Data Quadrant Awards 2022

Machine Learning

SoftwareReviews names MathWorks Matlab, Dataiku Data Science Studio (DSS), and Databricks as Machine Learning Data Quadrant Award Winners.

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Machine Learning

Data Quadrant

Data Quadrants are proudly founded in 100% user review data and are free of traditional "magical" components such as market presence and analyst opinion, which are opaque in nature and may be influenced by vendor pressure, financial or otherwise.

The SoftwareReviews Data Quadrant evaluates and ranks products based on feedback from IT and business professionals. The placement of a software in the Data Quadrant indicates its relative ranking as well as its categorization.

Read The In-Depth Report

A thorough evaluation and ranking of all software in an individual category to compare software across every dimension.

user satisfaction rankings
|
vendor capability comparisons
|
business value scores
|
individual feature evaluations
|
emotional connection to products

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30+ pages

Note Software product placement is based on the scores provided by users, recency of the reviews, and review volume. Axes are dynamically adjusted based on the minimum and maximum values in the data set.

Evaluate the Complete

Software Experience

When distilled down, the software experience is shaped by both the experience with the software and the relationship with the vendor. Evaluating enterprise software along these two dimensions provides a comprehensive understanding of the product and helps identify vendors that can deliver on both.

Product Features and Satisfaction

The satisfaction is captured in the overall satisfaction score, which is driven by the likelihood of users to recommend the software, combined with user satisfaction across top product features.

Vendor Experience and Capabilities

The vendor relationship is calculated in a weighted average of the satisfaction scores tied to vendor capabilities (e.g. software implementation, training, customer support, product roadmap) as well as emotional response ratings toward the vendor (e.g. trustworthy, respectful, fair).

Gold Medalists

17Reviews

MathWorks

MathWorks Matlab

MATLAB is a high-level language and interactive environment for numerical computation, visualization, and programming.

8.8

Composite
Score

+98

Emotional
Footprint

92%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

11Reviews

Dataiku

Dataiku Data Science Studio (DSS)

Dataiku is the platform democratizing access to data and enabling enterprises to build their own path to AI in a human-centric way.

8.5

Composite
Score

+92

Emotional
Footprint

88%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

11Reviews

Databricks

We believe big data should be simple. