By 2025 more than 465,000 petabytes of data will be collected on a daily basis across the globe, however, only a fraction of a percent of this data is considered to be useful for analysis and models. In order to locate the most useful attributes, feature engineering is a vital skill for all data scientists and analysts. But how does a data scientist decide how to engineer the right features? 

In this session, Brandon Southern explores:

• A framework for thinking like a business owner
• Developing a product and customer mindset
• Building new features that have saved millions of dollars in annual costs for top organizations