Online analytical processing (OLAP) is a category of software technology that enables analysts, managers, and executives to gain insight into data through fast, consistent, interactive access to a wide variety of possible views of information that has been transformed from raw data to reflect the real dimensionality of the enterprise as understood by the user. This presentation provides a good visualization of what OLAP does. In particular, it illustrates slicing and dicing data and drilldown and rollup.

Kinds of OLAP ROLAP- relational OLAP using relational databases; a star schema is used MOLAP- multidimensional OLAP using multidimensional databases DOLAP- desktop OLAP Other variations OLAP comes in many “flavors.” The most common is ROLAP, because organizations typically prefer to use relational database technology. In this case, a star schema data model is used. For performance reasons, special purpose database technology, such as Essbase, is used. When this is the case, the data model is a multidimensional cube. Multidimensional vendors sometimes jokingly refer to ROLAP as SLOWLAP. Students are typically only familiar with relational databases and do not know that there are other technologies.

Example: Olap Usage of an Automobile Marketer The Story An automobile marketer wants to improve business activity. Therefore he wants to view sales figures from different perspectives. The Data Needs Sales by model Sales by dealership Sales by color Sales over time etc. The dimensions in this example are the car’s model, color, and dealership. A Question What is the trend in sales volumes over a period of time for a specific model and color across a specific group of dealerships ?

Example: The Multidimensional View of the Data Sales Volumes Van MOD E L Coupe Smith Here the data is represented in a cube. The cells in the cube contain the number of cars sold that correspond to the specific measures of the dimensions; for example, the number of blue sedans sold at the Miller dealership. Sedan Clyde Miller Blue Red White DEALERSHIP COLOR

OLAP Features: “Slicing and Dicing“ the Data Choosing a range out of each dimension: Color: Blue and White Model: Coupe only Dealership: Clyde only Sales Volumes Clyde Blue White Coupe “Sliced and Diced“ Data Van MOD E L Coupe Smith Sedan The sum of the numbers in the two cubes gives the number of blue and white coupes sold at the Clyde dealership. Clyde Miller Blue Red White DEALERSHIP COLOR

OLAP Features: Rotating the Data Different users will require different views of the multidimensional cube – OLAP allows easy rotation of data View of the Product Manager View of the Account Manager Sales Volumes DEALERSHIP Sales Volumes Miller Smith Clyde Van Coupe Sedan MOD E L Rotate the data cube by 90° Van MOD E L Coupe Different users may want to slice and dice the data differently, depending on their needed perspective. In the second example, the account manager is primarily interested in how the different models are selling in the various dealerships. Sedan Blue Red White COLOR

Sales Volumes by Organization Dimension - three level hierarchy - OLAP Features: Drill-Down and Roll-Up Data can be disaggregated and aggregated along a dimension according to their natural hierarchy Roll-Up Sales Volumes by Organization Dimension - three level hierarchy - Georgia State Region Atlanta Athens Dealership In OLAP software, drill-down and roll-up are performed with a single mouse click. Miller Smith Clyde Lucas Gleason Drill-Down