What is ‘DataOps’ and Why It Matters
In a New Stack Analysts podcast, Toph Whitmore, principal analyst for Blue Hill Research and author of the recent Blue Hill Research report “DataOps: The Collaborative Framework for Enterprise Data-Flow Orchestration”, explains DataOps as a disciplined approach to collaborative data management, that allows organizations to transform their business by using a holistic approach across the entire data product life cycle. Composable Analytics, Inc. is mentioned as one company committed to DataOps and creating the industry’s leading DataOps platform.
You can hear the full podcast here.
The Blue Hill Research report DataOps: The Collaborative Framework for Enterprise Data-Flow Orchestration explains:
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.