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Prescriptive Recommendation Engines using GraphGridThe most common recommendation engines we interact with daily involve social media (the people we may know), retail (the products we may like), and entertainment (the music, clips and/or movies presented next in our streams).

Yet these are just the tip of the recommendation iceberg. When we look deeper into the inner workings of the largest organizations, enterprises and agencies in the world with critical business and mission decisions to make – based on a constant flow of ever changing, highly inter-connected data – we find much more complex and significant types of recommendations coming into play through prescriptive recommendation engines. Read more…

June 17, 2016

NBA Game Interactions with Neo4j on GraphGridThe NBA has enjoyed explosive growth in recent years; so much so that its TV deal, currently fetching $930 million annually from ESPN and Turner, will raise that number to $2.6 billion beginning next season, a 180 percent increase. In addition to its globalization, nutritional advancement, and technological progress, the quality of play itself has been consistently climbing season after season. Much of this trend can be attributed to team staffs making better decisions about personnel, playing time, play style, matchups, lineups, and the like. And as much as Barkley and other old-school players would like to minimize its impact, it is undeniable that the best teams who make the best decisions have a common underlying focus: data. Read more…

Moving Beyond Big Data with Neo4j on GraphGridEnterprises today are amassing data at a faster rate than ever before and largely this data flows into a data warehouse or data lake or just individual databases where it sits. With enterprises struggling to leverage it in a holistic and meaningful way for their business, the appeal of “big data” is waning. So how do enterprises begin moving beyond big data? Read more…

Research Organizations Using Neo4j on GraphGridMany enterprises today build their business around research that involves piecing together meaningful data from the public domain for their customers. When trying to connect data across a domain in a meaningful way building around a graph database is a great tool because it models very well exactly how the business analysts at these research organizations are piecing together the real-world data they are finding during their research. Read more…

Connected Enterprise with Neo4j on GraphGridThe 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. Read more…