Category: Computing & data (Page 19 of 80)

Stardog, a provider of an enterprise knowledge graph platform, announced Stardog 9, with a range of new features and enhancements that enable organizations to easily connect data, people, and processes, and improve performance, scalability, and security. With this release, Stardog’s knowledge graph powered semantic layer has new integrations for Azure Synapse, Collibra Data Governance and Databricks. Benefits include:

• Expanded Data Access: Stardog 9 supports federated access to Azure Synapse which enhances connectivity to data in Azure Data Lake Storage Gen-2 (ADLS2), reducing the friction in accessing and connecting data through meaning for self-serve analytics.
• Activated Metadata: Stardog 9 extends Stardog’s Knowledge Catalog to harvest enterprise metadata with integrations for Collibra and Microsoft Purview Data catalogs (in-preview mode only), and any JDBC-accessible data source. These integrations make it easy to semantically-enrich technical metadata with business concepts and enable Data Governance teams and end users to search, query, and explore data assets with an Enterprise Metadata Knowledge Graph.
• Smart, Automated Entity Linking Across Data Silos: Stardog 9 can identify and link data associated with business objects across data landscapes for better decisions in support of use-cases from Customer 360 to Digital Twin to Fraud Detection, leveraging Databricks Spark to process data.

https://www.stardog.com/blog/introducing-stardog-9/

Ontotext, a provider of enterprise knowledge graph (EKG) technology and semantic database engines, released Ontotext Metadata Studio version 3.2. The metadata management and tagging control solution helps organizations to transform content into knowledge. Users can utilize the taxonomical instance data in their knowledge graph to achieve explainable and customizable out-of-the-box taxonomy-driven tagging.

Ontotext Metadata Studio 3.2 makes it easy for users to determine whether a use case could be automated or not across any third-party text mining service, simplifies orchestrating complex text analysis across third-party services, and evaluates their quality against internal benchmarks or against one another.

With version 3.2, Ontotext Metadata Studio enables non-technical end users to create, evaluate, and improve the quality of their text analytics service by tagging and linking against their own business domain model. With extensive explainability and control features, users who are not proficient in text analytics techniques can understand the causal relationships between the underlying dataset, the specific text analytics service configuration, and the final output.

This enhancement enables efficient user intervention, making the human truly in the loop and completely in control of the whole extraction process. Ontotext Metadata Studio is domain neutral and applicable for various domains and use cases.

https://www.ontotext.com

Ontotext, a provider of enterprise knowledge graph (EKG) technology and semantic database engines, launched GraphDB 10.2, an RDF database for knowledge graph. GraphDB enables organizations to link diverse data, index it for semantic search, and enrich it via text analysis to build large scale knowledge graphs. With improved cluster backup and cloud support, GraphDB lowers traditional memory requirements, and provides a more transparent memory model.

Users can oversee system health and diagnose problems easier using industry-standard toolkit Prometheus or by monitoring performance directly within the GraphDB Workbench itself. The solution also includes support for X.509 client certificate authentication for greater flexibility when accessing a secured GraphDB instance.

Backups can also be stored directly in Amazon S3 storage to ensure the most up to date data is securely protected against inadvertent changes or hardware failures in local on-prem infrastructure.

Internal structures and moved memory usage from off-heap to the Java heap were also redesigned for a more straightforward memory configuration, where a single number i.e. (the Java maximum heap size) controls the maximum memory available to GraphDB. Memory used during RDF Rank computation was also optimized making it possible to compute the rank of larger repositories with less memory.

https://www.ontotext.com