Enterprise MDM & Data Governance for a Multinational Group
A multinational group with 12 subsidiaries across Europe and Latin America had no single source of truth for customer, material, or vendor master data. ATMA Technology designed and implemented an enterprise-wide MDM framework that unified all data domains and reduced month-end close from 5 days to 6 hours.
Business Challenge
12 subsidiaries, 4 ERPs, zero shared data model
The group had grown through acquisition over 15 years, inheriting a fragmented data landscape with each subsidiary maintaining its own master data in isolation. The same customer could exist under 40 different codes across the group, making consolidated reporting, credit risk management, and regulatory compliance practically impossible without massive manual effort.
The CFO had mandated a 3-day month-end close target. With the existing data landscape, the finance team was spending 5 full days on reconciliation alone before any actual close activities could begin.
ATMA's Approach
Governance model first, technology second
Data Domain Assessment
Profiled all data domains across 12 subsidiaries using automated data quality tooling. Identified 47 distinct data quality dimensions, established baseline metrics, and prioritised remediation by business impact. Defined a data ownership RACI across all entities.
MDM Architecture & Governance Model
Designed a hub-and-spoke MDM architecture with SAP MDG as the central governance hub. Defined data stewardship roles, workflow approval chains, and data quality KPIs. Established a Data Governance Council with representation from all 12 subsidiaries.
Automated Data Pipelines
Built Python-based data pipelines with Apache Airflow orchestration to automate data ingestion, validation, deduplication, and distribution. Implemented real-time data quality monitoring with automated alerting for threshold breaches.
Reporting & Continuous Improvement
Deployed Power BI governance dashboards giving data stewards real-time visibility into data quality scores by domain and entity. Established a continuous improvement cycle with monthly data quality reviews and quarterly governance board reporting.
Technical Architecture
SAP MDG hub with cloud-native data pipelines
SAP MDG serves as the central governance hub for all master data domains. Automated pipelines built with Python and Apache Airflow handle ingestion, validation, and distribution to all 12 subsidiary systems in near real-time.
Snowflake provides the analytical layer, with dbt transformations feeding Power BI dashboards that give the Data Governance Council real-time visibility into data quality scores across all domains and entities.
Technology Stack
"We had been living with data chaos for 15 years. ATMA Technology didn't just implement a tool - they built a governance culture across 12 organisations that had never agreed on anything before. Month-end close is now 6 hours. That alone has transformed how our finance team operates."
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