A data-driven enterprise maximizes the value of its data. Data management, architectures, and engineering are considered critical assets and priorities, and data-backed decisions with transparent measures of quality and confidence differentiate the business.
But how do enterprises emerging from technology and organization silos get there? While applications are tied to the business outcome, data in its raw form is tied to cost. So how do you make the business case and then execute the organizational and technology changes so that data becomes a first-class citizen?
Teresa Tung explains how to create a data-driven enterprise maturity model that spans technology and business requirements and walks you through use cases from the healthcare, oil and gas, and financial services industries that bring the model to life. The end state is not just an enterprise data platform but rather a platform of platforms needed so that your data platform interfaces with those of your partner ecosystem.
Teresa Tung is a managing director at Accenture Technology Labs, 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. Teresa holds a PhD in electrical engineering and computer science from the University of California, Berkeley.
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