Integrated Decision-Making in Databricks: How to Foster Collaboration via a Single Platform

In the landscape of custom decision-support tools using commercial platforms, developers often face the challenge of navigating across multiple platforms tailored to specific analytics methodologies. As a result, optimization, ML, and simulation models tend to live in their preferred platform based on a natural division, which makes it challenging for users to interpret and reconcile the recommendations from these various models. 

Gurobi’s available APIs in multiple programming languages provide a great opportunity to integrate optimization solutions in a variety of modern data warehouses and cloud architectures. In this talk, we demonstrate the benefits of Databricks through a network optimization example. Using this approach, we can streamline forecasting, optimization, and scenario analysis in a unifying platform, which can help foster better collaboration across teams with various analytics capabilities, and ultimately accelerate time-to-value in complex decision-making.