The growing potency in an Enterprise AI Platform combined with Graph Databases is successfully enhancing machine learning models and ultimately tackling complex decision making effectively. Undeniably, both technologies are working hand-in-hand to make data relationships simpler by being scalable, performant, efficient and agile.

The most evident advantages of Graph Databases were seen during the current pandemic when governments needed to track down community infections. From tracing connections via complicated social networks to comprehending interconnections, Data Graph databases with Enterprise AI Platform have proven to be an excellent tool for data management in real-time.

Graph Databases successfully assists in aiding governments to make data-driven, intelligent decisions. Additionally, it helps prevent fraud and potential information leaks that mushroom disproportionally with the rapid COVID-driven digitalisation.

The added agility that Enterprise AI Platform and Graph Databases offers, makes it clear that the combination should be the preferred decision-making methodology.
Further, an Enterprise AI Platform along with Graph Databases has proven to be cost-effective for the government.

Graph Databases Technology Serving as a New Form of High-speed Information

Obtaining information in real-time has become critical for decision-making, particularly in times of crises. It has been demonstrated that information can be structurally arranged quickly using Graph Databases which has to be integrated with an Enterprise AI Platform.

Qualities Requirement to Deliver Actionable Insights

It is essential to deliver insights from analysing information and drawing conclusions that will influence decisions making and drive change. Graph Databases integrated with an Enterprise AI Platform will serve as the missing link for government to drive actionable outcomes from the data.

Combination of Enterprise AI Platform and Graph Databases in the Public Sector

Government agencies will benefit from an enhanced machine learning model to build an intelligent application that traverses today’s large, interconnected datasets in real-time. The copious volumes of data that organisations generate and collect need to be analysed and interpreted if they are to streamline government methods in forecasting and serve policymakers in effective decision-making.