousing. Chapter Objectives. Infrastructure Supporting Architecture.
Hardware and Operating Systems. Database Software. Collection of Tools.
Data Warehouse Appliances. Chapter Summary. Review Questions. Exercises. 9
The Significant Role of Metadata. Chapter Objectives. Why Metadata is
Important. Metadata Types by Functional Areas. Business Metadata. Technical
Metadata. How to Provide Metadata. Chapter Summary. Review Questions.
Exercises. Part 4 DATA DESIGN AND DATA PREPARATION. 10 Principles of
Dimensional Modeling. Chapter Objectives. From Requirements to Data Design.
The STAR Schema. STAR Schema Keys. Advantages of the STAR Schema. STAR
Schema: Examples. Chapter Summary. Review Questions. Exercises. 11
Dimensional Modeling: Advanced Topics. Chapter Objectives. Updates to the
Dimension Tables. Miscellaneous Dimensions. The Snowflake Schema. Aggregate
Fact Tables. Families of STARS. Chapter Summary. Review Questions.
Exercises. 12 Data Extraction, Transformation, and Loading. Chapter
Objectives. ETL Overview. Data Extraction. Data Transformation. Data
Loading. ETL Summary. Other Integration Approaches. Chapter Summary. Review
Questions. Exercises. 13 Data Quality: A Key to Success. Chapter
Objectives. Why is Data Quality Critical?. Data Quality Challenges. Data
Quality Tools. Data Quality Initiative. Master Data Management (MDM).
Chapter Summary. Review Questions. Exercises. Part 5 INFORMATION ACCESS AND
DELIVERY. 14 Matching Information to the Classes of Users. Chapter
Objectives. Information from the Data Warehouse. Who Will Use the
Information? Information Delivery. Information Delivery Tools. Information
Delivery: Special Topics. Chapter Summary. Review Questions. Exercises. 15
OLAP in the Data Warehouse. Chapter Objectives. Demand for Online
Analytical Processing. Major Features and Functions. OLAP Models. OLAP
Implementation Considerations. Chapter Summary. Review Questions.
Exercises. 16 Data Warehousing and the Web. Chapter Objectives. Web-Enabled
Data Warehouse. Web-Based Information Delivery. OLAP and the Web. Building
a Web-Enabled Data Warehouse. Chapter Summary. Review Questions. Exercises.
17 Data Mining Basics. Chapter Objectives. What is Data Mining?. Major Data
Mining Techniques. Data Mining Applications. Chapter Summary. Review
Questions. Exercises. Part 6 IMPLEMENTATION AND MAINTENANCE. 18 The
Physical Design Process. Chapter Objectives. Physical Design Steps.
Physical Design Considerations. Physical Storage. Indexing the Data
Warehouse. Performance Enhancement Techniques. Chapter Summary. Review
Questions. Exercises. 19 Data Warehouse Deployment. Chapter Objectives.
Data Warehouse Testing. Major Deployment Activities. Considerations for a
Pilot. Security. Backup and Recovery. Chapter Summary. Review Questions.
Exercises. 20 Growth and Maintenance. Chapter Objectives. Monitoring the
Data Warehouse. User Training and Support. Managing the Data Warehouse.
Chapter Summary. Review Questions. Exercises. Answers to Selected
Exercises. Appendix A. Project Life Cycle Steps and Checklists. Appendix B.
Critical Factors for Success. Appendix C. Guidelines for Evaluating Vendor
Solutions. Appendix D. Highlights of Vendors and Products. Appendix E.
Real-World Examples of Best Practices. References. Glossary. Index.
Warehousing. Chapter Objectives. Escalating Need for Strategic Information.
Failures of Past Decision Support Systems. Operational Versus
Decision-Support Systems. Data Warehousing--The Only Viable Solution. Data
Warehouse Defined. The Data Warehousing Movement. Evolution of Business
Intelligence. Chapter Summary. Review Questions. Exercises. 2 Data
Warehouse: The Building Blocks. Chapter Objectives. Defining Features. Data
Warehouses and Data Marts. Architectural Types. Overview of Components.
