The world of business intelligence is maturing and early years of turbulant time is over. This progress is witnessed with increased importance seen from companies to drive their BI initiative from a business point of view rather than technology driven. Additionally, we have seen steady progress in the development of standards, models, and frameworks in the last few years.
Rome wasn't built in a day, so does a business intelligence system of any organization. It requires lot of strategies and efforts to build such a solution.
To start with the effort of building business intelligence system, one needs a framework comprising of best practices, policies, and standards. Business intelligence architecture, by providing this framework, ensures that the development efforts of multiple projects fit neatly together as a cohesive whole to achieve desired BI system.
Lets explore the definition of business intelligence(BI). It is an umbrella term that combines architectures, applications, and databases. It enables the real-time, interactive access, analysis, and manipulation of information, which provides the business community with easy access to business data. By analyzing the past and present business situations and performances, BI provides valuable insight to any organization.
Business intelligence and data warehousing technologies are heavy on jargons. There are specific terms to define specific method and processes. For a beginner, it may be confusing to go through a technical paper to grasp clear understanding.
A grocery chain used the data mining capacity of a software to analyze local buying patterns. They discovered that when men bought diapers on Thursdays and Saturdays, they also tended to buy beer. Further analysis showed that these shoppers typically did their weekly grocery shopping on Saturdays. On Thursdays, however, they only bought a few items. The retailer concluded that they purchased the beer to have it available for the upcoming weekend.
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