Erik Thomsen 
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 tools

* Teaches the best practices for building OLAP models that
improve business and organizational decision-making, completely
independent of commercial tools, using revised case studies

* Companion Web site provides updates on OLAP standards and
tools, code examples, and links to valuable resources

İçerik tablosu

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.

Yazar hakkında

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).