Data Management Suite
The Data Management Suite provides the core infrastructure tools to transform raw enterprise data into a rich, interconnected AI-ready Knowledge Graph. It achieves this by consolidating and cleaning data from various sources and formats. The Data Management Suite comprises an RDF graph database (GraphDB), an Extract-Transform-Load (ETL) framework for integrating data (Graph Automation), and a data cleaning and RDF conversion tool (Graph Automation). Together, these tools help enterprises effortlessly scale their intelligent systems with well-structured and classified data, unlocking hidden connections and deriving actionable insights.
Components of the Data Management Suite
GraphDB
Semantic graph database, providing the powerful engine for building and managing large Enterprise Knowledge Graphs. It unifies disparate data sources to break down silos, enabling real-time reasoning and inferencing at scale to power semantic search, recommendation systems, and AI applications like LLMs and GraphRAG.
Graph Modeling
Award-winning graph modeling tool delivering 1st class taxonomy and ontology management. It offers a centralized, user-friendly platform for subject matters to create and manage KGs, with GenAI recommendations and easy integration. By structuring and connecting enterprise data, it transforms siloed information into actionable insights for AI-driven applications.
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 Data 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 in the Data Management Suite
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 assurance
- 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