Knowledge Graphs for knowledge landscaping, discovery and inference
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The company offers a knowledge graph pipeline for knowledge landscaping services, enabling big-data insights for teams and organizations with limited IT capacity. They use scientific python, redis, and SQL to leverage small IT resources and benchmarked their data-model on neo4j, orientDB, and SQL to cut server costs. Full-text search is powered by elasticsearch.
Strengths
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Efficient knowledge discovery
Ability to quickly and accurately discover relevant knowledge
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Inference capabilities
Ability to draw conclusions and make predictions based on discovered knowledge
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Flexible data integration
Ability to integrate data from various sources and formats
Weaknesses
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Limited domain expertise
May not be suitable for certain specialized domains
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Complexity
May require significant expertise to set up and use effectively
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Cost
May be expensive compared to other knowledge management solutions
Opportunities
- Increasing need for efficient knowledge management solutions in various industries
- Opportunity to tailor the solution to specific business needs
- Potential to enhance the solution with AI and machine learning capabilities
Threats
- Presence of other established knowledge management solutions in the market
- Potential for data breaches and privacy violations
- Need to comply with various regulations and standards related to data management
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http://nifty.works
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Knowledge Graphs for knowledge landscaping, discovery and inference Plan
Pricing for Knowledge Graphs for knowledge landscaping, discovery and inference varies based on version features, contact for details.
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