Fragmented Customer Repositories
Each regional business unit maintained its own version of customer data, often governed by local processes without a unified data policy. This led to duplication, inconsistency, and a lack of standardization.
Finance
Boomi
Master Data Management
Each regional business unit maintained its own version of customer data, often governed by local processes without a unified data policy. This led to duplication, inconsistency, and a lack of standardization.
Salesforce Sales Cloud was the primary CRM platform, while SAP CRM and legacy systems were still in use across certain business units. Seamless integration across these disparate systems was required to unify customer records.
Customer data required significant cleansing and validation before consolidation. Inconsistent validation rules and synchronisation gaps across systems increased the complexity of building a reliable golden record.
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Explore our Boomi ExpertiseNeosAlpha initiated the program with a comprehensive data profiling exercise to assess inconsistencies, duplication patterns, and quality gaps across source systems. This provided clear visibility into the scale of cleansing and transformation required.
A structured customer data model was designed within Boomi Master Data Hub to define standardised attributes, validation rules, and governance structures for enterprise-wide adoption.
Customer data from Salesforce, SAP CRM, and legacy systems was integrated into Boomi MDH using its native connectors and transformation capabilities. Data were extracted, standardized, and loaded into the hub in a controlled, validated manner.
Matching and survivorship rules were configured within Boomi MDH to identify duplicates and generate golden records. Records requiring manual intervention were routed to quarantine for review by data stewards, ensuring controlled governance and accuracy.
The organisation established a unified customer master repository, enabling a complete and consistent view of each customer across business units.
Enhanced matching and validation mechanisms significantly reduced duplication and inconsistencies across systems.
Automation of integration and governance processes reduced the time and effort required to manage customer data.
With accurate and consolidated data, the business was able to deliver more targeted and customised value propositions to customers.
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