Dynamic Multidimensional Data Cubes

Dynamic Multidimensional Data Cubes

Mirek Riedewald (University of California, Santa Barbara, USA), Divyakant Agrawal (University of California, Santa Barbara, USA) and Amr El Abbadi (University of California, Santa Barbara, USA)
Copyright: © 2003 |Pages: 22
DOI: 10.4018/978-1-59140-053-0.ch007
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Abstract

Data cubes are ubiquitous tools in data warehousing, online analytical processing, and decision support applications. Based on a selection of pre-computed and materialized aggregate values, they can dramatically speed up aggregation and summarization over large data collections. Traditionally, the emphasis has been on lowering query costs with little regard to maintenance, i.e., update cost issues. We argue that current trends require data cubes to be not only query-efficient, but also dynamic at the same time, and we also show how this can be achieved. Several array-based techniques with different tradeoffs between query and update cost are discussed in detail. We also survey selected approaches for sparse data and the popular data cube operator, CUBE. Moreover, this work includes an overview of future trends and their impact on data cubes.

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Table of Contents
Preface
Maurizio Rafanelli
Chapter 1
Basic Notions  (pages 1-45)
Maurizio Rafanelli
This chapter presents the basic notions regarding multidimensional (aggregate) databases by referring to different definitions given for them in the... Sample PDF
Basic Notions
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Chapter 2
Arie Shoshani
The term “multidimensional databases” refers to data that can be viewed conceptually in a multidimensional space, where each dimension represents... Sample PDF
Multidimensionality in Statistical, OLAP and Scientific Databases
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Chapter 3
Riccardo Torlone
A variety of multidimensional data models have recently been proposed by both academic and industry communities. but consensus on formalism or even... Sample PDF
Conceptual Multidimensional Models
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Chapter 4
Hierarchies  (pages 91-115)
Elaheh Pourabbas, Maurizio Rafanelli
In this chapter we will focus on the rules of aggregation hierarchies in analysis dimensions of a cube. We give an overview of the related works on... Sample PDF
Hierarchies
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Chapter 5
Maurizio Rafanelli
In this chapter the author proposes the different approaches for defining operators able to manipulate this multidimensional structure. In... Sample PDF
Operators for Multidimensional Aggregate Data
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Chapter 6
Alberto O. Mendelzon, Alejandro A. Vaisman
In spite of the obvious importance of time in data warehousing and OLAP, current commercial systems do not support tracking the history of a data... Sample PDF
Time in Multidimensional Databases
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Chapter 7
Mirek Riedewald, Divyakant Agrawal, Amr El Abbadi
Data cubes are ubiquitous tools in data warehousing, online analytical processing, and decision support applications. Based on a selection of... Sample PDF
Dynamic Multidimensional Data Cubes
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Chapter 8
Stefano Paraboschi, Giuseppe Sindoni, Elena Baralis, Ernst Teniente
This chapter presents materialized views in the context of multidimensional databases (MDDBs). A materialized view is a view whose content is... Sample PDF
Materialized Views in Multidimensional Databases
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Chapter 9
Leonardo Tininini
A powerful and easy-to-use querying environment is certainly one of the most important components in a multidimensional database, and its... Sample PDF
Querying Multidimensional Data
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Chapter 10
Cirtis E. Dyreson, Torben Bach Pedersen, Christian S. Jensen
While incomplete information is endemic to real-world data, current multidimensional data models are not engineered to manage incomplete information... Sample PDF
Incomplete Information in Multidimensional Databases
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Chapter 11
Francesco M. Malvestuto, Marina Moscarini
When answering queries that ask for summary statistics, the query-system of a multidimensional database should guard confidential data, that is, it... Sample PDF
Privacy in Multidimensional Databases
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Chapter 12
Andrea Cali, Domenico Lembo, Maurizio Lenzerini, Riccardo Rosati
While the main goal of a data warehouse is to provide support for data analysis and management’s decisions, a fundamental aspect in design of a data... Sample PDF
Source Integration for Data Warehousing
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Chapter 13
Elaheh Pourabbas
The purpose of this chapter is to create cooperation between geographic databases (GDBs) and multidimensional databases (MDDBs), which are... Sample PDF
Cooperation with Geographic Databases
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About the Authors