Business Intelligence Essay

995 Words2 Pages

Business Intelligence (BI) It is often describe as “the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes”. Business Intelligence is a technology that are capable of handling a large amounts of undetermined data to help identify, develop and create a new strategic business opportunities. Business Intelligence also encloses a variety of tools, applications and methodologies that enable organizations to gathered data from the internal systems and external sources. It can also be used to support a wide range of business decisions from operational to strategic. It includes product positioning or pricing. Business Intelligence is also a most effective way when it …show more content…

Data Warehousing – This comprehensive database is used for reporting and data analysis. The information is uploaded from a separate operational system.
8. Decision Engineering – a framework that utilizes the best practices for organizational decision making. It helps businesses make decisions on a various business approaches.
9. Business Performance Management – Management and analytic processes that manage a business performance to achieve short-and-long term goals.

Practical Applications of Business Intelligent SAS Business Intelligence for the Health Care Industry: Practical Applications teaches health care executives, managers, providers, and business analysts how to use SAS Business Intelligence (BI) tools to convert data into knowledge and value at all levels in the health care industry.
All applications are created with sample data that has the richness and complexity of operational health care data. Topics include:
• using SAS Add-In for Microsoft Office and SAS Stored Processes technology to better track and forecast revenues and margins
• creating OLAP and relational web reports that enable care management programs to locate and assist the neediest patients
• implementing data access restrictions on OLAP and relational data in accordance with the industry’s need for secure data

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