Page 19 - DCAP606_BUSINESS_INTELLIGENCE

Business Intelligence Sartaj Singh, Lovely Professional University

Notes Unit 2: Multidimensional Analysis

CONTENTS
Objectives
Introduction

2.1 Dimension Attributes
2.1.1 Key Attribute
2.2 Dimension Hierarchy

2.2.1 Type of Hierarchy
2.3 Summary
2.4 Keywords
2.5 Review Questions
2.6 Further Readings

Objectives

After studying this unit, you will be able to:
Recognize the Dimension Attributes

Summarize the Dimension Hierarchy
Identify the Type of Hierarchy
Introduction

In statistics and related fields, multidimensional analysis is a data analysis process that groups
data into two or more categories: data dimensions and measurements. To show this, let us take
the case of a football game. A data set which comprises of the number of wins for one cricket
team every year for many years could be categorized into a single dimensional or longitudinal
data set. Another data set which comprises of the number of wins many different cricket groups
inside a year can be under a single dimensional or traverse sectional data set. A single data set
that comprises of the number of wins for diverse cricket teams over numerous years could be
comprised in a two-dimensional data set.

Multi-Dimensional analysis is an Informational analysis on data which takes into account
numerous distinct connections, each of which comprises a dimension. For example, a retail
analyst may want to understand the connections amidst sales by district, by quarter, by
demographic circulation or by product. Multi-dimensional analysis will yield outcomes for
these complex relationships.

2.1 Dimension Attributes

A dimension consists of members.

Example: The members of a product dimension are the individual products.

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