Data fabric architecture approach: ways, data drives the future
All modern business processes are based on data. More and more businesses have become data-driven and build their data architecture. It ensures that data is collected, stored, and used based on the needs of the definite relevant user as well as corresponding workflows.
One of the approaches, that helps to control data, is data fabric. It is an architectural approach that simplifies data access within an organization. Whether it is business users, data engineers, or business analysts, a data fabric delivers the exact data needed. In addition, it facilitates self-service data consumption.
Key elements of a data fabric architecture
- Augmented knowledge graph. Provides a common business understanding of the data and automation.
- Intelligent integration. Types of integration to work with data (extract, stream, virtualize and transform, etc.) based on data policies. Maximizing performance and minimizing storage and costs.
- Self-service data usage. A platform (marketplace) where users find, collaborate, and access high-quality specific data.
- Unified data lifecycle. Lifecycle management that provides composing, building, testing, and deploying the various capabilities of a data fabric architecture.
- AI and hybrid clouds. AI architecture built for hybrid cloud environments.