Graph Advantage: Master Data Management

Master Data Management (MDM) is an increasingly complex topic for organizations today. The rate at which data in an enterprise to is flowing and evolving as a business asset, requires a the need for a more flexible and connection-centric master data storage solution. Master Data Management, is a practice that involves discovering, cleaning, housing, and governing data. Data architects for enterprises require a data model that offers ad hoc, variable, and excellent structures as business needs are constantly changing. This rapidly changing model ideally fits with a graph database.

Why a Graph Database for Master Data Management?

Because master data is constantly shared and connected, poorly made Master Data Management (MDM) systems can cost business agility in a way that slows your evolution as organization. A majority of MDM legacy systems depend on a relational database that isn’t even optimized for rapid response or traversing relationships.

Fortunately, graph databases are perfect for housing, querying, and modeling hierarchies, metadata, and connections in your master data. Master data is a lot simpler to model with graph databases as it requires less resources than making relational approach. Furthermore, you won’t have to move all your master data into one location. Graph relationships easily connect your siloed information across your CRM systems, inventory structures, point-of-sale systems, and accounting to offer a comprehensive view of your enterprise data.

Master Data Management Challenges

Enterprises today are inundated with Big Data. Organizing its highly complicated relationships can also pose a challenge. These are some challenges in Master Data Management that the Neo4j graph database helps 
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