Data professionals an d their businesses face a host of challenges that demand a new approach. Pe rhaps the driving force is poor data quality. Or a disconnect from the lang uage the business uses. Or lack of a big picture. Maybe all.
\nRecogn ition is growing rapidly that traditional data design techniques are also i nadequate for the larger challenges of integrated digital business, includi ng highly-customized products, machine intelligence, and software ontologie s.
\nThe common factor? It’s what the company knows – bus iness knowledge. That knowledge isn’t limited to structured data &nda sh; it applies equally to so-called ‘unstructured data’. How di d they ever get disconnected?!
\nBusiness knowledge is more complicat ed – far richer – than most realize. It requires a blu eprint, which must be engineered conceptually.
\nIn short, you need t o know how to create a concept model. How do you form, define, name, and st ructure business concepts including both nouns and verbs? Using examples fr om real-life projects, this session shows you how.
\nLearning Objecti ves:
\n· &nbs p; What a concept model is and what it can be used for
\n· ; What goes into creating a concept model
\n· Why ambiguities arise a nd how they are resolved
\n· &n bsp; How to be business-effective about data design
\n· &n bsp; How to be business-driven about ontologies
\n DTSTART:20190320T104500 SUMMARY:Concept Engineering DTEND:20190320T114459 LOCATION: See Description END:VEVENT END:VCALENDAR