Business Intelligence | Computerworld


Companies use a wide range of technologies and products to generate what’s known as business intelligence (BI).

The most common tools – simple query and reporting, online analytical processing, statistical analysis, forecasting and data mining – can be used in a variety of ways.

Applications can provide ad hoc access to a single piece of data, such as monthly sales figures. Or they can be mission-critical, Web-enabled engines used to drive business processes. The goal is to turn what are often mountains of data into useful information. The common platform to achieve this is the database.

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Examples of Business Intelligence

A hotel franchise uses BI analytical applications to compile statistics on average occupancy and average room rate to determine revenue generated per room. It also gathers statistics on market share and data from customer surveys from each hotel to determine its competitive position in various markets. Such trends can be analyzed year by year, month by month and day by day, giving the corporation a picture of how each individual hotel is faring.

A bank bridges a legacy database with departmental databases, giving branch managers and other users access to BI applications to determine who the most profitable customers are or which customers they should try to cross-sell new products to. The use of these tools frees information technology staff from the task of generating analytical reports for the departments and it gives department personnel autonomous access to a richer data source.

A telecommunications company maintains a multiterabyte decision-support data warehouse and uses business intelligence tools and utilities to let users access the data they need without giving them carte blanche to access hundreds of thousands of mission-critical records. The tools set boundaries around the data that users can access, creating data “cubes” that contain only the information that’s relevant to a particular user or group of users.

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Actually, a refined aggregation of multiple databases, called a data warehouse, is the best source for BI. Data selected for use in the warehouse is reformatted and stored in a process called extraction, translation and loading (ETL). The process standardizes the various data structures so they can be accessed and analyzed with high accuracy.

With a rich, aggregated data source, BI applications and utilities can be used to forecast business conditions, improve operational efficiencies and manage supply chains. BI has been applied most commonly to customer relationship management (CRM), enabling analysis of customer behavior and market segmentation.

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