Understanding the value of a data science workbench

A data science workbench is an environment to standardize the machine learning tools and practices of an organization, allowing for rapid onboarding and development of models and analytics. One critical machine learning engineering function is to support data science practitioners with tools that empower and accelerate their day-to-day activities.

In a data science team, the ability to rapidly test multiple approaches and techniques is paramount. Every day, new libraries and open source tools are created. It is common for a project to need more than a dozen libraries in order to test a new type of model. These multitudes of libraries, if not collated correctly, might cause bugs or incompatibilities in the model.

Data is at the center of a data science workflow. Having clean datasets available for developing and evaluating models is critical. With an abundance of huge datasets, specialized big data tooling is necessary to process...