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DataOps Engineer Will Be the Sexiest Job in Analytics

In this contributed article, Christopher Bergh, a Founder and Head Chef at DataKitchen, discusses how DataOps, is transforming the roles on the data analytics team. DataOps is a better way to develop and deliver analytics. It applies Agile development, DevOps and lean manufacturing principles to data analytics producing a transformation in data-driven decision making.

Model Risk Management in the Age of AI

In this contributed article, Stu Bailey, Co-Founder and Chief AI Architect of ModelOp, discusses how financial services companies can easily validate multiple AI/ML models and reduce ML project costs by 30% through automation. ModelOps refers to the process of enabling data scientists, data engineers, and IT operations teams to collaborate and scale models across an organization. This drives business value by getting models into production faster and with greater visibility, accountability and control.