Graph Databases in the Enterprise: Master Data Management

Master data is the lifeblood of your enterprise. The umbrella of “master data” includes vital data such as: Users Customers Products Accounts Partners Sites Business units Many business applications use master data and it’s often held in many different places, with lots of overlap and redundancy, in different formats, and with varying degrees of quality and means of... Read more →

Learn More about the Master Data Management Use Case of Graph Databases in the Enterprise


Using Graph Structure Record Linkage on Irish Census Data with Neo4j

For just over a year I’ve been obsessed on-and-off with a project ever since I stayed in the town of Skibbereen, Ireland. Taking data from the 1901 and 1911 Irish censuses, I hoped I would be able to find a way to reliably link resident records from the two together to identify the same residents. Since then I’ve learned a bit about master data management and record linkage and so I... Read more →

See How We Used Graph Structure Record Linkage to Extract Insights on Irish Census Data with Neo4j


Neo4j: Real-World Performance Experience with a Graph Model [Community Post]

It’s All about Performance Ultimately it’s the performance of your company as a whole which determines whether you remain in business. It was with these thoughts in mind that we began a major project to improve the performance of our business. The company we have been working for is based in Melbourne, Australia and is involved in advertising, marketing, and business information... Read more →

Learn How the Sensis Dev Team Experienced a Real-World Performance Increase with a Neo4j Graph Model


From Good to Graph: Choosing the Right Database [GraphConnect Preview]

For many of us, it feels like software development has well and thoroughly moved into the NoSQL database era. However, recent studies suggest that adoption is still as low as 20%. Personally, I joined the NoSQL movement in 2008 when I took a position with database vendor MarkLogic. Since that time I have been a big advocate for NoSQL technologies in all of their various flavors. While it... Read more →

Learn about Clark Richey’s Journey to Graph Databases and Why He Chose Neo4j for FactGem


A New Way of Looking at “Moving Relationships” in Neo4j [Community Post]

Introduction A graph database is not only a simple way to store connected data, it is also a powerful tool to manage dynamic relationships between data. Since relationships are natively implemented in Neo4j, we can use them as a simple way to identify a group of connected nodes. But it is not the only usage we can make of them. There are many use cases where consecutive queries can... Read more →

Learn Why You Should Understand “Moving Relationships,” a New Kind of Data Relationship in Neo4j


Graph Databases in the Enterprise: Real-Time Recommendation Engines

Whether your enterprise operates in the retail, social, services or media sector, offering your users highly targeted, real-time recommendations is essential to maximizing customer value and staying competitive. Unlike other business data, recommendations must be inductive and contextual in order to be considered relevant by your end consumers. With a graph database, you capture a... Read more →

Learn More about the Real-Time Recommendation Engine Use Case of Graph Databases in the Enterprise


GraphConnect SF 2015

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