Working with Messy Data

Abstract

Data, no matter how prepared, usually needs some refinement before it’s ready to use in your analysis. During this talk, you’ll hear about some approaches to exploring data, recognizing common data quality issues, and what can be done to address those issues. You’ll hear about some practical approaches you can use in every project, and about some cautionary tales about what to avoid or how your decisions can start to influence the results of a project.

Christopher Teixeira

Department Chief Engineer

My interests include using my skills for the public good and playing with baseball data.