Data discipline for a telecom operator

What we know about telecom data

Telecom data is one of the richest in the industry: voice CDR, data sessions, location, payments, app behaviour, network performance. And one of the most fragmented — across systems, teams, quality.

Without data discipline, even the best CDP / CVM / AI initiatives do not deliver ROI.

Our expertise:

Data quality framework. Per-domain metrics (completeness, accuracy, timeliness, consistency). Operating routine for continuous monitoring and improvement.

Master Data Management. Customer master, product master, dealer master, network asset master. Source of record per domain, golden record builder, distribution layer.

Identity resolution. Linking MSISDN, ICCID, account, app_user_id, passport — non-trivial due to multi-line, family plans, corporate.

Data governance. Stewardship per domain, data contracts, change management, audit.

Consent architecture. Not “a tick in a form” but a structured object with purpose taxonomy, enforcement layer, withdrawal mechanism.

Data partnerships. What and how can be shared with banks, retailers, government within the regulatory framework.

Where we help

Data Maturity Assessment — current state across 8 dimensions. 4 weeks.

MDM Programme — 12-18 months, build customer / product / dealer master.

Data Quality Routine — embed into weekly per-domain review.

Consent Framework Design — purpose taxonomy, registry, enforcement.

Data Strategy — 5-year roadmap of data capabilities.

What we bring

Experience of data programmes in emerging markets with specific regulatory constraints.

Understanding of telecom data semantics — not generic data engineering knowledge.

Bridge between business owners (CMO, CCO) and technical teams (CDO, data engineering).

Related

• /en/architecture/telecom-cdp-architecture/ — CDP
• /en/architecture/telecom-master-data-management/ — MDM
• /en/architecture/telecom-consent-architecture/ — consent
• /en/decisions/telecom-data-team-centralized-vs-federated/ — data team org