Data subsystems are typically designed to support specific line of business processes, but as more organizations begin to employ enterprise-wide tools to support cross functional processes, what were tolerable data variations and discrepancies wreak havoc on cross-functional success.
When there is an intent to use data from multiple sources for cross-functional activities often embodied within ERP, CRM, SCM, procurement, A/P or data warehousing systems for reporting, there is a corresponding need for a platform to ensure that data instances created in one areas of the business are suitable for uses in other areas of the business.
In this webinar, we review how organizations can employ master data management (MDM) methods and techniques to resolve structural and semantic differences appearing from different data sources to reduce inconsistency and improve enterprise data quality across cross-functional departments.
The Webinar will walk you through:
The value proposition and business case for data quality improvement
Variation and inconsistency in originating source systems and the remedies to resolve them
Opportunities for cross-functional collaboration on data quality improvement programs
Using master data management methods to harmonize variant structures and semantics
Dollar Value savings from ensuring optimal enterprise data quality
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