Analysis on Dirty Data Survey |
Introduction
We're conducting research on industrial perspectives and practices on managing, analyzing, and serving “dirty” data. Dirtiness is broadly defined as any type of corruption that can negatively affect subsequent analysis. We hope to publish these results to help the research community bridge the gap between data cleaning theory and practice. These results will also inform the design of a new open-source data cleaning platform (sampleclean.org).
The survey should take about 15 minutes, and your responses are completely anonymous. If you are willing to allow us to follow-up with you through email, please provide your email address. We will not reveal or publish your email address. If you have any questions about the survey, please email us: sanjay@eecs.berkeley.edu dhaas@cs.berkeley.edu ewu@cs.columbia.edu We really appreciate your input!
The survey should take about 15 minutes, and your responses are completely anonymous. If you are willing to allow us to follow-up with you through email, please provide your email address. We will not reveal or publish your email address. If you have any questions about the survey, please email us: sanjay@eecs.berkeley.edu dhaas@cs.berkeley.edu ewu@cs.columbia.edu We really appreciate your input!