Medicaid Benefits Data Collection. This data collection reflects Medicaid benefits covered in each state, limitations applied to those benefits, cost-sharing charges, and the reimbursement methodologies used for those benefits as of October 1, 2012.
Data Rationalization is a Managed Meta Data Environment (MME) enabled application which creates/extends an ontology for a domain into the structured data world, based on model objects stored in various models (of varying levels of detail, across model files and modeling tools) and other meta data.
Normalization usually means transforming the data you are working with to a common frame of reference. I can give you a good example of data normalization for one of the areas I work in a lot. It is a function called the Z-Score. What it does is allows you to convert and data that is a Normal Distribution into a frame of reference where the Mean is Zero and the variation is expressed in standard deviations. The reason that data is usually normalized is that it takes out the matter of scale in the data and allows as much as possible an âapples to applesâ comparison of data.