Metadata in the Data Warehouse. Chapter Summary. Review Questions.
Exercises. 3 Trends in Data Warehousing. Chapter Objectives. Continued
Growth in Data Warehousing. Vendor Solutions and Products. Significant
Trends. Emergence of Standards. Web-Enabled Data Warehouse. Chapter
Summary. Review Questions. Exercises. Part 2 PLANNING AND REQUIREMENTS. 4
Planning and Project Management. Chapter Objectives. Planning Your Data
Warehouse. The Data Warehouse Project. The Project Team. Project Management
Considerations. Chapter Summary. Review Questions. Exercises. 5 Defining
the Business Requirements. Chapter Objectives. Dimensional Analysis.
Information Packages--A Useful Concept. Requirements Gathering Methods.
Requirements Definition: Scope and Content. Chapter Summary. Review
Questions. Exercises. 6 Requirements as the Driving Force for Data
Warehousing. Chapter Objectives. Data Design. The Architectural Plan. Data
Storage Specifications. Information Delivery Strategy. Chapter Summary.
Review Questions. Exercises. Part 3 ARCHITECTURE AND INFRASTRUCTURE. 7 The
Architectural Components. Chapter Objectives. Understanding Data Warehouse
Architecture. Distinguishing Characteristics. Architectural Framework.
Technical Architecture. Architectural Types. Chapter Summary. Review
Questions. Exercises. 8 Infrastructure as the Foundation for Data
Warehousing. Chapter Objectives. Infrastructure Supporting Architecture.
Hardware and Operating Systems. Database Software. Collection of Tools.
Data Warehouse Appliances. Chapter Summary. Review Questions. Exercises. 9
The Significant Role of Metadata. Chapter Objectives. Why Metadata is
Important. Metadata Types by Functional Areas. Business Metadata. Technical
Metadata. How to Provide Metadata. Chapter Summary. Review Questions.
Exercises. Part 4 DATA DESIGN AND DATA PREPARATION. 10 Principles of
Dimensional Modeling. Chapter Objectives. From Requirements to Data Design.
The STAR Schema. STAR Schema Keys. Advantages of the STAR Schema. STAR
Schema: Examples. Chapter Summary. Review Questions. Exercises. 11
Dimensional Modeling: Advanced Topics. Chapter Objectives. Updates to the
Dimension Tables. Miscellaneous Dimensions. The Snowflake Schema. Aggregate
Fact Tables. Families of STARS. Chapter Summary. Review Questions.
Exercises. 12 Data Extraction, Transformation, and Loading. Chapter
Objectives. ETL Overview. Data Extraction. Data Transformation. Data
Loading. ETL Summary. Other Integration Approaches. Chapter Summary. Review
Questions. Exercises. 13 Data Quality: A Key to Success. Chapter
Objectives. Why is Data Quality Critical?. Data Quality Challenges. Data
Quality Tools. Data Quality Initiative. Master Data Management (MDM).
Chapter Summary. Review Questions. Exercises. Part 5 INFORMATION ACCESS AND
DELIVERY. 14 Matching Information to the Classes of Users. Chapter
Objectives. Information from the Data Warehouse. Who Will Use the
Information? Information Delivery. Information Delivery Tools. Information
Delivery: Special Topics. Chapter Summary. Review Questions. Exercises. 15
OLAP in the Data Warehouse. Chapter Objectives. Demand for Online
Analytical Processing. Major Features and Functions. OLAP Models. OLAP
Implementation Considerations. Chapter Summary. Review Questions.
Exercises. 16 Data Warehousing and the Web. Chapter Objectives. Web-Enabled
Data Warehouse. Web-Based Information Delivery. OLAP and the Web. Building
a Web-Enabled Data Warehouse. Chapter Summary. Review Questions. Exercises.
17 Data Mining Basics. Chapter Objectives. What is Data Mining?. Major Data
Mining Techniques. Data Mining Applications. Chapter Summary. Review
Questions. Exercises. Part 6 IMPLEMENTATION AND MAINTENANCE. 18 The
Physical Design Process. Chapter Objectives. Physical Design Steps.
