Data Management Suite
The Data Management Suite facilitates the management and transformation of enterprise data siloes into actionable data that can be used for intelligent systems. The Data Management Suite comprises GraphDB’s RDF database and OpenRefine and UnifiedViews to help consolidate data from various formats and identify hidden connections between data objects. These capabilities serve as the foundation for enterprises to scale their systems effortlessly, while ensuring data remains well-structured and classified.
Components of the Data Management Suite
GraphDB
GraphDB is a semantic graph database for managing large knowledge graphs using RDF and SPARQL. It offers reasoning capabilities and integrates with applications like Elasticsearch for semantic search. Highly scalable, GraphDB supports real-time inferencing and query evaluation under massive data loads. It performs well across on-premise and cloud environments, making it suitable for healthcare and media industries.
Graph Modelling
Graphwise award-winning graph modeling tool delivers 1st class taxonomy and ontology management. It offers an intuitive, centralized platform to create, link, and manage knowledge structures, with generative AI recommendations and easy integration. By structuring and connecting enterprise data, PoolParty transforms siloed information into actionable insights, supporting AI-driven analytics and business growth.
UnifiedViews
PoolParty UnifiedViews is an ETL framework that integrates diverse data into a knowledge graph, supporting RDF and ontologies. It offers a graphical interface for creating data processing pipelines, allowing users to transform data into RDF and perform cleansing and validation. UnifiedViews supports features like SHACL for error detection and SPARQL queries for further data processing.
Refine
BI semantic layers focus on consistent data views for BI tools, using relational databases and SQL. Knowledge graph semantic layers represent data as interconnected entities, enabling reasoning and discovery via knowledge graph tech like RDF and SPARQL. Combining both leverages their strengths for comprehensive solutions. They aren’t the same concept.
Unify data and add context with ontologies and linking to a global knowledge with Graph Management Suite
Build, consume, govern enterprise knowledge graphs
Position
- Unify data via a shared model.
- Avoid misinterpretation via semantics.
- Manage data quality and trace provenance.
- Employ standards to avoid vendor lock-in.
Connect the dots across your IT systems
Position
- A data fabric to gain unified access to your structured data.
- Semantic models to search and recommend
- Uncover new relationships with reasoning.
Unlock the power of AI & LLM
Position
- Talk to your graph in using a no-code RAG
- Natural Language Query your graph from LangChain
Explore and clean your data efficiently
Position
- Explore and understand your data.
- Easily filter, edit and clean-up inconsistencies
- Work with raw data in many formats – TSV, CSV, *SV, XLS, XLSX, JSON, XML.
Map and transform data to RDF schemas
Position
- Intuitive RDF-ization workflow
- Access transformed data through virtual SPARQL endpoint.
- Save and apply transformations in batch mode
Streamline data integration
Position
- Reconcile raw data with remote reconciliation endpoints or custom-built endpoints.
- Integrate transformed data easily into existing knowledge graphs
Highlighted product features included in the Generative AI Bundle.
Highly performant simultaneous load, query and inference
- Custom reasoning and consistency checking rulesets
- Fast forward-chaining reasoning with efficient retraction of inferred statements upon update
Fully compliant with RDF
- RDF1.1 and SPARQL 1.1, with RDF-Star and SPARQL-Star extensions
- Compliant reasoning for the standard rulesets RDFS, OWL 2 RL and QL
- 100% compatible with the RDF4J framework
Connectors and API
- Plugin API for engine extensions
- MongoDB connector
- Lucene, Solr and Elasticsearch connector for full-text search
- Kafka connector for downstream synchronization
- Plugins for geo-spatial indexing, GeoSPARQL, RDF rank, etc.
Transform, Integrate and reconcile
- Intuitive RDF-ization workflow with visual mapping UI.
- Virtual SPARQL endpoint.
- Integrate transformed knowledge graphs with SPARQL federation.
WYSIWYG
- Drag and drop data processing unit (DPU)
- Connect to API’s, databases, servers, and other endpoints
- Specify the visibility of pipelines
Quality ensurance
- Monitor the progress of a pipeline
- Extensive debugging tools to improve data at any point of the pipeline
Services:
Access to the Graphwise Help Desk
Detailed Help documentation
Best Practice Configurations:
Once you have decided to use Graphwise it is time to find the configuration that best suits your needs. A key to this is the so-called multi-tiering, which is the use of Graphwise licenses on a distributed infrastructure.