DataOps: The Collaborative Framework for Enterprise Data-Flow Orchestration

DataOps is an enterprise collaboration framework that aligns data-management objectives with data-consumption ideals to maximize data-derived value. DataOps “explodes” the information supply chain to create a data production line optimized for efficiency, speed, and monetization.

Borrowing from production optimization models and DevOps theory, DataOps’ successful adoption requires adherence to three key principles:

- Global Enterprise Data View: Define data journeys from source to action to value delivered, and measure performance across the entire system.
- Collaborative Thinking: Structure organizational behavior around the ideal data-journey model to maximize data-derived value and foster collaboration between data managers and data consumers.
- Get in Front of Data: Decentralize, then empower self-service data services and analytics throughout the organization.

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About Toph Whitmore

Toph Whitmore is a Blue Hill Research principal analyst covering the Big Data, analytics, marketing automation, and business operations technology spaces. His research interests include technology adoption criteria, data-driven decision-making in the enterprise, customer-journey analytics, and enterprise data-integration models. Before joining Blue Hill Research, Toph spent four years providing management consulting services to Microsoft, delivering strategic project management leadership. More recently, he served as a marketing executive with cloud infrastructure and Big Data software technology firms. A former journalist, Toph's writing has appeared in GigaOM, DevOps Angle, and The Huffington Post, among other media. Toph resides in North Vancouver, British Columbia, Canada, where he is active in the local tech startup community as an angel investor and corporate advisor.
Posted on January 13, 2017 by Toph Whitmore

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