When and Who should use OLAP?

When and Who should use OLAP? Well all database professional will or already have come accross this question regarding OLAP. Here we will try to analyze and find out. I have found few interesting document on why OLAP.

Why OLAP – An overview of On-line Analytical Processing
A Databeacon.com White paper
October 2004

On-Line Analytical Processing (OLAP) tools meet the need for interactive multidimensional reporting and analysis. They allow operational managers to perform trend, comparative, and time-based analysis by enabling exploration of pre-calculated and summarized data along multiple dimensions. Operational managers can explore data first at a summary level, then drill down through the data hierarchy to examine increasingly granular levels of detail.

This document provides a brief description of On-Line Analytical Processing, its history, and some of the main features that define it.

Executive Summary

The diversity and pace of today's business require complementary tools that support greater variability of use and dynamic interaction with the data to support operational managers as they explore and evaluate interrelationships in the data. An operational manager doing trend analysis on a particular product line would require a mountain of static reports to accommodate his/her analysis needs, an approach that is not desired or sustainable.

On-Line Analytical Processing (OLAP) tools meet the need for interactive multidimensional reporting and analysis. They allow operational managers to perform trend, comparative, and
time-based analysis by enabling exploration of pre-calculated and summarized data along
multiple dimensions. Operational managers can explore data first at a summary level, then drill
down through the data hierarchy to examine increasingly granular levels of detail.

This document provides a brief description of On-Line Analytical Processing, its history, and
some of the main features that define it.

Introduction

Data is the life-blood of all organizations. It is constantly collected, manipulated, managed and explored by operational managers and other employees as they evaluate the health and operation of the business. They review past and present metrics such as cost and revenue to
make decisions that will improve the performance and profitability of their organization.

The responsibility and challenge of collection and delivery of this data in a meaningful form
traditionally belongs to the I.T. department. This is no small challenge as both data volume
and the number of operational managers requesting access are growing exponentially. This rapid growth and an Internet-paced business environment are causing many I.T. purchase decisions to be driven by the "frontline" needs of the operational managers tasked with the delivery of revenue-enhancing or cost-saving initiatives. And in some cases, the owners of those initiatives are bypassing central I.T. entirely to achieve their objectives. Whether departmental or I.T. rooted, organizations are constantly looking for new methods of delivery and new methods to quickly distill exploding data into useful, actionable information.

Special tools for special needs

From the beginning of data collection, we have had reporting tools - production, managed and
ad hoc - that allow report authors and operational managers such as the VP Finance to access, navigate and explore relational data and quickly create reports with minimal understanding of the underlying database language, connectivity and functionality. These tools evolved in capability and audience as we moved from database reporting, to Decision Support Systems (DSS), to Executive Information Systems (EIS) and now to Business Intelligence (BI) and Business Performance Management (BPM). The reporting solutions commonly offered in these toolsets invariably offer some snapshot of the data in a twodimensional, static view. A powerful example is an Income Statement, a periodic static view of the business for review by the VP Finance and other executives.

The diversity and pace of today's business require complementary tools that support greater variability of use and dynamic interaction with the data to support operational managers as they explore and evaluate interrelationships in the data. An operational manager doing trend analysis on a particular product line would require a mountain of static reports to accommodate his/her analysis needs, an approach that is not desired or sustainable. As seen in Figure 1, operational managers need multiple degrees of freedom in their exploration and analysis, as made available in dynamic reports, and in particular, interactive multidimensional reports.


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