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FactEngine solves 5 business problems when considering a knowledge graph for your organisation. FactEngine lets you:
1. Empowered Stakeholders:
Natural language enterprise modelling in business language is known to empower stakeholders and streamline communication.
Your data lake becomes a semantic knowledge graph;
Business Rules & Enterprise Model how you want to see it...as a semantic model, object-role/fact-based model, knowledge graph or relational model;
3. Data/Business Vault from the enterprise model:
Generate programming code and/or Database Definition Language (DDL) from your conceptual model;
4. Multi-database access:
Work with multiple data lakes/databases that comprise your knowledge graph. Minimise the number of databases you work with;
5. Natural language semantic graph queries.
Work with multiple query languages;
Query any database with natural language graph queries or your native database language* with FactEngine. Your knowledge graph...your way.
Keep your existing databases and use FactEngine's unique knowledge graph technology to query them as if they were a graph database. FactEngine is in beta release now.
Perform business language queries over your database with FactEngine's Knowledge Language. Natural language queries are graph queries. Write graph queries over your database Read More
Natural Language Queries over your Knowledge Graph
View your database as a graph or relational database with FactEngine's unique multi-model conceptual modelling. The choice is yours. Minimise overhead by minimising the number of databases that you need to work with. Leverage existing technology in your current architecture. Generate data definition script for your database from inside Boston, then use FactEngine to query your database.
Read more about FactEngine.
FactEngine is in beta release. Contact FactEngine for a demonstration.
* FactEngine uses one query language and an adaptor is required for each database type.