Master data management (MDM) involves creating a single master record for each person, place, or thing in a business, from across internal and external data sources and applications. This information has been de-duplicated, reconciled and enriched, becoming a consistent, reliable source. Once created, this master data serves as a trusted view of business-critical data that can be managed and shared across the business to promote accurate reporting, reduce data errors, remove redundancy, and help workers make better-informed business decisions.
As a discipline, MDM relies heavily on the principles of data governance with the goal of creating a trusted and authoritative view of a company’s data. Data governance and MDM have become critical to successful business practices as organizations put increasing importance on data-driven decisions in today’s global marketplace —and as a growing number of systems contribute digital records of the people, places, and things that matter most to a business.
As a technology, MDM solutions automate how business-critical data is governed, managed, and shared throughout applications used by lines of business, brands, departments, and organizations. MDM applies data integration, reconciliation, enrichment, quality, and governance to create master records. Automation and artificial intelligence (AI) are used to identify, match, and merge data across the systems that hold it, and then the clean data is shared with the applications, systems, and analytics that need it. In merging records, MDM can also correct for inconsistencies in records, capture where the data came from, and create an audit trail of changes. Providing transparency within a trusted framework offers visibility into how each master record is created or modified.
Master data management creates a master record (also known as a “golden record” or “best version of the truth”) that contains the essential information upon which a business or organization relies. The master record contains what an organization needs to know about critical “things”—a customer, location, product, supplier, and so on—to facilitate a task or action such as a marketing campaign, a service call, or a sales conversation.
One easily understood type of master data is reference data. Reference data is a subset of master data. Some examples of reference data are:
MDM solutions comprise a broad range of data cleansing, transformation, and integration practices. As data sources are added to the system, MDM initiates processes to identify, collect, transform, and repair data. Once the data meets the quality thresholds, schemas and taxonomies are created to help maintain a high-quality master reference. Organizations using MDM enjoy peace of mind that data throughout the enterprise is accurate, up-to-date, and consistent.
The categories into which master data is classified are called domains. Common MDM domains include:
But you can also master more specific elements like account, patient, provider, beneficiary, contract, claims, projects, movie, character, airports, aircraft, vehicles, sites, and more. It all depends on the business challenges with which you want to align your data.
Having multiple sources of information is a widespread problem, especially in large organizations, and the associated costs can be very high. Because data changes over time, it’s easy for it to get out of sync and become fragmented, incomplete, inaccurate, and inconsistent. As it degrades, the people that use it lose trust in it. Consider the impact on a sales call if the account manager accesses customer information that is incomplete or inaccurate:
The wrong answer to any of these questions could put a new sale—or existing relationship—at risk. In this example, MDM would ensure that a trusted customer profile is created to eliminate such issues in a company’s data.
MDM addresses the challenges associated with disparate applications that create, capture, and access data across multiple systems, applications, and channels. This includes SAP, Marketo, Salesforce, DemandBase, web portals, shipping systems, invoicing systems, contract systems, and more. With a trusted source of reliable, current data, organizations can get a better view of their products and suppliers, drive customer engagement, and offer a consistent experience to employees as well as customers.
Other issues addressed by MDM include:
MDM is of particular interest to large, global organizations, organizations with highly distributed data across multiple systems, and organizations that have frequent or large-scale merger and acquisition activity. Acquiring another company creates wide-reaching data integration challenges that MDM is designed to mitigate. Thus, MDM can accelerate the time-to-value from an acquisition.
MDM also helps prevent disjointed customer experiences in companies with segmented product lines, multiple interaction points and channels, and distributed geographies. With MDM, companies gain confidence that the data they rely on remains trusted and authoritative.
By providing one point of reference for critical business information, MDM eliminates costly redundancies that occur when organizations rely upon multiple, conflicting sources of information. For example, MDM can ensure that when customer contact information changes, the organization will not attempt sales or marketing outreach using both the old and new information.
Common business initiatives addressed by MDM include:
Curious about what master data management (MDM) brings to an end-to-end data strategy? Our webinar series covers everything from MDM basics to the difference between MDM and data quality.
2020 Gartner Magic Quadrant for Master Data Management Solutions: For the fourth straight time, Informatica has been named a Leader in the 2020 Gartner Magic Quadrant for Master Data Management Solutions.
Intelligent Master Data Management for Dummies: Learn how to deploy intelligent MDM and take the first steps toward capturing the full value of your data.