Integrating Data

Overcome the challenges, appreciate the varieties, and apply the process of data integration.

Learn all about data integration and become a data integration hero instead of following the masses and running in the opposite direction at the mere mention of the word “integration”. Understand why organizations avoid data integration and often wind up with spider web environments containing siloed applications instead of an enterprise database which excites analysts and data scientists. Distinguish the different types of integration: database, attribute, key, index, encoding, measurement, format, definition, KPI, calculations, summarization, selection criteria, data exclusion, lineage, and timing. Apply identification, equivocation, and physical conversion levels of integration for both structured and textual data. Leverage deidentification, proximity analysis, alternate spelling, stop word resolution, homographic resolution, stemming, taxonomical resolution, inline contextualization, classification, and acronym resolution. Learn how to combine structured and textual data in the context of three levels of interaction. Follow the steps of scope, model, and map in integrating structured data. Follow the steps of scope, connect taxonomies, ingest raw text, and determine analytical processes in integrating textual data. Apply integration best practices, including identifying integration roles, developing a reusable data integration process, and documenting the integration benefits. Compare taxonomies with data models. Know how data integration helps data science.

To reinforce all of the concepts within the book, we include a detailed case study on data integration.

About Bill
Bill Inmon, the "father of the data warehouse," has written 60 books published in nine languages. ComputerWorld named Bill one of the ten most influential people in the history of the computer profession. Bill's latest adventure is the building of technology known as textual disambiguation.

About Patty
Patty Haines is a senior advisor and data practitioner, who provides expertise in managing and integrating data to ensure data is transformed and available to provide value to the business community. She writes data integration articles and judges Data Warehouse Best Practice Awards.

About Dave
David Rapien is an Associate Professor - Educator of Information Systems and Business Analytics at the University of Cincinnati's Lindner College of Business. Along with teaching for over 25 years, Dave has developed and managed data integration systems in the Sports Management, Medical, Insurance, Banking, Legal, Horse Racing, and School Administration industries. David owes his success to his wife, Laura, and his four children for their constant support, and to his dad, for teaching him how to explain complex ideas in simple terms.