My takeaways from A Practical Introduction To Data Science at NDC by @markawest
Data Science is a combination of computer science, machine learning and traditional research from match statistics . It follows the scientific process: Hyptothesis and analysis. Question -> Data -> Exploration & analysis (which is about 80% of the work) -> modelling -> interpretation ("what insight am I learning from this model?") -> communication (storytelling) -> result. A successful data science team needs a wide range of competences: Whereas a data scientist uses models to try to read meaning out of the data at hand, it has generally very little experience and knowledge about operationalizing the model - putting it into production for use in systems. A data engineer deals with data integration, building data driven platforms and operationalize models. A visualization expert can be good at storytelling and provide insight. Then, there's a process owner that deals with project management and communication. Artif