Customer 360

Customer 360 Data Engineering

Customer 360 programs require integrating customer data from dozens of source systems — each with its own schema, format, and business rules. DE Copilot automates the metadata translation work that makes these programs slow and error-prone.

How DE Copilot Accelerates Customer 360 Delivery

From source system mappings to governed Snowflake customer data models — with full traceability and human review at every step.

Multi-Source Metadata Normalization

Normalize customer data mappings from CRM, ERP, billing, and transactional systems into a single Canonical Metadata Model — one source of truth for the entire C360 data model.

Customer Data Model Generation

Generate Snowflake DDL for customer entity tables, relationship tables, and aggregation layers — directly from the normalized metadata model.

Identity Resolution Mapping

Surface customer identifier mappings, key resolution logic, and deduplication rules from STTM metadata — flagging ambiguous identity logic for SME review.

Customer Data Quality Rules

Generate completeness, uniqueness, and referential integrity checks for customer data — ensuring the C360 model meets data quality standards before deployment.

Cross-System Lineage

Trace every customer attribute back to its source system, transformation logic, and business rule — providing complete lineage for compliance and audit purposes.

Governed Delivery

All C360 artifacts pass through human review before deployment. Engineers validate customer data logic, approve transformations, and sign off on the delivery package.

Retail & Financial Services Experience

Why Customer 360 Programs Stall

Customer data from dozens of source systems arrives in different formats, with different identifiers, and with undocumented transformation assumptions.

Manual STTM translation for C360 programs takes months — and produces inconsistent data models that diverge from the original business requirements.

Data quality issues in customer data are discovered in production, not in development — because DQ rules are applied inconsistently across source systems.

DE Copilot normalizes all source system mappings into one metadata model, generates consistent artifacts, and enforces DQ rules before the data reaches the C360 layer.

Accelerate your Customer 360 program.

DE Copilot|Metadata Engineering

Built by

Amit Kumar Singh

Lead Data Engineer · Founder, DE Copilot · Enterprise AI & Metadata Engineering

15+ Years Enterprise Data EngineeringAvailable for SpeakingTechnical AuthorAI Hackathon Judge

dataengineeringcopilot.com  ·  © 2026

Personal project focused on metadata-driven data engineering. All examples, datasets, mappings, and screenshots are synthetic and provided for demonstration purposes only. No employer, client, or proprietary information is used.