How to Achieve a Single View of Critical Business Data with MDM

Organizations today are critically reliant on data. However, as enterprise applications accumulate—often through digital transformation initiatives, new product launches, or mergers and acquisitions—business-critical data becomes increasingly siloed.

As a result, organizations struggle to gain a complete view of customers, products, business partners, or other data domains scattered across legacy systems, cloud, databases, and spreadsheets—typically featuring unique ways of defining, modeling, and recording master data. Working with a network of vendors and suppliers, each with their own array of applications and data systems only complicates the picture further. All of which inhibit an organization’s ability to realize value from their data.

Master Data Management (MDM) allows organizations to consolidate data from multiple sources to create a single source of truth that provides a holistic view of enterprise-wide information. Join this webinar to discover how multi-domain MDM can eliminate the guesswork and uncertainty that results from data gaps and inconsistencies, paving the way for new, powerful insights through cross-domain intelligence.

Topics covered will include:

• Following a proven method to define and execute a data harmonization strategy that’s directly aligned with business objectives and outcomes
• Establishing a ‘contextually relevant’ golden record of consistent, valid, and accurate data across domains, applications,  and services
• Creating linked relationships between data domains and surfacing up analytics on different data types to provide context and enable more informed decision-making
• Ensuring that your data governance strategy both complements and supports your data harmonization and consolidation approach
• Managing all administrative, stewardship, and governance functions across domains from a single user interface
• Allowing various user personas to utilize data and collaborate effectively with structured operating models that are ‘fit for purpose