[Data Quality Topic] Enabling data dogfooding: how to ensure data re-use
26 Sep 2024
Sonoma
Drug Response Prediction
![[Data Quality Topic] Enabling data dogfooding: how to ensure data re-use](https://cdn.asp.events/CLIENT_HubXchan_638DBA0F_0C6E_8D3C_A444829FC0C4B73E/sites/HubXChange/media/libraries/partners/Elsevier.png/fit-in/1500x9999/filters:no_upscale())
- How can we capture data with model building and reuse in mind?
- What are the best practices for mapping, harmonizing, and combining internal and external data sets for analytics and ML model training?
- What role do ontologies play in data harmonization?
- How can organizations assess the quality of both internal and external/public data and build trust in using this data for ML model training?
