Presented by David Newman, Wells Fargo

http://sps.columbia.edu/executive-edu...

We are at the juncture of a major shift in how we represent and manage data in the financial industry. Conventional data management capabilities are ill equipped to effectively link, harmonize and understand increasing volumes of highly variable data, especially when it is dispersed across multiple line of business organizations or sourced from external sites containing unstructured content. Knowledge graph technology has emerged as a viable production ready capability to elevate the state of the art of data management. Knowledge graph can remediate these challenges and open up new realms of opportunities not possible before with legacy technologies.

This presentation describes the operational capabilities and benefits of knowledge graph technology, the "future of financial data". We will discuss how knowledge representation and reasoning capabilities using ontologies is the way forward to tame the enterprise data management monster. The Financial Industry Business Ontology (FIBO) is described as an exemplar of a semantically modeled knowledge graph for finance. David describes how semantic graphs can be further enriched with probabilistic associations from machine learning and data mining algorithms.

David also discusses the evolution of data from strings and numbers, to first class semantic objects to distributed representations of concept embeddings in vector space and describe how knowledge graph technology can provide a layer of ‘knowledge’ over legacy data structures to obtain maximum understanding of content and provide the foundational building blocks for powerful semantic data catalogs and data lakes. Knowledge graph also positions organizations to better support customer 360, risk management, regulatory compliance, asset management and many other use cases.

- - -

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.