Failure in Data Science

Abstract:
There have been many talks about how to succeed as a data scientist. Yet, according to Gartner, most data science projects fail. So, let’s talk about failure in data science.

Every data scientist will encounter failure with their projects. But, why do these projects fail? And how can you respond to failures in a professional context? And what constitutes “failure”, anyway?

This talk will discuss these elements about failures with real-world examples to illustrate the concepts. Note that this will be shorter than usual so that there is ample time for discussion regarding the examples or to get feedback on your experiences with failure in data science.

Bio:
Dr Craig Savage has worked in a number of technical fields, including rocket science and bringing sight to the blind. He has experience in Credit Risk at NAB and ANZ, and is currently an independent consultant. His professional interests include data analysis, data visualisation and, more importantly, driving evidence-based decisions and actions.