Practical articles on AI, Data Engineering, Metadata-Driven Development, Snowflake, Enterprise Architecture, and Modern Data Platforms.
Real-world engineering lessons, technical deep dives, and implementation guides by Amit Singh · 11 articles published
Showing 6 articles tagged #STTM
A practical pattern for moving from source-to-target mappings and business definitions to a semantic Customer 360 model that business users can query safely.
Data engineering teams spend countless hours on repetitive, metadata-driven work. The STTM already contains everything needed to build engineering deliverables. The challenge is that teams repeatedly translate that metadata into different formats.
Most people see DE Copilot as a code generation tool. The real engine sits in the middle - a metadata abstraction layer that transforms enterprise STTMs into unlimited engineering deliverables.
Can a metadata-driven engine understand and generate engineering artifacts from large, complex STTM documents without custom coding for every project? Here is what happened when we put it to the test.
Source-to-Target Mappings sit at the center of every data pipeline, yet they are treated as throwaway documents. Here is why that needs to change - and what becomes possible when it does.
The promise of AI-assisted data engineering is compelling. But can a language model actually read a Source-to-Target Mapping and produce artifacts that are production-ready? Here is an honest look at what works, what does not, and what the path forward looks like.