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Modeling and Querying Multidimensional

Databases: an Overview by Patrick Marcel

Presented By: Amani Al-Ajlan Asma Al-Saleh

King Saud UniversityThe College of Computer & Information Science

Computer Science Department

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Outlines

• Multidimensional Database query2

• Introduction

• Multidimensional DB VS Relational DB

• On-Line Analytical Processing (OLAP)

• Multidimensional Database modeling

• Multidimensional Database operations

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Outlines

• Multidimensional Database query3

• Introduction

• Multidimensional DB VS Relational DB

• On-Line Analytical Processing (OLAP)

• Multidimensional Database modeling

• Multidimensional Database operations

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• MDD is a database designed to allow efficient storageand retrieval of large volumes of data that is viewed andanalyzed from different perspectives.

• Use when the objective is to analyze data rather than toperform online transactions.

• MDD is a key factor in the interactive analysis of large

amounts of data for decision-making purposes.

Introduction

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Outlines

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• Introduction

• Multidimensional DB VS Relational DB

• On-Line Analytical Processing (OLAP)

• Multidimensional Database modeling

• Multidimensional Database operations

• Multidimensional Database query

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Multidimensional DB VS Relational DB

Relational DB MDD

Many different tables all linkedand joined together in a variety

of ways

Not good at retrieving a largenumber of records and

summarizing them on the fly

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Structured in specificdimensions, not tables

Many relationships areprecalculated, this greatly

speeds response andcomputation time

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Multidimensional DB VS Relational DB

Region Time

Product

Answer Answer

Multidimensional DBRelational DB

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Multidimensional DB VS Relational DB

Sales 1996(Relational)

Sales 1996(2-dimintional)

Simple Example:

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MDD Advantages

1. Fast retrieval

2. Fast calculation

3. Storage is very efficient

4. Fast query response time

5. Ease of Data Presentation and Navigation

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MDD Limitations

1. This research area is very recent, and several workshave appeared, but no commonly agreed frameworkhas emerged

2. Not used in one-to-one relationship

1

3

2

4 M a n

a g e r

Department

1 40

80 50

59 33

90 50 4

Region

P r o

d u c

t

10(One-to-One) (Many-to-Many)

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Outlines

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• Introduction

• Multidimensional DB VS Relational DB

• On-Line Analytical Processing (OLAP)

• Multidimensional Database modeling

• Multidimensional Database operations

• Multidimensional Database query

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• Is an approach to quickly providinganswers to analytical queries that are

multidimensional in nature

Online Analytical Processing(OLAP)

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Outlines

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• Introduction

• Multidimensional DB VS Relational DB

• On-Line Analytical Processing (OLAP)

• Multidimensional Database modeling

• Multidimensional Database operations

• Multidimensional Database query

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Database Modeling Categories:

1. Two-dimensional databases

2. Full multidimensional (hypercube) models

3. Multidimensional models based on relations

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2.Full multidimensional(hypercube) models

cells

measure

dimens ion

members

The cube sales

F sales (1994,nuts,north) = 10

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Example:

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3.Multidimensional models based on relations

Example:

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Dimension

Relations

Measure

Relation

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Dimension Hierarchy

• Organizing the information into a hierarchy, to be able to examine it at different levels of detail

• Levels are described by a graph that indicatehow members of some level are grouped

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Example:

Dimension Hierarchy

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Example Cont.: Sale result can be viewed at region level or at cities

level.

Region level Cities level

Dimension Hierarchy Cont.

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• Group ing relat ion : used to model part of the hierarchies associated with the cube sales . It represents how citiesare grouped to form regions.

•

this relation can be used to compute the cube sales fromthe cube sales cities

Dimension Hierarchy Cont.

(Grouping relation)

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