Deb is a motivated, passionate, and impact-focused senior consultant at Thorogood Associates, a Databricks partner since 2018. She has extensive experience leading end-to-end engagements for data engineering & data science implementation projects using Databricks. She has led engagements to deliver rapid experimentation & exploratory data science outputs to senior CPG executives for strategic decision-making, leveraging Databricks for data engineering and data science (she co-presented on this use case with Databricks last fall). Deb is currently engaged with Databricks customers to operationalize data science use cases spanning eCommerce, supply chain & manufacturing, and financial systems using MLOps. Most recently, she has been leading Thorogood’s MLOps practice, working on projects to help large enterprise organizations define their technical standards and best practices around the people, processes, and tools needed to successfully deliver MLOps.
May 26, 2021 12:05 PM PT
In this presentation, drawing upon Thorogood’s experience with a customer’s global Data & Analytics division as their MLOps delivery partner, we share important learnings and takeaways from delivering productionized ML solutions and shaping MLOps best practices and organizational standards needed to be successful.
We open by providing high-level context & answering key questions such as “What is MLOps exactly?” & “What are the benefits of establishing MLOps Standards?”
The subsequent presentation focuses on our learnings & best practices. We start by discussing common challenges when refactoring experimentation use-cases & how to best get ahead of these issues in a global organization. We then outline an Engagement Model for MLOps addressing: People, Processes, and Tools. ‘Processes’ highlights how to manage the often siloed data science use case demand pipeline for MLOps & documentation to facilitate seamless integration with an MLOps framework. ‘People’ provides context around the appropriate team structures & roles to be involved in an MLOps initiative. ‘Tools’ addresses key requirements of tools used for MLOps, considering the match of services to use-cases.