Physical Design Considerations. Physical Storage. Indexing the Data
Warehouse. Performance Enhancement Techniques. Chapter Summary. Review
Questions. Exercises. 19 Data Warehouse Deployment. Chapter Objectives.
Data Warehouse Testing. Major Deployment Activities. Considerations for a
Pilot. Security. Backup and Recovery. Chapter Summary. Review Questions.
Exercises. 20 Growth and Maintenance. Chapter Objectives. Monitoring the
Data Warehouse. User Training and Support. Managing the Data Warehouse.
Chapter Summary. Review Questions. Exercises. Answers to Selected
Exercises. Appendix A. Project Life Cycle Steps and Checklists. Appendix B.
Critical Factors for Success. Appendix C. Guidelines for Evaluating Vendor
Solutions. Appendix D. Highlights of Vendors and Products. Appendix E.
Real-World Examples of Best Practices. References. Glossary. Index.
Preface. Part 1 OVERVIEW AND CONCEPTS. 1 The Compelling Need for Data
Warehousing. Chapter Objectives. Escalating Need for Strategic Information.
Failures of Past Decision Support Systems. Operational Versus
Decision-Support Systems. Data Warehousing--The Only Viable Solution. Data
Warehouse Defined. The Data Warehousing Movement. Evolution of Business
Intelligence. Chapter Summary. Review Questions. Exercises. 2 Data
Warehouse: The Building Blocks. Chapter Objectives. Defining Features. Data
Warehouses and Data Marts. Architectural Types. Overview of Components.
Metadata in the Data Warehouse. Chapter Summary. Review Questions.
Exercises. 3 Trends in Data Warehousing. Chapter Objectives. Continued
Growth in Data Warehousing. Vendor Solutions and Products. Significant
Trends. Emergence of Standards. Web-Enabled Data Warehouse. Chapter
Summary. Review Questions. Exercises. Part 2 PLANNING AND REQUIREMENTS. 4
Planning and Project Management. Chapter Objectives. Planning Your Data
Warehouse. The Data Warehouse Project. The Project Team. Project Management
Considerations. Chapter Summary. Review Questions. Exercises. 5 Defining
the Business Requirements. Chapter Objectives. Dimensional Analysis.
Information Packages--A Useful Concept. Requirements Gathering Methods.
Requirements Definition: Scope and Content. Chapter Summary. Review
Questions. Exercises. 6 Requirements as the Driving Force for Data
Warehousing. Chapter Objectives. Data Design. The Architectural Plan. Data
Storage Specifications. Information Delivery Strategy. Chapter Summary.
Review Questions. Exercises. Part 3 ARCHITECTURE AND INFRASTRUCTURE. 7 The
Architectural Components. Chapter Objectives. Understanding Data Warehouse
Architecture. Distinguishing Characteristics. Architectural Framework.
Technical Architecture. Architectural Types. Chapter Summary. Review
Questions. Exercises. 8 Infrastructure as the Foundation for Data
Warehousing. Chapter Objectives. Infrastructure Supporting Architecture.
Hardware and Operating Systems. Database Software. Collection of Tools.
Data Warehouse Appliances. Chapter Summary. Review Questions. Exercises. 9
The Significant Role of Metadata. Chapter Objectives. Why Metadata is
Important. Metadata Types by Functional Areas. Business Metadata. Technical
Metadata. How to Provide Metadata. Chapter Summary. Review Questions.
Exercises. Part 4 DATA DESIGN AND DATA PREPARATION. 10 Principles of
Dimensional Modeling. Chapter Objectives. From Requirements to Data Design.
The STAR Schema. STAR Schema Keys. Advantages of the STAR Schema. STAR
Schema: Examples. Chapter Summary. Review Questions. Exercises. 11
Dimensional Modeling: Advanced Topics. Chapter Objectives. Updates to the
Dimension Tables. Miscellaneous Dimensions. The Snowflake Schema. Aggregate
Fact Tables. Families of STARS. Chapter Summary. Review Questions.
