What is DataOps?
Learn how you can operationalize data integration for constant change and continuous delivery.
Defining your data universe with DataOps
The audacious, ambitious goal of teasing order out of the expanding chaos of modern data architectures requires a different approach to data integration. For decades, the automation of business analytics relied on predictable, well-defined data sets used in predictable, well-defined ways. But today’s data is messy. It’s unpredictable. Data producers and consumers find it painful to stay in sync.
What is DataOps?
DataOps is a set of practices and technologies that operationalize data management and integration to ensure resiliency and agility in the face of constant change. It helps you tease order and discipline out of the chaos and solve the big challenges to turning data into business value.
Manage data drift with DataOps
The challenge to the provisioning of continuous data is the unexpected, unannounced, and unending changes to data that constantly disrupt dataflow. That’s data drift, and it’s the reason why, sometimes when you go fast, things break. But when you take your time, you fall behind.
To manage data drift, you need to ensure continuous data flows by automatically identifying and handling data drift. DataOps operationalizes data management and integration, turning data chaos into a continuous, reliable flow of data to the people and systems that turn it into value.
Why DataOps? Why now?
3 Key Principles of DataOps
Bring DevOps to data
DataOps practices and technologies enable automation and monitoring across the full lifecycle of productivity from design to deployment and operations. Operationalize your data pipeline lifecycle with a single hub to manage data pipelines.
