Business Intelligence Model (BIM)
This article provides a practical explanation of the Business Intelligence Model (BIM). After reading, you'll understand the basics of this powerful strategy tool.
What is the Business Intelligence Model (BIM)
The Business Intelligence Model (BIM) is a model that offers opportunities for businesses to transform raw data into meaningful and useful information, in order to build an effective strategic plan, as well as create tactical and operational insights for decision-making within a given timeframe.
In the end, this knowledge needs to get to the right people, at the right moment, and via the right channel. Organisations collect large quantities of information. These are often raw data, such as facts and large data chains.
This information, data, needs to be processed and interpreted because it opens up new opportunities within the organisation, which may result in a competitive advantage.
The purpose of Business Intelligence (BI) depends on the strategy of the organisation. This is often derived from the business goal or mission statement.
Richard Millar Devens presented the term Business Intelligence (BI) to the Cyclopaedia of Commercial and Business Anecdotes in 1865. Later, in 1958, IBM computer scientist Hans Peter Luhn published an article about the potential of BI through the use of technology.
Business Intelligence Applications and Tools
Business Intelligence (BI) is not a product or system in itself. More often, the Business Intelligence Model (BIM) is referred to as an architecture that includes a collection of integrated applications and databases which support operations and the decision-making process.
These provide the business world with easy access to business and market data. Such Business Intelligence (BI) applications support activity and decision support systems (DSS), systems, reports, online analytical processing (OLAP), static data analyses, prognosis, and data mining.
The Decision Support System (DSS) is a computer support system used by managers and planners for decision-making. DSS combines human thinking and modelling systems in order to make well-informed and considered decisions.
For instance, DSS is used in logistical solutions. A business with a large inventory list can use DSS to generate movement in the supply chain.
Online Analytical Processing (OLAP) is another effective IT solution that is much used in the decision-making process of the business world. With this system, it is possible ...
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