This talk was recorded at NDC Porto in Porto, Portugal. #ndcporto #ndcconferences #ai #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndcporto.com/ Subscribe to our YouTube channel and learn every day: /@NDC Follow our Social Media! https://www.facebook.com/ndcconferences https://twitter.com/NDC_Conferences https://www.instagram.com/ndc_conferences/ 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. By the end of this session, audience members will have a better understanding of the different ways a Data Science project can fail. They will be able to identify points of failure in the context of different case studies. They will feel motivated to share and learn from their failures and leave with actionable steps to reduce the risk of failing.
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