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
Connected Enterprise: Data Essentials
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.
Data Management and Graph Databases
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
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