In data science experimentation is vital, the more we can experiment, the more we can learn. However quick iteration isn't sufficient we also need to be able to easily promote these experiments to production to deliver value. This requires all the stability and reliability of any production system. John will discuss building platforms that treat iteration as a first class consideration, the role of open source libraries, and balancing trade-offs.