What is Data Federation
Data federation refers to the integration of data from multiple sources into a single, coherent view. This allows users to access and query data from various sources as if it were all stored in a single location. Data federation can be used to combine data from different systems, databases, applications, or organizations, and can be implemented using a variety of technologies and approaches.
There are several benefits to using data federation, including:
- Improved data access: Data federation allows users to access data from multiple sources without having to move or copy the data, which can be time-consuming and error-prone.
- Reduced data redundancy: By integrating data from multiple sources, data federation can help reduce the need for redundant copies of data, which can save storage space and reduce the risk of data inconsistencies.
- Enhanced data security: Data federation can be used to enforce security policies and controls across multiple data sources, helping to ensure that sensitive data is only accessed by authorized users.
- Increased data interoperability: Data federation can facilitate the exchange of data between different systems, applications, and organizations, making it easier to share and use data across different contexts.
Examples of data federation technologies include data virtualization, data warehousing, and enterprise data integration. These technologies can be used to create a unified view of data from various sources, allowing users to access and query the data as if it were all stored in a single location.
- Data Integration
- Federated Database System
- Data Virtualization
- Data Warehouse
- Data Lake
- Enterprise Data Management (EDM)
- Data Replication
- Data Marts
- Data Aggregation
- Master Data Management (MDM)