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Stardog’s Joe Pindell discusses accelerating analytics and AI with knowledge graphs

Knowledge graphs are on the rise at enterprises hungry for greater automation and intelligence. The flexibility of the graph model, along with its explicit storage of data relationships, makes it not only easy to manage data arriving from diverse sources but search and explore data to reveal new insights that would otherwise be very difficult to discover.

KMWorld recently held a webinar with Joe Pindell, senior director, product marketing, Stardog who discussed evolving best practices and strategies for leveraging knowledge graphs.

According to a survey of 190 executives by Accenture Research, only 32% of companies surveyed are realizing tangible and measurable value from data, Pindell cited.

Data democratization and literacy are critical to modernizing analytics. By 2024, 50% of new system deployments in the cloud will be based on a cohesive cloud data ecosystem rather than on manually integrated point solutions. Organizations that utilize active metadata to enrich and deliver a dynamic data fabric will reduce time to integrated data delivery by 50% and improve the productivity of data teams by 20%, according to Pindell.

According to Gartner, by 2025, graph technologies will be used in 80% of data and analytics innovations, up from 10% in 2021, facilitating rapid decision making across the organization.

An enterprise knowledge graph is a flexible, semantic data layer for answering complex queries across data silos, Pindell said.

It unifies data and metadata using semantics and inferencing; evolves as your data fabric evolves; and queries data where it is, without requiring a major project to centralize data.

The most important capabilities of an enterprise knowledge graph platform are virtualization, semantic graphing, and inferencing. A knowledge graph enables a faster path to analytics production and agile self-service, Pindell noted.

With Stardog’s enterprise knowledge graph platform, Pindell said, users see an increase in data analyst productivity, shorter time to solution delivery, and less time spent fixing ETL.

A Forrester Consulting TEI Study by Stardog found, “Up to 320% ROI, total benefits over $9.8 million over three years.”

An archived on-demand replay of this webinar is available here.

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