What is Data Federation?
Data Federation is an architecture that allows organizations to connect and use data from multiple sources as though they were within a single data source. Data federation platforms access data from multiple distributed sources and create a virtualized data layer that consume the data via a single interface. The platform hides the complexities of data integration and enables organizations to quickly access and utilize the data.
How Data Federation Works
Data Federation uses a virtualized data layer that acts as an intermediary between applications and data sources. The layer acts as a single data source with a unified set of APIs. Whenever a request is made through the APIs, the virtualized layer translates the request into a language that the respective data source understands. This allows the organizations to work with multiple data sources and applications without requiring individual integration and maintenance for each source.
Why Data Federation is Important
Data Federation provides an efficient method of integrating data from diverse sources. The ability to access data from multiple sources in real-time without the need for data copies reduces data management overhead, and eliminates data silos. Organizations can build a unified data system at a lower cost than traditional approaches. Furthermore, it enables organizations to use all available data from all relevant sources to make more informed decisions.
The most important Data Federation use cases
Several use cases demonstrate the importance of data federation.
- Real-time reporting: Data federation enables businesses to access data in real-time without the need for data warehousing. It allows businesses to access, analyze and report on data from multiple sources at a single point.
- Customer 360: Data federation enables businesses to have a comprehensive view of their customers by integrating data from multiple sources. This allows businesses to personalize customer experiences and provide better customer service.
- Cloud migration: Data federation helps organizations transition to cloud-based infrastructure. It allows legacy applications to interact effectively with modern architectures and data sources.
Other technologies or terms that are closely related to Data Federation
Data virtualization: A technology that enables data storage, integration, and management by presenting data from different sources without requiring the technical details of data storage, modeling, or format. Data virtualization allows users to access and use data without worrying about the complexity of the data infrastructure.
Data integration: A process that combines data from different sources into a single, meaningful view. Data integration ensures that data is consistent, accurate and relevant across multiple systems.
Why Dremio users would be interested in Data Federation
Dremio users can benefit from data federation technology, which provides a cost-effective way of integrating data from multiple sources. Dremio's cloud-based data lakehouse simplifies data access, speed up data analysis, and eliminates data silos. It enables organizations to take advantage of all available data sources for better and more informed decisions.
Data federation enables Dremio to access data from cloud and on-premises data sources, including structured, semi-structured and unstructured data. Since Dremio caches data in-memory, it enables faster queries and data exploration. Dremio users can connect to data sources such as Hadoop, AWS S3, NoSQL databases, and relational databases without the need to build data pipelines, data lake storage, or ETL scripts.
