Chapter 1. How to Get Value from Graphs in Just Five Days
All the world’s a graph. The early 2010s saw modern enterprises adopting what was niche at the time—graphs—for use cases, such as online real-time recommendations or impact analysis. They chose graph databases over relational and other NoSQL databases because of their performance, scalability, and astonishing ability to traverse, in real time, relationships that connect data. The graph captured rich connections that mirrored the real world.
Fast forward 10 years, and the graph technology landscape has exploded. Beyond those initial use cases, graphs are the answer to a critical aspect of today’s data: complexity.
The last two decades have been about data—data collection, analysis, prediction, and protection. Everything around us captures data. Some organizations exist solely to analyze data and provide insights. For others, the usage of data determines the success of the business.
Ever since Clive Humby1 proclaimed that “data is the new oil” back in 2006, the imagination, creativity and technical innovation of various companies deriving value from data has seen no bounds. From the rise of NoSQL databases in the first decade of the 2000s to the mind-boggling pace of generative AI (GenAI) today, it is clear that we are not even close to being done with data. We live in the data age for sure, but more importantly, we live in the time of connected data—and value lies in the connections. As digital consumers, we now expect relevant, ...
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