Mastering Enterprise Data at Global Scale

Fortune 50 Quick-Service Restaurant

Context. A Fortune 50 quick-service restaurant operated at a scale where small inconsistencies become enormous problems — roughly 1.5 million employees, tens of thousands of locations, and a constantly changing menu, spread across international systems that had grown up semi-independently. Each region had its own way of representing the same essential things: who works where, what a location is, what a menu item costs and contains. Reconciling those representations into one trusted, centralized source — and keeping it current in a fast-moving business — was the work. This was not a greenfield build but an exercise in imposing order on a sprawling, living enterprise without slowing it down.

The Stakes. At this scale, master data is not a back-office concern — it is operational physics. A single inconsistency in how an employee, a location, or a menu item is represented multiplies across 35,000 locations and 1.5 million people, distorting payroll, reporting, and operations simultaneously. Centralized, trustworthy master data is what lets an organization this size act as one company rather than tens of thousands of improvising outlets. The cost of getting it wrong scales as fast as the business does.

The Challenge. Centralize and master enterprise data — employees, locations, and menu — for ~1.5 million employees and 35,000 locations, synchronizing across international systems in a rapidly changing environment, with the data quality and reliability that scale demands.

Our Approach.

• Led the MDM initiative on Microsoft SQL Server 2012/2014 with Master Data Services (MDS), centralizing employee, location, and comprehensive menu data into a single authoritative source.
• Connected international systems. We built a C# LDAP connector interface supporting multiple authentication methods to synchronize data across the organization's international systems, so one master could feed many regional environments.
• Built in data quality. We incorporated a standardized data-quality methodology that generated dynamic rules to enforce data integrity, and developed complex parsing for multi-formatted source files — because at this scale, quality has to be structural, not manual.
• Made delivery fault-tolerant and repeatable. We designed fault-tolerant multi-file incremental import/export, enhanced error handling and logging, and established deployment templates and standards — including managing SQL Server installations, environment configuration, and database migrations.

The Outcome. A centralized master-data backbone serving the enterprise at global scale, synchronized across international systems, with repeatable, fault-tolerant delivery and data quality enforced by design.

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What It Demonstrates. The ability to lead master data management at a scale where most approaches break — and to make data quality and fault tolerance structural properties of the system rather than aspirations bolted on afterward.

Capabilities. Master Data Services (MDS) · large-scale MDM · C# / LDAP integration · international synchronization · data quality · fault-tolerant ETL · deployment standardization.