Exercises. 12 Data Extraction, Transformation, and Loading. Chapter
Objectives. ETL Overview. Data Extraction. Data Transformation. Data
Loading. ETL Summary. Other Integration Approaches. Chapter Summary. Review
Questions. Exercises. 13 Data Quality: A Key to Success. Chapter
Objectives. Why is Data Quality Critical?. Data Quality Challenges. Data
Quality Tools. Data Quality Initiative. Master Data Management (MDM).
Chapter Summary. Review Questions. Exercises. Part 5 INFORMATION ACCESS AND
DELIVERY. 14 Matching Information to the Classes of Users. Chapter
Objectives. Information from the Data Warehouse. Who Will Use the
Information? Information Delivery. Information Delivery Tools. Information
Delivery: Special Topics. Chapter Summary. Review Questions. Exercises. 15
OLAP in the Data Warehouse. Chapter Objectives. Demand for Online
Analytical Processing. Major Features and Functions. OLAP Models. OLAP
Implementation Considerations. Chapter Summary. Review Questions.
Exercises. 16 Data Warehousing and the Web. Chapter Objectives. Web-Enabled
Data Warehouse. Web-Based Information Delivery. OLAP and the Web. Building
a Web-Enabled Data Warehouse. Chapter Summary. Review Questions. Exercises.
17 Data Mining Basics. Chapter Objectives. What is Data Mining?. Major Data
Mining Techniques. Data Mining Applications. Chapter Summary. Review
Questions. Exercises. Part 6 IMPLEMENTATION AND MAINTENANCE. 18 The
Physical Design Process. Chapter Objectives. Physical Design Steps.
Physical Design Considerations. Physical Storage. Indexing the Data
Warehouse. Performance Enhancement Techniques. Chapter Summary. Review
Questions. Exercises. 19 Data Warehouse Deployment. Chapter Objectives.
Data Warehouse Testing. Major Deployment Activities. Considerations for a
Pilot. Security. Backup and Recovery. Chapter Summary. Review Questions.
Exercises. 20 Growth and Maintenance. Chapter Objectives. Monitoring the
Data Warehouse. User Training and Support. Managing the Data Warehouse.
Chapter Summary. Review Questions. Exercises. Answers to Selected
Exercises. Appendix A. Project Life Cycle Steps and Checklists. Appendix B.
Critical Factors for Success. Appendix C. Guidelines for Evaluating Vendor
Solutions. Appendix D. Highlights of Vendors and Products. Appendix E.
Real-World Examples of Best Practices. References. Glossary. Index.
Warehousing. Chapter Objectives. Escalating Need for Strategic Information.
Failures of Past Decision Support Systems. Operational Versus
Decision-Support Systems. Data Warehousing--The Only Viable Solution. Data
Warehouse Defined. The Data Warehousing Movement. Evolution of Business
Intelligence. Chapter Summary. Review Questions. Exercises. 2 Data
Warehouse: The Building Blocks. Chapter Objectives. Defining Features. Data
Warehouses and Data Marts. Architectural Types. Overview of Components.
Metadata in the Data Warehouse. Chapter Summary. Review Questions.
Exercises. 3 Trends in Data Warehousing. Chapter Objectives. Continued
Growth in Data Warehousing. Vendor Solutions and Products. Significant
Trends. Emergence of Standards. Web-Enabled Data Warehouse. Chapter
Summary. Review Questions. Exercises. Part 2 PLANNING AND REQUIREMENTS. 4
Planning and Project Management. Chapter Objectives. Planning Your Data
Warehouse. The Data Warehouse Project. The Project Team. Project Management
Considerations. Chapter Summary. Review Questions. Exercises. 5 Defining
the Business Requirements. Chapter Objectives. Dimensional Analysis.
Information Packages--A Useful Concept. Requirements Gathering Methods.
Requirements Definition: Scope and Content. Chapter Summary. Review
Questions. Exercises. 6 Requirements as the Driving Force for Data
Warehousing. Chapter Objectives. Data Design. The Architectural Plan. Data
Storage Specifications. Information Delivery Strategy. Chapter Summary.
