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The two types of OLAP are MOLAP (Multidimensional OLAP) and ROLAP (Relational OLAP) as explained
1. MOLAP: In this type of OLAP, a cube is aggregated from the relational data source (data warehouse). When user generates a report request, the MOLAP tool can generate the create quickly because all data is already pre-aggregated within the cube.
2. ROLAP: In this type of OLAP, instead of pre-aggregating everything into a cube, the ROLAP engine essentially acts as a smart SQL generator. The ROLAP tool typically comes with a 'Designer' piece, where the data warehouse administrator can specify the relationship between the relational tables, as well as how dimensions, attributes, and hierarchies map to the underlying database tables.
Right now, there is a convergence between the traditional ROLAP and MOLAP vendors. ROLAP vendor recognize that users want their reports fast, so they are implementing MOLAP functionalities in their tools; MOLAP vendors recognize that many times it is necessary to drill down to the most detail level information, levels where the traditional cubes do not get to for performance and size reasons.
The criteria for evaluating OLAP tools:
Slicing means taking out the slice of a cube, given certain set of select dimension (product), and value (home furnishings..) and measures (sales value, sales units..). Dicing means viewing the slices from different angles. For example -Revenue for different products within a given state or revenue for different states for a given product. One form of Slicing and Dicing is called pivoting.
Slicing means taking out the slice of a cube, given certain set of select dimension (customer segment), and value (home furnishings..) and measures (sales revenue, sales units..) or KPIs (Sales Productivity). Dicing means viewing the slices from different angles. For example -Revenue for different products within a given state OR revenue for different states for a given product.
Slicing and Dicing leads to what you can call Pivot. Pivot is known in Excel context. Pivot is the standard and basic look and feel of the views you create on the OLAP cubes. A pivot creates an ability for you to create the width and depth in your view of the data.
A pivot is a two dimensional lay-out of the summary data. The x and y axis are the dimensions and the intersection cells for any two dimension values contain the value of the measures.
To slice and dice is to break a body of information down into smaller parts or to examine it from different viewpoints so that you can understand it better. In cooking, you can slice a vegetable or other food or you can dice it (which means to break it down into small cubes). One approach to dicing is to first slice and then cut the slices up into dices. In data analysis, the term generally implies a systematic reduction of a body of data into smaller parts or views that will yield more information. The term is also used to mean the presentation of information in a variety of different and useful ways.