Articles
Dec 9, 2021The modern data analytics stack is undergoing shocks as the requirements imposed by a hybrid multicloud world upon data analytics become more apparent. What’s ahead in 2022?
Press Releases
Dec 7, 2021Industry-first knowledge graph data platform study shows how Stardog customers can realize up to $9.86 million in benefits.
Articles
Dec 5, 2021Graph models help provide capabilities like improved feature engineering, root cause analysis, and graph analytics. This functionality is key to helping knowledge graphs transition to the dominant data management construct as data management and AI converge.
Articles
Dec 3, 2021Data fabrics are the cornerstone of modern analytics architecture, especially when implemented with data virtualization, knowledge graphs, and expressive data models.
Articles
Nov 23, 2021When properly implemented, data fabrics are a key technology area in artificial intelligence (AI), an ideal means of preparing data for machine learning, and an irreplaceable component in modern data integration methods that deliver better, faster and less expensive analytics than almost any other approach. The closer we can bring the common-sense business terminology and questions as the underlying fabric of data in an IT ecosystem, the more agility the enterprise builds to establish trust with highly connected and context-rich data to assist customers along every step of their journey.
Articles
Nov 17, 2021Data warehouses, data lakes, and data lakehouses are arguably the most popular methods of integrating data today. They’re older, current, and newer integration approaches—respectively—for running analytics and applications across all enterprise data. Using a semantic layer to connect them to the rest of the data ecosystem in the cloud, on-premises, and at the edge ensures their continued relevance now and in the future.
Articles
Nov 10, 2021The majority of large data integration projects falter because systems are developed in a bespoke fashion, leaving organisations with critical applications that have been modified and transformed into a hornet’s nest of code that they cannot unravel for fear of breaking something. So, instead of trying to unravel systems, organisations have tended to duplicate processes, leading to more silos and custom solutions, which is an expensive proposition. Similarly, projects that end up as mass data cleansing and manipulation exercises are not sustainable in a world where organisations want insight into their data at speed.
