Data Virtualization Pattern

2.1 Definitions

• **Data Virtualization**: A technology that allows data to be accessed and manipulated without regard to its physical location.
• **Data Federation**: The process of aggregating data from multiple sources into a single view.
• **Data Abstraction**: The simplification of data for easier access and analysis, often removing complexities associated with data sources.

3.1 Data Virtualization Workflow

graph TD;
    A[Identify Data Sources] --> B[Define Data Models];
    B --> C[Implement Data Abstraction Layer];
    C --> D[Create Access Layer];
    D --> E[Access Data via API];
            

3.2 Detailed Steps

1. Identify the data sources that need to be integrated.
2. Define data models that represent the structure and relationships of the data.
3. Implement a data abstraction layer to unify the data access.
4. Create an access layer, such as APIs, for applications to retrieve data.
5. Ensure performance and security measures are in place for data access.

4.1 Recommendations

• Use caching to improve performance for frequently accessed data.
• Standardize data formats across different sources to simplify integration.
• Implement security measures to protect sensitive data during access.
• Monitor performance and optimize queries to reduce latency.
• Document the data sources and their structures for easier maintenance.