QUESTION: The promise of BI to help society advance preventative medicine and healthcare versus sick care is just starting to be tapped. Looking to the future, what are three breakthroughs in preventative health you predict will come about because of the use of BI? (Explain your choices). Cite your work!
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READING: Economic and political drivers are making the use of BI a critical function for healthcare organizations. Tapping into the hidden knowledge within data through BI holds promise for improving patient care outcomes, increasing efficiency, and decreasing healthcare costs. However, before tapping into this new wealth of knowledge can be achieve, a myriad of data management issues must be addressed. Many of these issues are associated with other EIM functions such as metadata, master data, and content management. A synchronous and coordinated approach must be taken so management in all these areas support BI functions. Good BI relies on good data.
Implementation of a BI effort is an enormous undertaking and needs to be approached iteratively. Various BI maturity models exist that organizations can use to assess themselves in the BI continuum. A roadmap for development and implementation that aligns with the strategic goals of the organization should be created. The roadmap must set out priorities that are realistic and consistent with organizational capabilities.
Various data sources are used in BI analysis including internal primary and secondary data sources as well as external sources. The BI data lifecycle begins with identification of data sources and extraction and preparation of data for use in BI activities. Importantly, data schema and metadata must be developed before data are stored in the data warehouse. There are two predominate architecture models for BI that have different philosophies, design, and implementation. The Kimball Method is a bottom up approach and starts with the implementation of data marts to serve specific business unit needs. The Corporate Information Factory (CIF) model starts with a single, centralized enterprise-wide data warehouse that feeds data to satellite and dependent data marts.
Policies, procedures, and standards must be developed that ensure appropriate data maintenance, quality, and security of the data used in BI. Development of BI capability is a large undertaking. Organizations usually approach BI incrementally and can benchmark themselves against several BI maturity models. BI maturity models describe five steps of growth and development of BI technologies and processes along a continuum that goes from simple and complex. Data governance is an essential success factor in BI and depends upon the implementation of an accounting and reporting structure for oversight and management of BI data lifecycle.
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