Data cleaning, or the work of making a dataset ready for analysis, is a key component of learning to use data well (in fact, the adage goes that 80% of the work of a data professional is data cleaning!). 

This workshop will approach data cleaning in two sections: 1) we will first discuss what motivates researchers to clean their data, that is, we will discuss some practical circumstances that require data cleaning, and 2) we will then compare tools for learning how to clean data, including applications, software, code languages and instructional pathways. Tools and resources discussed include: Open Refine, Tableau Prep, Python, MOOCs, and Free Code Camp. 

This workshop is a part of the “where to start” data workshop series. This means that the point of the session is not to deliver a step-by-step tutorial. Instead, we aim to help you to identify the best resources to begin a sustainable, practical journey to the form of data literacy that best suits your needs. Each workshop is a stand-alone experience, though they are offered in an intentional sequence.