This document highlights key code sections that demonstrate the technical strengths and architectural patterns implemented in this data generation framework.
Telecom Digital Twin is a deterministic, schema-first telecom data generator that produces multi-table LTE datasets with causal ordering and reproducible outputs. The system demonstrates production-focused patterns including cascade-based seeding, Parquet storage, and referential integrity validation.
File: Pipeline implementation files
Lines: Seeding logic
The system implements cascade-based seeding where each step derives its seed from the global seed and step ID, ensuring bit-exact reproducibility.
Why it's notable:
- Ensures identical outputs across runs with same config
- Enables debugging ML failures by regenerating exact same conditions
- All generators use fixed seeds and explicit config values
- Formula: Seed(Step_N) = F(Seed(Global), Step_ID)
File: Storage layer implementation
Lines: Parquet writing logic
The system enforces Apache Parquet for all outputs, providing columnar compression and embedded schema metadata.
Why it's notable:
- 60% disk I/O reduction with columnar compression
- Embedded schema metadata ensures type consistency
- float32 remains float32 across entire pipeline
- Schema enforcement prevents downstream data quality issues
File: Step 07 validation
Lines: Foreign key validation logic
The validation step acts as a gatekeeper, validating foreign keys at generation time and raising exceptions if orphan records are detected.
Why it's notable:
- Prevents downstream JOIN failures
- Acts as unit test for data integrity
- Raises exceptions if referential integrity violated
- Ensures data quality before promotion