Awards

Aug 24, 2022

Stardog a Finalist in DBTA Readers’ Choice Awards 2022

Stardog named a finalist in the 2022 DBTA Readers’ Choice Awards.

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Articles

Aug 10, 2022

Key Enterprise Knowledge Graph Examples for Data Quality Success

Enterprise knowledge graphs can help enforce data integrity, improve data correctness, and ensure data consistency. With these safeguards in place, organizations and end-users can clean up their data and rest easy knowing they are receiving complete and accurate results that they can use to solve their business needs.

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Press Releases

Aug 9, 2022

Stardog Strengthens Enterprise-Grade Security to Knowledge Graph in the Cloud

Achievement of SOC 2 Type 1 compliance validates Stardog as a trusted semantic layer for enterprise data and analytics.

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Articles

Jul 20, 2022

How Semantic-Based Knowledge Graphs Accelerate the Value of Data Lakes

Whether performing advanced analytics to drive decision-making or modeling complex relationships against data that is both too wide and big to describe people, places, things, and how they relate, knowledge graphs are making a difference in how information is found, used, and leveraged.

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Articles

Jul 20, 2022

PODCAST: Knowledge Graphs 101 with Kendall Clark, Founder & CEO of Stardog

What happens when an analyst has a new idea about how to organize and understand data? They have to start from scratch. They have to recreate a new version of the data, a new data set. And then, they have to go through the process of remodeling, retransforming and resummarizing the data all over again. But what if they didn’t have to? What if we could make data modeling far more flexible?

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Articles

Jul 18, 2022

5 Steps to Implementing a Modern Data Fabric Framework

If your organization wants a modern data management strategy, consider following the five fundamental steps to implementing a data fabric framework described here.

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Articles

Jun 15, 2022

Leveraging Knowledge Graph Technology to Fuel Advanced Analytics

Since the early 1990s, organizations have been collecting, storing, analyzing and reconfiguring a plethora of information, only to find 20 years later that they are still struggling to maximize their big data investments. The challenge remains clear for organizations of all sizes; they must have the ability to connect data and deliver analytics solutions to help solve urgent business problems.

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