Dr. E.F. Codd the ―father‖ of the relational model, created a list of rules to deal with the OLAP systems. Users should priorities these rules according to their needs to match their business requirements. These rules are:
1. Multidimensional conceptual view: The OLAP should provide an appropriate multidimensional Business model that suits the Business problems and Requirements.
2. Transparency: The OLAP tool should provide transparency to the input data for the users.
3. Accessibility: The OLAP tool should only access the data required only to the analysis needed.
4. Consistent reporting performance: The Size of the database should not affect in any way the performance.
5. Client/server architecture: The OLAP tool should use the client server architecture to ensure better performance and flexibility.
6. Generic dimensionality: Data entered should be equivalent to the structure and operation requirements.
7. Dynamic sparse matrix handling: The OLAP too should be able to manage the sparse matrix and so maintain the level of performance.
8. Multi-user support: The OLAP should allow several users working concurrently to work together.
9. Unrestricted cross-dimensional operations: The OLAP tool should be able to perform operations across the dimensions of the cube.
10.Intuitive data manipulation. ―Consolidation path re-orientation, drilling down across columns or rows, zooming out, and other manipulation inherent in the consolidation path outlines should be accomplished via direct action upon the cells of the analytical model, and should neither require the use of a menu nor multiple trips across the user interface.‖(Reference 4)
11. Flexible reporting: It is the ability of the tool to present the rows and column in a manner suitable to be analyzed.
12. Unlimited dimensions and aggregation levels: This depends on the kind of Business, where multiple dimensions and defining hierarchies can be made.
In addition to these guidelines an OLAP system should also support:
Comprehensive database management tools: This gives the database management to control distributed Businesses
The ability to drill down to detail source record level: Which requires that The OLAP tool should allow smooth transitions in the multidimensional database.
Incremental database refresh: The OLAP tool should provide partial refresh.
Structured Query Language (SQL interface): the OLAP system should be able to integrate effectively in the surrounding enterprise environment.
OLTP vs OLAP
OLTP stands for On Line Transaction Processing and is a data modeling approach typically used to facilitate and manage usual business applications. Most of applications you see and use are OLTP based. OLTP technology used to perform updates on operational or transactional systems (e.g., point of sale systems)
OLAP stands for On Line Analytic Processing and is an approach to answer multi-dimensional queries. OLAP was conceived for Management Information Systems and Decision Support Systems. OLAP technology used to perform complex analysis of the data in a data warehouse.