OLAP Solutions: Building Multidimensional Information Systems

OLAP enables users to access information from multidimensional data warehouses almost instantly, to view information in any way they like, and to cleanly specify and carry out sophisticated calculations. Although many commercial OLAP tools and products are now available, OLAP is still a difficult and complex technology to master.Substantially updated with expanded coverage of implementation methods for data storage, access, and calculation; also, new chapters added to combine OLAP with data warehouse, mining, and decision support toolsTeaches the best practices for building OLAP models that improve business and organizational decision–making, completely independent of commercial tools, using revised case studiesCompanion Web site provides updates on OLAP standards and tools, code examples, and links to valuable resources

Spis treści:
Preface.
Acknowledgments.
PART ONE: THE NEED FOR MULTIDIMENSIONAL TECHNOLOGY.
The Functional Requirements of OLAP Systems.
The Limitations of Spreadsheets and SQL.
Thinking Clearly in N Dimensions.
PART TWO: CORE TECHNOLOGY.
Introducton to the LC Model.
The Internal Structure of a Dimension.
Hypercubes or Semantic Spaces.
Multidimensional Formulas.
Links.
Analytic Visualization.
Physical Design of Applications.
PART THREE: APPLICATIONS.
Practical Steps for Designing and Implementing OLAP Models.
Introduction to the Foodcakes Application Example.
Purchasing and Currency Exchange.
Materials Inventory Analysis.
FCI′s Sales and Marketing.
FCI′s Activity–Based Manegement.
A Computational Example.
PART FOUR: FURTHER ISSUES.
Multidimensional Guidelines.
Product Language Comparisons.
DSS Fusion.
Appendix A: Formula Index.
Appendix B: Standards in the OLAP Marketplace.
Appendix C: LC Language Constructs.
Appendix D: Glossary.
Appendix E: The Relationship Between Dimensions and Variables.
Appendix F: Toward a Theoretically Grounded Model for OLAP and Its Conection to the Relational Model and Canonical Logic.
Appendix G: Codd′s 18 Features.
Notes.
Bibliography.
Index.

Nota biograficzna:
ERIK THOMSEN (ethomsen@dsslab.com) is Chief Scientist at DSS Lab, Inc., where he consults on the design and implementation of OLAP–based decision support systems, teaches at corporations and universities, and conducts research in the field of unified information systems. He also writes the "Analytic Solutions" column for Intelligent Enterprise. He is a coauthor of Microsoft OLAP Solutions (Wiley).