In practice, we’ve found that a combination of structured workflows and clear ownership makes a huge difference. For example, using tools like
Praxi AI has helped us centralize curation, automate categorization, and maintain consistent metadata across datasets, which really reduces errors and improves accessibility. In our organization, it’s not just IT or the data team alone—curation is shared across business units, data stewards, and analysts, so everyone understands the data’s context and relevance. Regular cleansing, annotation, and quality checks have become routine, and storing curated data in an organized, searchable catalog means we can actually trust and act on insights rather than chasing raw, unmanageable files.
