Stardog in the News

The Future of Data Management: It’s Already Here

Analysts such as Gartner are claiming that data fabric is the future of data management. But, in fact, the future is already here. We see many signs of market maturity, ranging from total-addressable market projections to vendors pushing ROI. Data fabric’s unique ability to integrate enterprise data and reduce the need for repetitive tasks in data discovery, analysis, and implementation are the reasons why many believe this will be the breakout year for the modern data integration approach…

Why Data Fabrics are the Next Step in the Maturation of Data Management

Data fabrics enabled by Enterprise Knowledge Graphs offer a new way forward by weaving together data from internal silos and external sources and creating a network of information to power business applications, AI, and analytics.

10 Big Data Trends You Should Know About For 2022

From predictive analytics and data fabric architecture to data observability and data governance software, here’s a look at 10 big data trends and technologies that solution and service providers need to be aware of in the new year.

Eradicating Broken Data Integration Approaches to Unleash Advanced Analytics

Stardog CEO Kendall Clark shares his thoughts on how to eradicate broken data management approaches to unleash advanced analytics.

Speeding Time to Value: The ‘Just in Time’ Data Analytics Stack

The notion of just-in-time (JIT) analytics is one of the latest developments throughout the data landscape. This novel concept not only eliminates many of the conventional limits that have hampered enterprise use of analytics, it also spurs a newfound capability for continuous data intelligence that drastically increases the value derived from analyzing data.

The Turning Point for Enterprise Artificial Intelligence

Instead of different branches of AI competing with each other in vendor solutions, the industry has reached a point of inflection in which there are more offerings “doing new school AI, i.e. statistical learning, machine learning, what we call machine learning and also, at the same time, and we’ve worked on this so it all works together seamlessly, they’re also doing that symbolic or rules-based AI,” Stardog CEO Kendall Clark commented.

Turning data into gold: Knowledge graphs, AI, and machine learning

“There’s an analytics capability on one side, and a data integration or data prep capability on the other side. And you can think about the interaction of them as almost a third capability,” said Kendall Clark, of knowledge graphs.