Do you think it makes more sense to apply semantics when data is generated, or further down the data/analytics pipeline?
At data generation43%
Further down the pipeline54%
I don't know, but curious what others think3%
95 PARTICIPANTS
Director of Data in Healthcare and Biotech, 10,001+ employees
I think the approach varies depending on the nature of the data, such as whether it is structured or unstructured, and the quantity of data. In the healthcare domain where I work, I think performing semantic redefinition is most effective later in the pipeline. I would be concerned about performance if it were done upfront, especially given the terabytes of data we receive daily, much of which is non-discrete and unstructured. I also appreciate the flexibility to modify the semantic model later in the pipeline without the need to regenerate data.Content you might like
Analytics developers24%
Business analysts35%
Business consumers38%
Data analysts52%
Data engineers31%
Data scientists29%
Data stewards12%
Database administrators (DBAs)13%
Integration architects9%
ML and AI engineers20%
Elsewhere1%
Nowhere, we aren't adding new GenAI capabilities2%
86 PARTICIPANTS
Physical Access Control29%
Regulatory & Compliance60%
Maintenance & Updates10%
Other1%
91 PARTICIPANTS
Community User in Software, 11 - 50 employees
organized a virtual escape room via https://www.puzzlebreak.us/ - even though his team lost it was a fun subtitue for just a "virtual happy hour"
SEO in IT Services, 11 - 50 employees
yes