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What is MDM?

by Eric
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Master data management (MDM) refers to the set of disciplines, processes, and technologies used to manage corporate data. Master data is a massive collection of data related to business entities or objects, such as customers, suppliers, vendors, and products, around which business is conducted. MDM provides context and can be found across various data sources such as spreadsheets and applications.

The Basics of MDM

The Basics of MDM

Master data is often scattered across data silos, which makes it difficult to access pertinent information. An effective MDM solution unifies master data into a centralized data center to provide a single source of information. This ensures the consistency and quality of data, including product data, customer data, and asset data, and makes data available to end-users. MDM tools are used to improve workflow, operational efficiency, and improve business outcomes.

Master Data vs Reference Data

Master Data vs Reference DataReference data arises from master data. Both types of data provide context for business decisions. Master data focuses on business entities, while reference data focuses on the classification and organization of data. Examples of reference data include zip codes, transaction codes, country codes, customer segments, etc. Master data also provides key insights that aid business processes while reference data provides data that can be used for classification.

MDM tools ensure an organization’s data is consistent and accurate. MDM solutions include the people, processes, and systems necessary to ensure master data is accurate and consistent. Many businesses glean data from KPIs such as CRM and ERPs, which leads to data silos, data duplicates, and incomplete data.

What is MDM? An MDM system is a key organizational asset that drives business processes, is evaluated by analytics, and is controlled through data governance. There are several benefits of using the right MDM software. It can lead to increased revenue growth, improved workplace productivity, an optimized supply chain, better business insights, improved customer satisfaction, and improve compliance with data governance rules.

Master data management comes from several sources. It can come from unstructured data, from transactional data such as customer data, metadata, master data, supplier data, and from product data. There are several use cases for master data management. An effective MDM strategy can lead to faster product launches, personalized marketing, supply chain efficiency, operational efficiency, brand consistency, artificial intelligence and Internet of Things (IoT) applications, and GDPR compliance.

The best MDM platform supports the main styles of master data management including centrally authored, consolidation of source systems, coexistence, and registry. It allows the ability to publish and subscribe to real-time secure data, provides data and workflow visualization, and features a user-friendly interface.

MDM Strategy 101

MDM Strategy 101There are several aspects of building an effective MDM strategy. A successful MDM initiative requires an MDM agent of sorts who can manage the initiative. This means driving the project, keeping the IT department engaged, addressing any potential cultural or political issues, and balancing the need for support costs with long-term outcomes. A data steward will need to configure business processes to see the ROI of an MDM strategy. Having the right technology is key to implement an MDM strategy. This includes an MDM hub that centralizes all source system data, data integration, getting source system data into the MDM hub, and a data quality tool.

A combination of external and internal data is necessary to get a full view of business entities. Maintaining data security is key to a successful MDM strategy. Keeping up with compliance helps streamline MDM by providing rules for data validation and resolving data ownership.

MDM is one of the best practices for modern businesses. When data is used correctly, it can provide insights that reveal business opportunities, risks, and scalability.

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