Statements (56)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:Cloud_Computing_Service
|
| gptkbp:aimsTo |
Data quality
|
| gptkbp:developedBy |
gptkb:IBM
|
| gptkbp:enables |
Real-time data processing
Data sharing Collaboration among data teams Faster time to market for data products |
| gptkbp:enhances |
Data analytics
|
| gptkbp:facilitates |
Data integration
|
| https://www.w3.org/2000/01/rdf-schema#label |
IBM Cloud Pak for DataOps
|
| gptkbp:includes |
Data catalog
Collaboration features |
| gptkbp:integratesWith |
gptkb:IBM_Watson
|
| gptkbp:isAvailableIn |
gptkb:IBM_Marketplace
Multiple languages |
| gptkbp:isCompatibleWith |
Kubernetes
Various data sources OpenShift |
| gptkbp:isDesignedFor |
Enterprise data management
Enhance data collaboration |
| gptkbp:isIntegratedWith |
gptkb:IBM_Cloud_Pak_for_Integration
gptkb:IBM_Cloud_Pak_for_Applications |
| gptkbp:isOptimizedFor |
Big data environments
|
| gptkbp:isPartOf |
IBM's_AI_strategy
IBM_Cloud_Pak_family IBM_Cloud_ecosystem |
| gptkbp:isRated |
Open-source technologies
|
| gptkbp:isSupportedBy |
IBM_support_services
|
| gptkbp:isTargetedAt |
Organizations seeking data-driven insights
|
| gptkbp:isUsedBy |
Business analysts
Data scientists Data engineers |
| gptkbp:isUsedFor |
Data analysis
Data migration |
| gptkbp:offers |
User-friendly interface
Customizable workflows Data visualization tools Monitoring and logging capabilities Automated_data_pipeline_management |
| gptkbp:provides |
APIs for integration
Data preparation Data lineage tracking Scalability options Data access controls Data orchestration capabilities Data quality assessment tools DataOps capabilities |
| gptkbp:supports |
Data security
Data governance Data transformation Hybrid cloud Private cloud Public cloud Data privacy compliance Multi-cloud strategy |
| gptkbp:utilizes |
AI and machine learning
|