Today data modeling i s not only about working your way top-down from the business level through logical and physical models. More often than not, refactoring of some data is on many engineering cards. And metadata is the starting point. This pres entation walks through some scenarios, where graph technology and language processing are ideal for transforming metadata to new models. For example a n XMI-representation of a UML class model being given a makeover to become a property graph data model. We will demo the actual technology applied (ye s, some code and nice visualizations), based on practical experiences:
\ n\n Loading the metadata\n Discovering the structure and meaning contained in the metadata\n Filtering metadata\n Transformation / refactoring\n Generating a new data model graph and other NoSQL\n Maintaining lineage between old and new\n\nThe focus in data science is bottom-up from the data, building catalogs. Automation of metadata discover y and refactoring is even more important. Obviously raw data has value. But the structure and the meaning of the data comes from the metadata and are business critical. Welcome to a happy hour in the metadata lab!
\n DTSTART:20190320T120000 SUMMARY:Open House in the Metadata Science Lab DTEND:20190320T125959 LOCATION: See Description END:VEVENT END:VCALENDAR