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IBM Watson Studio

IBM Watson Studio

Overview

What is IBM Watson Studio?

IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data…

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Recent Reviews

Beginner Guide Review

7 out of 10
December 01, 2020
Incentivized
IBM Watson studio is being used to host Juypter Notebooks. These notebooks contains analyses for various projects. The primary project …
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Review on IBM Watson

9 out of 10
November 25, 2020
Incentivized
I have been using IBM Watson [Studio (formerly IBM Data Science Experience)] for the purpose of Data science course which was offered by …
Continue reading
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 16 features
  • Interactive Data Analysis (22)
    10.0
    100%
  • Visualization (22)
    10.0
    100%
  • Connect to Multiple Data Sources (22)
    8.0
    80%
  • Extend Existing Data Sources (22)
    8.0
    80%
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Pricing

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N/A
Unavailable

What is IBM Watson Studio?

IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI…

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Features

Platform Connectivity

Ability to connect to a wide variety of data sources

8.1
Avg 8.5

Data Exploration

Ability to explore data and develop insights

10
Avg 8.4

Data Preparation

Ability to prepare data for analysis

9.5
Avg 8.2

Platform Data Modeling

Building predictive data models

9.5
Avg 8.5

Model Deployment

Tools for deploying models into production

8
Avg 8.6
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Product Details

What is IBM Watson Studio?

IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.

IBM Watson Studio Competitors

IBM Watson Studio Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

Amazon SageMaker and Azure Machine Learning are common alternatives for IBM Watson Studio.

Reviewers rate Automatic Data Format Detection and Visualization and Interactive Data Analysis highest, with a score of 10.

The most common users of IBM Watson Studio are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(221)

Attribute Ratings

Reviews

(1-22 of 22)
Companies can't remove reviews or game the system. Here's why
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (3)
86.66666666666666%
8.7
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
100%
10.0
Data Exploration (2)
100%
10.0
Visualization
100%
10.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
95%
9.5
Interactive Data Cleaning and Enrichment
100%
10.0
Data Transformations
100%
10.0
Data Encryption
80%
8.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
95%
9.5
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
80%
8.0
Model Deployment (2)
80%
8.0
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
70%
7.0
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
65%
6.5
Connect to Multiple Data Sources
70%
7.0
Extend Existing Data Sources
70%
7.0
Automatic Data Format Detection
60%
6.0
MDM Integration
60%
6.0
Data Exploration (2)
50%
5.0
Visualization
50%
5.0
Interactive Data Analysis
50%
5.0
Data Preparation (4)
55%
5.5
Interactive Data Cleaning and Enrichment
60%
6.0
Data Transformations
60%
6.0
Data Encryption
50%
5.0
Built-in Processors
50%
5.0
Platform Data Modeling (4)
55%
5.5
Multiple Model Development Languages and Tools
60%
6.0
Automated Machine Learning
50%
5.0
Single platform for multiple model development
50%
5.0
Self-Service Model Delivery
60%
6.0
Model Deployment (2)
55%
5.5
Flexible Model Publishing Options
50%
5.0
Security, Governance, and Cost Controls
60%
6.0
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
42.5%
4.3
Connect to Multiple Data Sources
50%
5.0
Extend Existing Data Sources
50%
5.0
Automatic Data Format Detection
70%
7.0
MDM Integration
N/A
N/A
Data Exploration (2)
80%
8.0
Visualization
80%
8.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
75%
7.5
Interactive Data Cleaning and Enrichment
70%
7.0
Data Transformations
70%
7.0
Data Encryption
80%
8.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
75%
7.5
Multiple Model Development Languages and Tools
80%
8.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
70%
7.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
30%
3.0
Flexible Model Publishing Options
50%
5.0
Security, Governance, and Cost Controls
10%
1.0
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
62.5%
6.3
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
60%
6.0
Automatic Data Format Detection
60%
6.0
MDM Integration
50%
5.0
Data Exploration (2)
75%
7.5
Visualization
70%
7.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
77.5%
7.8
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Data Encryption
70%
7.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
72.5%
7.3
Multiple Model Development Languages and Tools
60%
6.0
Automated Machine Learning
60%
6.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
65%
6.5
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
50%
5.0
Venugopal Dontaraboyana | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
90%
9.0
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
80%
8.0
MDM Integration
90%
9.0
Data Exploration (2)
100%
10.0
Visualization
100%
10.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
77.5%
7.8
Interactive Data Cleaning and Enrichment
100%
10.0
Data Transformations
70%
7.0
Data Encryption
60%
6.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
95%
9.5
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
70%
7.0
Flexible Model Publishing Options
60%
6.0
Security, Governance, and Cost Controls
80%
8.0
February 04, 2021

