This provides an example of how to create an FDX API using Hasura DDN in a completed metadata driven approach.
It will automatically log data lineage and data provenance from DDN to the custom API endpoints at the field level. This enriched metadata provides valuable metadata that can be leveraged by PromptQL for analysis supporting multiple personas including the:
- CMO
- CRO
- CTO/CIO
- COO
All transformations are managed through a metadata driven transformation engine using the hasura-route-forge
Demonstrates how to create an the FDX /accounts routes, using
- a metadata transformation engine
- automatic field-level data lineage from DDN to FDX endpoint
- automatic field-level data provenance from DDN to FDX endpoint
- automatic connection to PromptQL for intelligent, GenAI-based data analysis
Just add the datasets generated by this DDN route plugin to a data_governance subgraph and ask it questions like:
- Summarize improvements in my FDX API from its inception.
- List and segment the financial institutions consuming the FDX API.
- Which financial institution segments adopt FDX API changes the quickest?
- Show me the most common transformation applied in FDX APIs.
- Show me FDX transformation that are no longer in use.
- Provide an explanation summarizing how account data is transformed and used in the FDX APIs.
- Find the most common data validation exceptions associated with an FDX API call and summarize the issue.
- Node
- Npm
- Typescript
- Postgres DB server or other database supported by TypeORM (MongoDB, Maria DB, SQL Server, MySQL,...)
- This is example is based on the data set from this repo @hasura/data-generator. If you modify the incoming query and transformers - you can adapt to your data. The data generator repo also demonstrates how to connect the route plugin and PromptQL into DDN.