Description
The nature of the field of Data Science encourages trial and error, but we can do a better job of destigmatizing failure and learn from our collective experiences. Join me as I take us on an adventure to find the beasts i.e. the different ways Data Science projects can fail. I will be talking about 4 major reasons for failure (data, infrastructure, implementation, and culture), their different aspects, and supplementing it with my experiences and case studies. I will also share how to control these beasts and recommend actions to be taken to ensure a successful end-to-end Data Science project.