Review of IBM services

Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
80%
8.0
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
90%
9.0
MDM Integration
70%
7.0
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
75%
7.5
Interactive Data Cleaning and Enrichment
70%
7.0
Data Transformations
80%
8.0
Data Encryption
80%
8.0
Built-in Processors
70%
7.0
Platform Data Modeling (4)
70%
7.0
Multiple Model Development Languages and Tools
70%
7.0
Automated Machine Learning
70%
7.0
Single platform for multiple model development
70%
7.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
70%
7.0
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
70%
7.0
Score 6 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
70%
7.0
Connect to Multiple Data Sources
70%
7.0
Extend Existing Data Sources
70%
7.0
Automatic Data Format Detection
70%
7.0
MDM Integration
70%
7.0
Data Exploration (2)
70%
7.0
Visualization
70%
7.0
Interactive Data Analysis
70%
7.0
Data Preparation (4)
70%
7.0
Interactive Data Cleaning and Enrichment
70%
7.0
Data Transformations
70%
7.0
Data Encryption
70%
7.0
Built-in Processors
70%
7.0
Platform Data Modeling (4)
70%
7.0
Multiple Model Development Languages and Tools
70%
7.0
Automated Machine Learning
70%
7.0
Single platform for multiple model development
70%
7.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
80%
8.0
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
80%
8.0
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
75%
7.5
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
70%
7.0
MDM Integration
70%
7.0
Data Exploration (2)
85%
8.5
Visualization
90%
9.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
77.5%
7.8
Interactive Data Cleaning and Enrichment
70%
7.0
Data Transformations
80%
8.0
Data Encryption
70%
7.0
Built-in Processors
90%
9.0
Platform Data Modeling (4)
80%
8.0
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
75%
7.5
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
80%
8.0
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
90%
9.0
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
100%
10.0
MDM Integration
80%
8.0
Data Exploration (2)
95%
9.5
Visualization
90%
9.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
100%
10.0
Interactive Data Cleaning and Enrichment
100%
10.0
Data Transformations
100%
10.0
Data Encryption
100%
10.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
87.5%
8.8
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
100%
10.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
100%
10.0
NARESH SAMPARA | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (3)
83.33333333333334%
8.3
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
80%
8.0
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
85%
8.5
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
90%
9.0
Data Encryption
80%
8.0
Built-in Processors
90%
9.0
Platform Data Modeling (3)
83.33333333333334%
8.3
Multiple Model Development Languages and Tools
80%
8.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
80%
8.0
Model Deployment (2)
75%
7.5
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
60%
6.0
December 01, 2020

Beginner Guide Review

Score 7 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
62.5%
6.3
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
40%
4.0
MDM Integration
50%
5.0
Data Exploration (2)
60%
6.0
Visualization
60%
6.0
Interactive Data Analysis
60%
6.0
Data Preparation (4)
57.5%
5.8
Interactive Data Cleaning and Enrichment
40%
4.0
Data Transformations
50%
5.0
Data Encryption
70%
7.0
Built-in Processors
70%
7.0
Platform Data Modeling (4)
75%
7.5
Multiple Model Development Languages and Tools
70%
7.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
60%
6.0
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
50%
5.0
November 25, 2020

Review on IBM Watson

Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
90%
9.0
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
80%
8.0
MDM Integration
90%
9.0
Data Exploration (2)
85%
8.5
Visualization
90%
9.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
92.5%
9.3
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
92.5%
9.3
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
85%
8.5
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
90%
9.0
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
87.5%
8.8
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
100%
10.0
MDM Integration
80%
8.0
Data Exploration (2)
65%
6.5
Visualization
70%
7.0
Interactive Data Analysis
60%
6.0
Data Preparation (4)
67.5%
6.8
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
80%
8.0
Data Encryption
50%
5.0
Built-in Processors
50%
5.0
Platform Data Modeling (4)
80%
8.0
Multiple Model Development Languages and Tools
80%
8.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
70%
7.0
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
70%
7.0
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
40%
4.0
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
N/A
N/A
MDM Integration
N/A
N/A
Data Exploration (2)
90%
9.0
Visualization
100%
10.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
40%
4.0
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Data Encryption
N/A
N/A
Built-in Processors
N/A
N/A
Platform Data Modeling (3)
80%
8.0
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
70%
7.0
Model Deployment (2)
85%
8.5
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
90%
9.0
November 04, 2019

