Designing and Building Enterprise Knowledge Graphs from Relational Databases in the Real World

Описание: Presented by Juan F. Sequeda, co-founder of Capsenta.

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Knowledge Graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and large scale data. We observe the adoption of Knowledge Graphs by the Googles of the world. However, not everybody is Google. Enterprises still struggle to understand their relational databases consisting of thousands of tables, tens of thousands of attributes and how the data all work together. How can enterprise adopt Knowledge Graphs successfully to address Data Integration and Business Intelligence needs, without boiling the ocean?

This tutorial chronicles the obstacles encountered and lessons learned by Capsenta when deploying Knowledge Graph technologies with enterprise users in domains such as E-commerce, Oil & Gas and Life Science. The tutorial also presents a step by step methodology to design knowledge graph schemas and mappings. Furthermore, it covers different types of relational databases to graph mapping patterns. The content of this tutorial is applicable to knowledge graphs being built either with Property Graph or RDF Graph technologies. The audience will take away concrete steps on how to effectively start designing and building knowledge graphs that will be widely useful within their enterprise.

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Offered on Columbia University’s Morningside campus in New York City, the Knowledge Graph Conference (KGC) is a world-class curated program that brings experienced practitioners, technology leaders, cutting-edge researchers, academics and vendors together for two days of presentations, discussions and networking on the topic of knowledge graphs.

While the underlying technologies to store, retrieve, publish and model knowledge graphs have been around for a while, it is only in recent years that widespread adoption has started to take hold.

As knowledge is an essential component of intelligence, knowledge graphs are an essential component of AI. They form an organized and curated set of facts that provide support for models to understand the world. Today, they power tasks like natural language understanding, search and recommendation, and logical reasoning. Tomorrow they will ubiquitously be used to store and retrieve facts learned by intelligent agents.

In the enterprise, knowledge graphs are the ultimate dataset. Integrating and organizing together internal and external data sources. Knowledge graphs integrate with the larger information system: master data management, data governance, data quality. Their flexibility and powerful representation capabilities allow data scientists to tap them to build powerful models.

The Knowledge Graph Conference is coordinated by Columbia University School of Professional Studies' Executive Education program. Visit: http://sps.columbia.edu/executive-edu... for more information.

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