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Showing 3 open source projects for "security"
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Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Cube
Universal semantic layer platform for AI, BI, spreadsheets
Cube is the semantic layer for building data applications. It helps data engineers and application developers access data from modern data stores, organize it into consistent definitions, and deliver it to every application. Cube was designed to work with all SQL-enabled data sources, including cloud data warehouses like Snowflake or Google BigQuery, query engines like Presto or Amazon Athena, and application databases like Postgres. Cube has a built-in relational caching engine to provide... -
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TRAK Metamodel
Tuples (triples) for TRAK architecture viewpoints and views
The definition of the metamodel for TRAK (defines allowed AD elements and relationships i.e. tuples/ triples for the TRAK viewpoints and views). TRAK is a general systems-thinkers'/system engineering enterprise architecture framework. It is simple, user-friendly, pragmatic and not limited to IT. 100% triple-centric and semantically-sound. Forms basis for RDF + OWL ontology description - see https://trakmetamodel.sourceforge.io/vocab/TRAK_metamodel.html. Each TRAK metamodel element now has... -
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survol
RDF-based framework monitoring business systems activity
A Python agent and a web interface aiming to help the analysis and investigation of a legacy application. A set of machines, processes, databases, programs etc ... all communicating with each other, manipulating your data, and whose software architecture has become, with time, complicated, difficult to understand, and undocumented. Data are aggregated with an RDF inference engine, creating a global vision of the business information processing.
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