The Laws and Limits of Data Science

Revised

 

Big Data is in its infancy and is opening the door to grand opportunities and challenges in Data Science.

We know that the data science tools and techniques being developed have enormous power. We also know that these tools and techniques break, but we just don’t know under what conditions.

In a keynote presentation for AnalyticsWeek Boston, Michael Brodie of MIT’s CSAIL outlines some “Laws and Limits of Data Science” and corresponding best practices designed to guide — as they did Tamr — the development of more reliable data science tools and techniques.

Click here to view full presentation