Presented by Ronald G. Ross
What messes up your data so badly? Why is data pollution so common? Are business users and data professionals spending way too much time chasing phantoms around in your data?
Poor models make data corruption inevitable. It’s time to rethink old habits and pursue approaches better suited for the knowledge economy. The solution is concept models, which base their structure on language and communication. This presentation surveys the three fundamental techniques of concept models: classification, categorization, and verb concepts. It shows you how to capture the business meaning of data by creating a structured business vocabulary and common business language.
Whether your concern is Data Quality or consolidation, better data design, eliminating silos, preparing for Artificial Intelligence (AI) and Machine Learning (ML) for text, or simply communicating business knowledge more effectively, you need to know how to create a concept model. This presentation shows you how.
Getting at hidden knowledge in business people’s heads and creating shared understanding
Knowing how to avoid rampant type codes
Testing your model for clarity and precision
Escaping all technical bias and truly speaking ‘business’
Avoiding deep-seated ambiguity in all forms of business communication
Based on Ron’s newly released book: Business Knowledge Blueprints: Enabling Your Data to Speak the Language of the Business