Uploaded April 2026 | Updated September 2026, 1 week ago
Following the definition of our data model, we will try to understand the critical per-requisites for successful entity resolution: Profiling and Mapping. This session highlights how profiling analyses source data quality and structure to enable AI-driven auto-mapping, which efficiently aligns source fields with defined MDM attributes. We also discuss the value of flexible, free-form modelling, which allows for on-the-fly schema adjustments as business requirements evolve. This workflow concludes with the essential publishing step—committing both the model and operational data to the database to prepare the system for matching—before moving into a live application demonstration.
Following the definition of our data model, we will try to understand the critical per-requisites for successful entity resolution: Profiling and Mapping. This session highlights how profiling analyses source data quality and structure to enable AI-driven auto-mapping, which efficiently aligns source fields with defined MDM attributes. We also discuss the value of flexible, free-form modelling, which allows for on-the-fly schema adjustments as business requirements evolve. This workflow concludes with the essential publishing step—committing both the model and operational data to the database to prepare the system for matching—before moving into a live application demonstration.
