Business Intelligence Plan Essay

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Business Intelligence Plan

Executive Summary
The purpose of this report is to explain the importance of Business Intelligence and all of its components for implementation into the business structure. During the recent years obtaining useful information in real time has become something that is extremely important, if not even a critical, factor of success for companies. The time managers have available for use in making business decisions has been reduced dramatically. Competitive pressures are now requiring that businesses make intelligent decisions based on their incoming business data, and these decisions must be made immediately (Business Intelligence and Data Warehousing, 2005, p.5; Hocevar &
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This is an essential component of BI for arriving at valid business decisions. Similar data can be stored in multiple repositories within a single business; one example would be the inventory of items for sale. When considering data sources, it is important to understand if there is a recognized authoritative source for a specific type of data. In many enterprises, the data required for making business decisions is created by wide ranging applications, perhaps from separate lines of business (Theme 1).
BI systems today have the capacity to work with numerous types of data such as numerical or non-numerical data. The quality of this data is as important as any other data. The difference in the level of data quality is one of the many factors that may explain why some organizations are successful with their BI initiative while some are not so successful (Isik, O., Jones, M.C., & Sidoroya, A. 2011).
Component three is Data Analytics. This component is used for the analysis of data. Data analytics refers to the business intelligence technologies that are grounded for the most part in data mining and statistical analysis. Due to the success that has been achieved overall by the data mining and statistical analysis community, data analytics continues to be an active area of research (Hsinchun, Chiang, & Storey, 2012).
Data analytics are structured in statistical theories and models, multivariate statistical analysis. It also covers other
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