Common Mistakes Data Scientists Make With BIG DATA

What are the big mistakes that data scientists and big organisations often make when dealing with big data? What does engineering for data entail? If software engineering is about dealing with the problems of handling information, and it is, then what are the principles and learnings that we should take from decades of experience in dealing with information systems and how do we apply them to data?

In this episode Dave Farley writer and speaker on the topics of software engineering and continuous delivery explores how we could do a better job of dealing with data. Ideas like data pipelines and data mesh are becoming more common and more applicable as the scale of the data that we are dealing with grows. Managing the complexity in these activities, as in any other aspect of software engineering, is critical to success with data.


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