Connected Enterprise: Data Essentials

Data Management and Graph Databases

Real-time Insights and Data Relationships

The connected enterprise is the new norm. Traditional chain paradigm with sequential and siloed operations lacking a connection between customer and factory is no longer cutting it. Today enterprises are excepted to be sufficiently in touch and aware of how to interact with each uniquely individual person they are fortunate to call their customer. Technologies and operational procedures are rapidly changing to enable information to be connected and taken together to drive decision making, direction, and interaction with the customer.

Connected data is the lifeblood of today’s enterprise. Yet, it’s frequently isolated in varying silos across an organization, with different accessibility, redundancy, quality, and varying data formats. Managing connected data involves identifying, cleaning, storing, and governing increased data volumes within an enterprise. Connected data involves essential information such as customers, users, products, services, sites, and business units.

Adequate practices for connected data management differ along a wide range of approaches. On one end, many believe that connected data should be united in one location; while on the other end, some recommend managing data assets from one application or service, even if information is housed in multiple locations.

In both cases, data architects require a data model that’s versatile and fluid when exceptions arise and business needs change. And the only model that can answer this is the graph database.

Enterprises today are flooded with “big data”, a majority of which is master data. Dealing with complex relationships between data points could be the biggest problem facing today’s enterprises.

The cost of a poor-performing data management system will affect an enterprise because data is constantly being shared, remixed, enhanced and connected. As a matter of fact, a majority of data management systems are created with a relational database, which aren’t even made for traversing connected data.

Yet, relationships in a data are essential to maintain competitive advantage with business analytics continuing to evolve.

The good news is, the fully open source graph database, ONgDB (Open Native Graph Database), uses an ideal data model for housing and querying connected data. They model your data in a straightforward and simple manner, enabling you to represent the complexity of your data connections in an explicit way compared to that of a relational database.

In addition, an ONgDB graph integrates seamlessly alongside existing data silos within an enterprise, acting as a catalyst to unify all data across the enterprise. Graph database relationships can easily link data siloed in a CRM (Customer Relationship Management) financial, inventory systems, etc to offer a consistent view of connected data.

Enterprise-grade data-driven decisions today shouldn’t be based on siloed data. Instead, a data management solution should offer real-time insights into data relationships.

ONgDB is precisely created to support critical data relationships. An efficient data model of a graph database and query language will aid in finding relevant answers more quickly and with increased flexibility than ever before. GraphGrid is designed for connecting data within the enterprise and enables you to jumpstart your journey towards being a connected enterprise.