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Business Process Management and Enterprise Architecture
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Business Intelligence is described as the set of tools and techniques for the transformation of raw data into effective and relevant information for business analysis. The word data surfacing is also more often associated with BI functionality.

BI technologies are enough competent for handling large amounts of unstructured data to help classifying, developing and creating new strategic business opportunities. The objective of BI is to permit for easy interpretation of these large volumes of data. Analyzing new opportunities and implementing a powerful strategy based on insights can prepare businesses for a competitive market advantage and long-term stability.

BI technologies offers current,predictive and historical views of business operations. Common functions of BI technologies are data mining, reporting, on-line analytical processing,benchmarking, analytics,text mining, complex event processing, predictive analytics, process mining, prescriptive analytics and business performance management.

It can be used to support a large range of business decisions ranging from operational to strategic. In this, basic operating decisions include product positioning or pricing and strategic business decisions includes goals, objectives, priorities and directions at the broadest level. BI is most effective and powerful when it integrates data derived from the market in which a company operates with data from company sources internally to the business such as financial and operations data. When it combined, the internal and external data can provide a more complete picture which creates an “intelligence” that cannot be achieved by any singular set of data.


BI is made up of an increasing number of components including:

  • Standardization, denormalization,tagging and multidimensional aggregation and allocation
  • A procedure of interfacing with unstructured data sources
  • Real time reporting with analytical observance
  • Probabilistic simulation and statistical inference
  • Rolling forecasts, budgeting and group consolidation
  • Key performance indicators optimization and open item management.

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