CDR Validator

Aimed at telecom analysts and data engineers, this tool validates CDR fields, formats, and calculations to ensure accurate billing and reporting.

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About This Tool

The CDR Validator is designed for telecom data teams who ingest large volumes of Call Detail Records for billing, compliance, and reporting. It applies a schema-driven approach to verify that each record contains required fields, correct data types, and valid values. Conceptually, it treats a CDR as a structured record and checks syntactic and semantic correctness before it enters downstream processes.
Core capabilities include per-record validation, computed charges, and cross-field checks. It supports fields such as call_id, origin, destination, start_time, duration_sec, rate_per_min, currency, and billed_amount, with options for custom mappings and regional rule templates.
Unique value lies in its flexible rule engine, support for batch and streaming processing, and export options for audit trails. Users can define severity levels, generate summaries, and integrate with data lakes or warehouses for end-to-end validation.
Use cases include pre-billing validation, QA reconciliation, and regulatory reporting. Advanced users can enable anomaly detection, currency conversion, and time-zone normalization; overall, the tool improves data quality and accelerates financial close.

How to Use

  1. Provide inputs: upload or point to a CDR dataset or stream.
  2. Configure schema or select template for field mappings and rules.
  3. Run validation to process records and generate results.
  4. Review results: identify errors, severities, and summaries.
  5. Export valid and invalid records for downstream processing.
How to use cdr validator

Frequently Asked Questions

Find Quick Answers

What input formats are supported?
The tool accepts CSV, JSON, and Parquet inputs, with optional schema templates to map fields. It supports batch and streaming ingestion for large datasets, and can adapt to regional field conventions via templates.
How are invalid records reported?
Invalid records are returned with structured error codes and severity levels. A summary includes total counts, top error types, and a breakdown by field. Export options support CSV/JSON for audit trails.
Can it handle large datasets?
Yes. It supports parallel processing, streaming ingestion, and chunked validation to scale with cluster resources. Memory usage remains controlled by batch size and streaming windows.
Is data security considered?
Yes. Validation can run in your environment or in a secure cloud setup. Data is not stored by default unless explicitly configured, and encryption options are available for in-transit and at-rest data.

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