Abstract: Agile Data Science 2.0 (O'Reilly 2017) defines a methodology and a software stack with which to apply the methods. *The methodology* seeks to deliver data products in short sprints by going meta and putting the focus on the applied research process itself. *The stack* is but an example of one meeting the requirements that it be utterly scalable and utterly efficient in use by application developers as well as data engineers. This talk will cover the full lifecycle of large data application development and how to use lessons from agile software engineering to do data science.
Bio: Russell Jurney is principal consultant at Data Syndrome, a product analytics consultancy dedicated to advancing the adoption of the development methodology Agile Data Science. He has worked as a data scientist building analytics products for over a decade, starting in interactive web visualization and then moving towards full-stack data products, machine learning and artificial intelligence at companies such as Ning, LinkedIn, Hortonworks and Relato. He is a self taught visualization software engineer, data engineer, data scientist, writer and most recently, he's becoming a teacher.
Author of Agile Data Science & Big Data for Chimps and Principal Consultant at Data Syndrome