Review Questions. Exercises. Part 3 ARCHITECTURE AND INFRASTRUCTURE. 7 The
Architectural Components. Chapter Objectives. Understanding Data Warehouse
Architecture. Distinguishing Characteristics. Architectural Framework.
Technical Architecture. Architectural Types. Chapter Summary. Review
Questions. Exercises. 8 Infrastructure as the Foundation for Data
Warehousing. Chapter Objectives. Infrastructure Supporting Architecture.
Hardware and Operating Systems. Database Software. Collection of Tools.
Data Warehouse Appliances. Chapter Summary. Review Questions. Exercises. 9
The Significant Role of Metadata. Chapter Objectives. Why Metadata is
Important. Metadata Types by Functional Areas. Business Metadata. Technical
Metadata. How to Provide Metadata. Chapter Summary. Review Questions.
Exercises. Part 4 DATA DESIGN AND DATA PREPARATION. 10 Principles of
Dimensional Modeling. Chapter Objectives. From Requirements to Data Design.
The STAR Schema. STAR Schema Keys. Advantages of the STAR Schema. STAR
Schema: Examples. Chapter Summary. Review Questions. Exercises. 11
Dimensional Modeling: Advanced Topics. Chapter Objectives. Updates to the
Dimension Tables. Miscellaneous Dimensions. The Snowflake Schema. Aggregate
Fact Tables. Families of STARS. Chapter Summary. Review Questions.
Exercises. 12 Data Extraction, Transformation, and Loading. Chapter
Objectives. ETL Overview. Data Extraction. Data Transformation. Data
Loading. ETL Summary. Other Integration Approaches. Chapter Summary. Review
Questions. Exercises. 13 Data Quality: A Key to Success. Chapter
Objectives. Why is Data Quality Critical?. Data Quality Challenges. Data
Quality Tools. Data Quality Initiative. Master Data Management (MDM).
Chapter Summary. Review Questions. Exercises. Part 5 INFORMATION ACCESS AND
DELIVERY. 14 Matching Information to the Classes of Users. Chapter
Objectives. Information from the Data Warehouse. Who Will Use the
Information? Information Delivery. Information Delivery Tools. Information
Delivery: Special Topics. Chapter Summary. Review Questions. Exercises. 15
OLAP in the Data Warehouse. Chapter Objectives. Demand for Online
Analytical Processing. Major Features and Functions. OLAP Models. OLAP
Implementation Considerations. Chapter Summary. Review Questions.
Exercises. 16 Data Warehousing and the Web. Chapter Objectives. Web-Enabled
Data Warehouse. Web-Based Information Delivery. OLAP and the Web. Building
a Web-Enabled Data Warehouse. Chapter Summary. Review Questions. Exercises.
17 Data Mining Basics. Chapter Objectives. What is Data Mining?. Major Data
Mining Techniques. Data Mining Applications. Chapter Summary. Review
Questions. Exercises. Part 6 IMPLEMENTATION AND MAINTENANCE. 18 The
Physical Design Process. Chapter Objectives. Physical Design Steps.
Physical Design Considerations. Physical Storage. Indexing the Data
Warehouse. Performance Enhancement Techniques. Chapter Summary. Review
Questions. Exercises. 19 Data Warehouse Deployment. Chapter Objectives.
Data Warehouse Testing. Major Deployment Activities. Considerations for a
Pilot. Security. Backup and Recovery. Chapter Summary. Review Questions.
Exercises. 20 Growth and Maintenance. Chapter Objectives. Monitoring the
Data Warehouse. User Training and Support. Managing the Data Warehouse.
Chapter Summary. Review Questions. Exercises. Answers to Selected
Exercises. Appendix A. Project Life Cycle Steps and Checklists. Appendix B.
Critical Factors for Success. Appendix C. Guidelines for Evaluating Vendor
Solutions. Appendix D. Highlights of Vendors and Products. Appendix E.
Real-World Examples of Best Practices. References. Glossary. Index.