From the course: Executive Guide to Predictive Modeling Strategy at Scale
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Data and the data scientist
From the course: Executive Guide to Predictive Modeling Strategy at Scale
Data and the data scientist
- For both understandable and appropriate reasons, most enterprise data management and data governance is designed around the typical user of enterprise data. When I attend and speak at TDWI conferences, I sit in on the talks of expert enterprise data professionals, and in a variation of the 80/20 rule, they often describe that about 80% of users of data are content with existing tables, data sources, reports, and dashboards. The other 20% need some kind of extra attention. Most of these same experts put data scientists in the top 1 to 3% in terms of their need for custom requests and access to unusual data. It's worth pausing to ask why. As we've seen, they're often looking over long time horizons and should also be crossing departmental boundaries, pulling data from multiple silos. No standard, prebuilt monthly or quarterly report is going to do all of that. Frankly, if data scientists aren't at least considering some unstructured data, they probably aren't working hard enough to…
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