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Massive-Scale Entity Resolution Using the Power of Apache Spark and Graph

Massive-Scale Entity Resolution Using the Power of Apache Spark and Graph

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Spark’s graph capabilities are great at enabling analysis of networks for use-cases such as fraud-detection, illicit network detection, and supply chain risk analysis. However, in order for a data scientist to perform analytics on a network (e.g., Page Rank, community detection, etc.), they end up spending all their time fighting a mountain of data integration challenges. A specific challenge this talk will focus on is connecting entities in a network within and across data domains. We will explore how you can leverage the Spark ecosystem’s graph capabilities to perform massive-scale entity resolution (ER). As a result, your data scientists will be able to more quickly and effectively perform graph analytics that drive business and mission value. Key takeaways: 1) The Spark ecosystem enables you to quickly get started with graph analytics use-cases at scale 2) Complementing traditional ER techniques with the context of graph relationships allows you to connect entities that you could not easily connect before
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