In this module, you will be able to define the foundational terms used in discussing and building healthcare data models. You'll be able to describe the conceptual model showing how data flows from operations to analysis. You will compare and contrast common data models used in healthcare data systems. You will also be able to identify common measures used in healthcare data analysis.

In this module, you'll be able to describe the Star Schema Data Model, distinguish it from the hierarchical and relational model, list some pros and cons and explain situations in which it could be appropriately used. You should also recognize when another type of data model might be better suited to a particular use case.

In this module, you'll be able to explain how information is stored in data models and how we assemble relevant information to analyze an interesting problem that can improve our healthcare systems. We'll review how we normalize data and how that facilitates analysis. We'll go on to discuss how to bring together information from different sources and across various functional systems. We will also consider how to measure it accurately.

In this module, you will be able to examine the data that goes into these models and explain how we work with the information that comes from the practice and business of medicine. We will transition from raising the data quality to focusing on finding and correcting data errors by validation and verification. You will also be able to describe several ways data is checked to eliminate errors and improve data quality.