Data Warehousing for Biomedical Informatics

Data Warehousing for Biomedical Informatics is a step-by-step how-to guide for designing and building an enterprise-wide data warehouse across a biomedical or healthcare institution, using a four-iteration lifecycle and standardized design pattern. It enables you to quickly implement a fully-scalable generic data architecture that supports your organization's clinical, operational, administrative, financial, and research data. By following the guidelines in this book, you will be able to successfully progress through the Alpha, Beta, and Gamma versions, plus fully implement your first production release in about a year.

Richard E. Biehl is an information technology consultant with 37 years of experience, specializing in logical and physical data architectures, quality management, and strategic planning for the application of information technology. His research interests include semantic interoperability in biomedical data and the integration of chaos and complexity theories into the systems engineering of healthcare. Dr. Biehl holds a PhD in applied management and decision science and an MS in educational change and technology innovation from Walden University, Minneapolis, Minnesota. He is a certified Six Sigma Black Belt (CSSBB) and a Software Quality Engineer (CSQE) by the American Society for Quality (ASQ), Milwaukee, Wisconsin. Dr. Biehl is a visiting instructor at the University of Central Florida (UCF), Orlando, Florida, in the College of Engineering and Computer Science (CECS), teaching quality and systems engineering in the Industrial Engineering and Management Systems (IEMS) Department.

Biomedical Data Warehousing. SECTION I ALPHA VERSION. Dimensional Data Modeling. Understanding Source Data. Biomedical Warehouse. Star Dimension Design Pattern. Loading Alpha Version. SECTION II BETA VERSION. Completing the Design. Data Sourcing. Generalizing ETL Workflows. ETL Reference Pipe. ETL Definition Pipe. ETL Fact Pipe. Finalizing Beta. SECTION III GAMMA VERSION. Finalizing ETL Workflows. Establishing Data Controls. Building out the Data. Delivering Data. Finalizing Gamma. SECTION IV RELEASE 1.0. Knowledge Synthesis. Data Governance.