Building an Azure architecture optimized for your ML projects
Hygiene technologies leader Ecolab brings data science to production with Microsoft Azure and Iguazio
To provide vital predictive analytics capabilities, global hygiene technologies provider Ecolab turned to machine learning (ML) and data science to address risks before they happened. But getting a single model to production took more than 12 months.
To deal with complex issues related to operationalizing and scaling ML projects, and start doing this on a regular, repeatable basis, Ecolab turned to MLOps technology provider Iguazio to accelerate and improve their data science projects on Microsoft Azure without incurring exorbitant costs.
Prior to implementing this solution, model deployment times exceeded 12 months. Thanks to Iguazio and Microsoft Azure, by 2020, these had been reduced to between 30 and 90 days.
Read this case study to learn how this cutting-edge, cloud data science architecture was built and discover more of the tangible benefits Ecolab has seen.