Watson Studio Review

Score 6 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
55%
5.5
Connect to Multiple Data Sources
70%
7.0
Extend Existing Data Sources
60%
6.0
Automatic Data Format Detection
20%
2.0
MDM Integration
70%
7.0
Data Exploration (2)
75%
7.5
Visualization
80%
8.0
Interactive Data Analysis
70%
7.0
Data Preparation (4)
27.5%
2.8
Interactive Data Cleaning and Enrichment
30%
3.0
Data Transformations
N/A
N/A
Data Encryption
30%
3.0
Built-in Processors
50%
5.0
Platform Data Modeling (4)
47.5%
4.8
Multiple Model Development Languages and Tools
60%
6.0
Automated Machine Learning
50%
5.0
Single platform for multiple model development
50%
5.0
Self-Service Model Delivery
30%
3.0
Model Deployment (2)
55%
5.5
Flexible Model Publishing Options
50%
5.0
Security, Governance, and Cost Controls
60%
6.0
Christopher Penn | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
ResellerIncentivized
Platform Connectivity (4)
47.5%
4.8
Connect to Multiple Data Sources
50%
5.0
Extend Existing Data Sources
60%
6.0
Automatic Data Format Detection
20%
2.0
MDM Integration
60%
6.0
Data Exploration (2)
70%
7.0
Visualization
70%
7.0
Interactive Data Analysis
70%
7.0
Data Preparation (4)
85%
8.5
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Data Encryption
100%
10.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
87.5%
8.8
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
90%
9.0
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
100%
10.0
February 22, 2019

Analytics for the Masses

Score 10 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (3)
83.33333333333334%
8.3
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
80%
8.0
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
82.5%
8.3
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
90%
9.0
Data Encryption
70%
7.0
Built-in Processors
90%
9.0
Platform Data Modeling (4)
90%
9.0
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
95%
9.5
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
100%
10.0
ashish devassy | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
67.5%
6.8
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
70%
7.0
MDM Integration
N/A
N/A
Data Exploration (2)
80%
8.0
Visualization
80%
8.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
80%
8.0
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Data Encryption
80%
8.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
100%
10.0
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
100%
10.0
Model Deployment (2)
100%
10.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
100%
10.0
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
65%
6.5
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
70%
7.0
Automatic Data Format Detection
90%
9.0
MDM Integration
N/A
N/A
Data Exploration (2)
80%
8.0
Visualization
80%
8.0
Interactive Data Analysis
80%
8.0
Data Preparation (3)
90%
9.0
Interactive Data Cleaning and Enrichment
100%
10.0
Data Transformations
70%
7.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
65%
6.5
Multiple Model Development Languages and Tools
N/A
N/A
Automated Machine Learning
100%
10.0
Single platform for multiple model development
70%
7.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
55%
5.5
Flexible Model Publishing Options
60%
6.0
Security, Governance, and Cost Controls
50%
5.0
February 14, 2019

Watson Studio review

Van West | TrustRadius Reviewer
Score 5 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
55%
5.5
Connect to Multiple Data Sources
60%
6.0
Extend Existing Data Sources
50%
5.0
Automatic Data Format Detection
50%
5.0
MDM Integration
60%
6.0
Data Exploration (2)
50%
5.0
Visualization
40%
4.0
Interactive Data Analysis
60%
6.0
Data Preparation (4)
42.5%
4.3
Interactive Data Cleaning and Enrichment
50%
5.0
Data Transformations
40%
4.0
Data Encryption
70%
7.0
Built-in Processors
10%
1.0
Platform Data Modeling (4)
52.5%
5.3
Multiple Model Development Languages and Tools
60%
6.0
Automated Machine Learning
60%
6.0
Single platform for multiple model development
60%
6.0
Self-Service Model Delivery
30%
3.0
Model Deployment (2)
55%
5.5
Flexible Model Publishing Options
40%
4.0
Security, Governance, and Cost Controls
70%
7.0
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
65%
6.5
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
80%
8.0
MDM Integration
N/A
N/A
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
90%
9.0
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
90%
9.0
Platform Data Modeling (4)
100%
10.0
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
100%
10.0
Model Deployment (2)
95%
9.5
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
100%
10.0
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
77.5%
7.8
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
80%
8.0
MDM Integration
70%
7.0
Data Exploration (2)
70%
7.0
Visualization
70%
7.0
Interactive Data Analysis
70%
7.0
Data Preparation (4)
75%
7.5
Interactive Data Cleaning and Enrichment
70%
7.0
Data Transformations
70%
7.0
Data Encryption
80%
8.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
77.5%
7.8
Multiple Model Development Languages and Tools
80%
8.0
Automated Machine Learning
70%
7.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
80%
8.0
Model Deployment (2)
70%
7.0
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
60%
6.0
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