"I've built a model -- now what?"
Developing a predictive model is only one part of a larger journey. Data scientists have to access and transform data, and engineer features, before exploratory modeling happens. A model doesn't do anything until it's applied to data, productionised and deployed.
3 Things to Learn About:
- How to uplevel your existing analytics stack with a collaborative environment that supports the latest open source languages and libraries.
- How to get better use of your core data management investments while opening up new supported tools for data science.
- How to expand data science outside of silo’d environments and enable self-service data science access.
