Knowledge management for health data analytics

This chapter focuses on the necessity of putting data management layers in place before applying more advanced tools is possible. It discusses these processes within the framework of knowledge management (KM). KM is the academic discipline that studies and effects the transformation of data into information, and the application of that new information to create actionable knowledge. The chapter also discusses the state of analytics technologies that could then be applied and discuss the impact that it could have on healthcare in the United States. A cross-functional data governance model will help healthcare organizations harness value from their stored information. Data are often needed from multiple data sources, including laboratory values, unstructured text records of clinical findings, cost and quality information, and genetic data. Given the complexity and cost of traditional data warehouses, many organizations can use data lakes to expedite the process. Health organizations are capable of generating and collecting a large amount of data.