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Understanding data services
Data services bring more business value to data so it can be implemented as part of cloud-native applications—an integral component of open hybrid cloud IT strategies.
Data services (or Data-as-a-Service) are collections of small, independent, and loosely coupled functions that enhance, organize, share, or calculate information collected and saved in data storage volumes. Data services amplify traditional data by improving its resiliency, availability, and validity, as well as adding characteristics to data that it doesn't already have natively—like metadata.
Data services are self-contained units of software functions that give data characteristics it doesn't already have. Data services can make data more available, resilient, and comprehensible, which makes data more useful to users and programs.
Data service functions turn inputs into outputs. The inputs are varied sets of raw data—data that hasn’t been processed for a specific purpose—configured in its native format and saved in physical, virtual, or cloud-based storage volumes. The outputs are usually:
- Organizational: The consolidation, batching, and structure of data, usually pulled from structured (databases), semi-structured (data warehouses), or unstructured (data lakes) sources.
- Transferable: The movement of data from their place of origin across a network to an end point, like an application or platform.
- Procedural: The processing of data, usually as part of data modeling, analytics, or artificial intelligence/machine learning (AI/ML) software.
Without data services that help developers and data scientists collaborate as data moves between systems, cloud-native application development is impossible. Multiple code commits that use the same data can extend build times, but a data service like Red Hat® OpenShift® Container Storage can reduce time dependencies on concurrent builds.
The Massachusetts Open Cloud (MOC) uses data services. The MOC is a nonprofit initiative of universities, government organizations, and businesses. It was formed to develop a common, cloud-based infrastructure for businesses, governments, and nonprofits to analyze big data. MOC used Red Hat Ceph Storage—a software-defined storage service—to organize and share large amounts of data with multiple entities running custom data analytics platforms.
Because our data services not only work well with every data storage provider, but our data services are built to compliment cloud-native application development.
So use any datacenter or cloud you want, and start implementing all that data into your ever-evolving cloud-native apps. With our data services, your enterprise’s old data can be enhanced and streamed right into your cloud-native apps to reveal important information that may solve tomorrow’s biggest challenges.
Software-defined storage for container environments.