Part 7/10:

• Time Savings: From 5-6 hours per object to just 30-40 minutes for large sets.

• Accuracy: Benchmarking against manual data engineer outputs revealed an accuracy of 85-93%, depending on object complexity.

• Efficiency Gains: Time spent on manual tracing reduced by approximately 96%, enabling faster migration and validation cycles.

Visualization and Impact Analysis

Generated outputs include:

• Hierarchical graph visualizations of data lineage.

• Impact analysis diagrams to assess downstream and upstream dependencies.

• Reconciliation sheets to verify and validate automated outputs.

Deployment and Data Governance

• Solutions are deployed on Azure Kubernetes Service (AKS), ensuring scalable and secure operation.