Bi Maturity Models Describe

Bi Maturity Models Describe

  

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!

Business Intelligence and Big Data

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.

 
In 1854, data visualization was used as a persuasion technique to convince city officials in London that cholera was due to contaminated water and not bad air, as was commonly thought. Over 160 years later, BI is becoming a powerful tool for infectious disease surveillance. Please view the posted video (it’s really good 

 

Steven Johnson: How the “ghost map” helped end a killer disease (10 minutes)

Author Steven Johnson takes us on a 10-minute tour of The Ghost Map, his book about a cholera outbreak in 1854 London and the impact it had on science, cities and modern society.

Click https://www.ted.com/talks/steven_johnson_tours_the_ghost_map?language=en (Links to an external site.) link to open resource.

 

 Visit the website http://healthmap.org (Links to an external site.) and learn how data visualization and data mining are being used to track and predict infectious disease outbreaks today.  Also https://coronavirus.jhu.edu/us-map (Links to an external site.) is an interesting resource as well.

·  Read the Harvard Business Review article at https://hbr.org/2014/09/how-cities-are-using-analytics-to-improve-public-health/ (Links to an external site.) on how cities are using analytics to improve public health. (It’s older but still good!)

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