Self-Service Model Delivery
Multiple model delivery modes to comply with existing workflows
Cat avg: 0
Top Performing Features
Flexible Model Publishing Options
Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.
Cat avg: 0
Interactive Data Analysis
Ability to analyze data interactively using Python or R Notebooks
Cat avg: 0
Multiple Model Development Languages and Tools
Access to multiple popular languages, tools, and packages such as R, Python, SAS, Jupyter, RStudio, etc.
Cat avg: 0
Worst Performing Features
Connect to Multiple Data Sources
Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion
Cat avg: 0
Automatic Data Format Detection
Automatic detection of data formats and schemas
Cat avg: 0
Automated Machine Learning
Tools to help automate algorithm development
Cat avg: 0
Data Science Workbench Features from Reviews
Platform Connectivity
Ability to connect to a wide variety of data sources
7.50%
Connect to Multiple Data Sources
Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion
Category average: 0
Extend Existing Data Sources
Use R or Python to create custom connectors for any APIs or databases
Category average: 0
Automatic Data Format Detection
Automatic detection of data formats and schemas
Category average: 0
MDM Integration
Integration with MDM and metadata dictionaries
Category average: 0
Data Exploration
Ability to explore data and develop insights
7.60%
Visualization
The product’s support and tooling for analysis and visualization of data.
Category average: 0
Interactive Data Analysis
Ability to analyze data interactively using Python or R Notebooks
Category average: 0
Data Preparation
Ability to prepare data for analysis
7.80%
Interactive Data Cleaning and Enrichment
Access to visual processors for data wrangling
Category average: 0
Data Transformations
Use visual tools for standard transformations
Category average: 0
Data Encryption
Data encryption to ensure data privacy
Category average: 0
Built-in Processors
Library of processors for data quality checks
Category average: 0
Platform Data Modeling
Building predictive data models
7.60%
Multiple Model Development Languages and Tools
Access to multiple popular languages, tools, and packages such as R, Python, SAS, Jupyter, RStudio, etc.
Category average: 0
Automated Machine Learning
Tools to help automate algorithm development
Category average: 0
Single platform for multiple model development
Single place to build, validate, deliver, and monitor many different models
Category average: 0
Self-Service Model Delivery
Multiple model delivery modes to comply with existing workflows
Category average: 0
Model Deployment
Tools for deploying models into production
8.00%
Flexible Model Publishing Options
Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.
Category average: 0
Security, Governance, and Cost Controls
Built-in controls to mitigate compliance and audit risk with user activity tracking
Category average: 0