CASE STUDIES
How we helped a leading Saudi telecommunications operator align its data architecture with national data governance standards.
CASE STUDIES
How we helped a leading Saudi telecommunications operator align its data architecture with national data governance standards.
Our data governance program brought enterprise architecture into line with Saudi Arabia’s National Data Management Office standards, closing compliance gaps early and giving every new system a governed foundation to build on.
The Client & Category
Our client is a leading telecommunications operator in Saudi Arabia, operating at national scale across consumer and enterprise markets.
As the Kingdom’s National Data Management Office introduced binding standards for data management and personal data protection, the operator needed to prove, and continuously maintain, compliance across a large and fast-evolving technology estate. That meant translating national regulatory requirements into concrete architecture decisions and closing the gap between existing systems and a defined target state, in a way that would hold up as new platforms and payment schemes were added.
The Solution
We acted as enterprise data architect, evaluating three control groups against the operator’s target-state architecture to validate regulatory compliance and pinpoint exactly where gaps existed.
We closed those gaps through targeted data architecture programs that translated national requirements into concrete, implementable design standards, and benchmarked the operator’s architecture maturity against two major international operators to give leadership an external reference point. A formal maturity assessment, run against a globally recognized data management framework and compared with global telecom-sector benchmarks, helped prioritize what to fix first. We also defined reusable data integration patterns and governance standards, including naming conventions and modern data-modeling guidelines, so new projects would launch compliant instead of retrofitting compliance later.
The Outcome
The operator’s systems now align with a single Enterprise Data Model, closing the regulatory gaps identified during assessment, while reusable architecture patterns catch redundancies and inconsistencies early, before they reach development. Standardized naming conventions, modern data-modeling guidelines, and a formal review process now apply across every new system, and closer alignment with national data governance standards has streamlined how new data initiatives get designed and approved.
