Data integration projects can be time consuming, expensive and difficult to manage. Traditional data integration methods require point to point mapping of source and target systems. This effort typically requires a team of both business SMEs and technology professionals. These mappings are time consuming to create and code and errors in the ETL (Extract, Transform, and Load) process require iterative cycles through the process.
A powerful new approach to addressing this challenge involves using semantic web technology as the glue to manage integration and dramatically simplify the process. This includes:
- Using semantic models to describe data in standard business terms (e.g., FIBO, CDISC, existing enterprise model etc.)
- Mapping source and target data to the semantic model instead of directly from source to target
- Combining these maps as needed to create end-to-end semantic descriptions of ETL jobs
- Automatically generating ETL code from the semantic descriptions for leading ETL tools
Check out this short video to learn more