Domino Data Science Blog

Containerization is a key technology that accelerates the adoption and impact of data science amongst numerous companies in the world. An experiment’s state (data, code, results, package versions, parameters, etc.) at any point in time can be captured as a whole in a lightweight container and deployed on customers’ on-premise infrastructure and/or elastic compute infrastructures such as the cloud. This means data science experiments are easy and fast to reproduce, and data science teams can build on the prior work of others, which ultimately helps them drive the next level of innovation.

As organizations increasingly strive to become model-driven, they recognize the necessity of a data science platform. According to a recent survey report, “Key Factors on the Journey to Become Model-Driven”, 86% of model-driven companies differentiate themselves by using a data science platform. And yet the question of whether to build or buy still remains.