How To Lay The Groundwork For Data Science Adoption In The Enterprise
Data science is hard. It's a lot harder than it looks, and it's not just about building models. In fact, building those models is actually one of the least important parts of data science. Successful teams focus on the outcomes they want to achieve, from both a business perspective and a technical perspective. They also focus on building an environment (and culture) where everyone can talk openly about what's working, what isn't working—and how we can improve things for everyone involved in our company's data science initiatives. Understand Business Outcomes Data science is a powerful tool, but it can only be as good as the insights it generates. The most important step to ensure that data science delivers on its potential is therefore to identify the business outcomes that are most relevant for your organization and make sure that these are reflected in every data science project you take on. A business out...