Part 3/10:
Diversity: Different database systems such as SQL Server and Oracle, with varying schema and scripting conventions.
Age: Object code dating back decades, often with inconsistent naming and hardcoded values.
Interdependencies: Complex relationships and data lineage that require meticulous tracing.
AI-Driven Solution: Concept and Components
To streamline this laborious process, the team developed a sophisticated AI-enabled framework that ingests, contextualizes, and simplifies legacy SQL objects for data engineers.
Core Pillars of the Approach
Contextual Layer: Organizes and indexes all SQL objects, making them searchable and interpretable.
Retrieval Mechanism: Efficiently fetches relevant objects and their metadata based on user prompts.