As Accenture scaled to millions of predictive models, it required automation to ensure accuracy, prevent false alarms, and preserve trust. Teresa Tung, Ishmeet Grewal, and Jurgen Weichenberger explain how Accenture implemented a DevOps process for analytical models that’s akin to software development—guaranteeing analytics modeling at scale and even in noncloud environments at the edge.
This approach treats data scientists as developers. Failure is assumed, and exception handling and resiliency is central to the design. When a data scientist submits the model for deployment, she also specifies a quality condition and the associated behavior when that condition is broken. Automatic retraining can happen as a result of breaking that condition or through regularly scheduled intervals. Accenture refers to this capability as self-healing.
Teresa, Ishmeet, and Jurgen walk you through how to use the approach to include deep learning models and to govern workflow with risk models. Along the way, they outline the deployment of models into environments with little or no internet connectivity at the edge.
Teresa Tung is a managing director at Accenture, where she’s responsible for taking the best-of-breed next-generation software architecture solutions from industry, startups, and academia and evaluating their impact on Accenture’s clients through building experimental prototypes and delivering pioneering pilot engagements. Teresa leads R&D on platform architecture for the internet of things and works on real-time streaming analytics, semantic modeling, data virtualization, and infrastructure automation for Accenture’s Applied Intelligence Platform. Teresa is Accenture’s most prolific inventor with 170+ patent and applications. She holds a PhD in electrical engineering and computer science from the University of California, Berkeley.
Ishmeet Grewal is a senior research analyst at Accenture Labs, where he is the lead developer responsible for developing and prototyping a comprehensive strategy for automated analytics at scale. Ishmeet has traveled to 25 countries and likes to climb rocks in his free time.
Jürgen Weichenberger is a data science senior principal at Accenture Analytics, where he works within resources industries with interests in smart grids and power, digital plant engineering, and optimization for upstream industries and the water industry. Jürgen has over 15 years of experience in engineering consulting, data science, big data, and digital change. In his spare time, he enjoys spending time with his family and playing golf and tennis. Jürgen holds a master’s degree (with first-class honors) in applied computer science and bioinformatics from the University of Salzburg.
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