Web-enabled OLAP Tutorial

- DW Overview

--------Back-end Tools

- Intro to OLAP

--------Codd's 12 Rules

- MD Data Structures

- OLAP Server

- OLAP Operations

- OLAP Architectures

--------MOLAP: Part I
--------MOLAP: Part II
--------ROLAP: Part I
--------ROLAP: Part II

- Data Explosion

- OLAP Criteria

- Glossary

- References

OLAP Server

In order to offer consistent, rapid response to queries (regardless of database size and complexity), OLAP needs to be implemented in a multi-user client/server mode. This can be achieved through use of an OLAP server. So what is an OLAP server? It is specifically designed to support and operate on multidimensional data structures, as the name implies. It can handle a high capacity of data with multi-users. The multidimensional structure is arranged in a way where every data item is located and accessed based on the intersection of the dimension members which define that item. The server design and data structure are optimized for rapid ad-hoc information retrieval in any orientation. Also it allows fast, flexible calculation and transformation of raw data based on the formulaic relationships. The OLAP server could physically stage the processed multi-dimensional information to deliver consistent and rapid response times to users. Or, it could populate its data structures in real time from relational or other databases. Staging the multi-dimensional data in the OLAP server is typically preferred.

OLAP Server
Figure 1. OLAP server

OLAP Server Roles


Rules governing business issues must be clearly outlined as they are keys to successful data warehouse implementation. Some examples would include goals and scope of the data warehouse, operational issues such as loading and maintenance frequency, and organizational issues such as information security.


Raw data must be transformed and cleansed before storing in a data warehouse. This involves restructuring, redefining, filtering, combining, recalculating, and summarizing data fields from operations systems.


It must allow all applications accessing the data warehouse to use a common set of conventions, which is possible with metadata. It stores information about data structures, objects, rules in the data warehouse.


Data must be stored in a way that can maximize system flexibility, manageability, and overall accessibility.


The analytic component must support sophisticated queries, rapid calculation of business metrics, planning and forecasting functions, and what-if analysis on large volumes.

Presentation and access

It must provide users with tools for selecting, viewing, manipulating, visualizing, analyzing, and navigating through data. Some examples would include spreadsheets, query tools, web browsers, statistical packages, visualization tools, or report writers.

Selecting an OLAP Server

Relational OLAP (ROLAP) Server

  • Standard or extended relational database management systems.
  • Data is stored in relational databases.
  • Support extensions to SQL and special access and implementation methods to efficiently implement the multidimensional data model and operations.

Multidimensional OLAP (MOLAP) Server

  • Directly store multidimensional data in special data structures such as arrays.
  • Implement the OLAP operations over these special data structures