Exam 12: Business Intelligence

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OLAP, which stands for Online Analytical Processing, is a category of software tools that provide analysis of data stored in a database. OLAP allows users to conduct multidimensional analysis of business data and provides the capability for complex calculations, trend analysis, and sophisticated data modeling. It is an approach to quickly answer multi-dimensional analytical queries.

The key element of OLAP is the concept of multidimensionality, which allows for complex calculations, trend analysis, and data modeling. This is where the data cube comes into play.

A data cube is a multi-dimensional array of values, typically derived from a relational database. To understand a data cube, imagine a spreadsheet that has more than two dimensions. While a traditional spreadsheet is two-dimensional (rows and columns), a data cube has three or more dimensions. These dimensions are aspects of the data that can be summarized, such as time, geography, product, and customer demographics.

Each cell within a data cube contains aggregated data related to elements along each of its dimensions. For example, in a retail sales data cube, one can have dimensions like time (years, quarters, months), products (categories, brands, items), and location (countries, cities, stores). A cell in this cube might contain the total sales for a particular product, in a specific store, during a certain month.

Users can "slice and dice" the data cube to look at different facets of the data. "Slicing" is taking a single layer from the cube—for instance, sales for a specific month—while "dicing" is creating a sub-cube by selecting specific values of multiple dimensions—for example, sales for a particular product in a certain region over a set time period.

OLAP tools can also perform operations such as "drill-down" and "roll-up". Drill-down involves navigating from summarized data to more detailed data, while roll-up is the opposite, summarizing detailed data into more general terms.

In summary, OLAP is a powerful technology for data discovery, including capabilities for limitless report viewing, complex analytical calculations, and predictive “what if” scenario planning. The data cube is a central component of OLAP and provides a multidimensional view of data, which allows for quick access to strategic information for analysis.