IBM Cloud Data Science Studio
GPTKB entity
Statements (63)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:Company
|
| gptkbp:allows |
data exploration
|
| gptkbp:compatibleWith |
gptkb:IBM_Cloud_Pak_for_Data
|
| gptkbp:developedBy |
gptkb:IBM
|
| gptkbp:enables |
team collaboration
data visualization |
| gptkbp:facilitates |
machine learning
|
| gptkbp:features |
version control
collaborative workflows interactive visualizations integrated development environment |
| https://www.w3.org/2000/01/rdf-schema#label |
IBM Cloud Data Science Studio
|
| gptkbp:includes |
data preparation tools
data connectors |
| gptkbp:integratesWith |
gptkb:IBM_Watson
|
| gptkbp:is_accessible_by |
web interface
|
| gptkbp:is_available_in |
gptkb:IBM_Cloud_platform
|
| gptkbp:is_designed_to |
data scientists
accelerate data science workflows |
| gptkbp:is_integrated_with |
gptkb:IBM_Cloud_services
|
| gptkbp:is_known_for |
user-friendly interface
|
| gptkbp:is_part_of |
gptkb:IBM_Cloud
IBM's_AI_strategy |
| gptkbp:is_used_in |
business analysts
data-driven decision making enterprise environments predictive analytics data-driven insights AI model development |
| gptkbp:offers |
gptkb:Jupyter_Notebooks
customizable dashboards data sharing capabilities automated machine learning model monitoring data science lifecycle management cloud-native data science solutions |
| gptkbp:provides |
data analysis tools
data insights data security features data governance tools notebook sharing model deployment capabilities data collaboration tools scalable resources collaborative data science environment collaborative notebooks API_access |
| gptkbp:supports |
gptkb:Apache_Spark
Python R cloud computing Docker containers data analytics real-time data processing big data analytics data modeling data import/export team projects data pipelines data science education data wrangling data science best practices data science experiments |