Handling Structural Heterogeneity in OLAP

Handling Structural Heterogeneity in OLAP

Carlos A. Hurtado (Universidad de Chile, Chile) and Claudio Gutierrez (Universidad de Chile, Chile)
Copyright: © 2007 |Pages: 31
DOI: 10.4018/987-1-59904-364-7.ch002
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Abstract

Structural heterogeneous OLAP data arise when several OLAP dimensions with different structure are mixed into a single OLAP dimension. In this chapter, we examine the problems encountered when handling structurally heterogeneity in OLAP and survey techniques that have been proposed to solve them. We show how to incorporate structural heterogeneity in the design of OLAP models. We explain why structural heterogeneity weakens aggregate navigation, the framework that guides users to formulate correct OLAP operations and systems to efficiently process them. We survey different techniques to deal with heterogeneity, including the modeling of heterogeneity by unbalanced dimensions, the solution proposed by Kimball, and the use of null elements to fix heterogeneity. Finally, we present a class of integrity constraints to model structural heterogeneity, called dimension constraints, introduced in previous work of the authors. We show the practical application of dimension constraints to support aggregate navigation and some of the aforementioned techniques for dealing with the problem.

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Table of Contents
Foreword
Tadeusz Morzy
Preface
Robert Wrembel, Christian Koncilia
Acknowledgments
Robert Wrembel, Christian Koncilia
Chapter 1
Stefano Rizzi
In the context of data warehouse design, a basic role is played by conceptual modeling, that provides a higher level of abstraction in describing... Sample PDF
Conceptual Modeling Solutions for the Data Warehouse
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Chapter 2
Carlos A. Hurtado, Claudio Gutierrez
Structural heterogeneous OLAP data arise when several OLAP dimensions with different structure are mixed into a single OLAP dimension. In this... Sample PDF
Handling Structural Heterogeneity in OLAP
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Chapter 3
Alejandro Vaisman
Today, information and timely decisions are crucial for an organization’s success. A Decision Support System is a software tool that provides... Sample PDF
Data Quality-Based Requirements Elicitation for Decision Support
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Chapter 4
Jovanka Adzic, Valter Fiore, Luisella Sisto
ETL stands for Extraction, Transformation, and Loading: in other words, for the Data Warehouse (DW) backstage. The main focus of our exposition here... Sample PDF
Extraction, Transformation, and Loading Processes
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Chapter 5
Alkis Simitsis, Panos Vassiliadis, Spiros Skiadopoulos, Timos Sellis
In the early stages of a data warehouse project, the designers/administrators have to come up with a decision concerning the design and deployment... Sample PDF
Data Warehouse Refreshment
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Chapter 6
Nikos Karayannidis, Aris Tsois, Timos Sellis
Star queries are the most prevalent kind of queries in data warehousing, OLAP and business intelligence applications. Thus, there is an imperative... Sample PDF
Advanced Ad Hoc Star Query Processing
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Chapter 7
Kurt Stockinger, Kesheng Wu
In this chapter we discuss various bitmap index technologies for efficient query processing in data warehousing applications. We review the existing... Sample PDF
Bitmap Indices for Data Warehouses
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Chapter 8
Karen C. Davis, Ashima Gupta
Bitmap Indexes (BIs) allow fast access to individual attribute values that are needed to answer a query by storing a bit for each distinct value and... Sample PDF
Indexing in Data Warehouses: Bitmaps and Beyond
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Chapter 9
Pedro Furtado
Running large data warehouses (DW) efficiently over low cost platforms places special requirements on the design of system architecture. The idea is... Sample PDF
Efficient and Robust Node-Partitioned Data Warehouses
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Chapter 10
Uwe Rohm
This chapter presents a new approach to on-line decision support systems that is scalable, fast, and capable of analysing even up-to-date data. It... Sample PDF
OLAP with a Database Cluster
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Chapter 11
Rokia Missaoui, Ganaël Jatteau, Ameur Boujenoui, Sami Naouali
In this paper, we present alternatives for coupling data warehousing and data mining techniques so that they can benefit from each other’s advances... Sample PDF
Toward Integrating Data Warehousing with Data Mining Techniques
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Chapter 12
Carlo Combi, Barbara Oliboni
This chapter describes a graph-based approach to represent information stored in a data warehouse, by means of a temporal semistructured data model.... Sample PDF
Temporal Semistructured Data Models and Data Warehouses
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Chapter 13
Yvan Bedard, Sonia Rivest, Marie-Josée Proulx
It is recognized that 80% of data have a spatial component (ex. street address, place name, geographic coordinates, map coordinates). Having the... Sample PDF
Spatial Online Analytical Processing (SOLAP): Concepts, Architectures, and Solutions from a Geomatics Engineering Perspective
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