Large Scale Graph Solutions: Use-cases and Lessons Learnt
summary
Covers Microsoft’s large-scale graph platform used for advertising, real-time streaming, fraud prediction, analytics and AI, emphasizing that connections between data drive intelligence. Describes building and comparing prototypes using DSE Titan, Spark GraphX, OWL reasoners with Python, and Apache Jena, and discusses engineering and infrastructure challenges such as cloud migration, technology whitelisting, real-time streaming, measurement and testing encountered while deploying graph ontologies at scale.
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chapters (4)
- 0:00Start
- 1:23Abstraction Is The Art
- 16:04Anonymized, attributes, direction, degrees
- 20:08Marklogic 9 Data Hub, Harmonization Create graph based on ontological inference
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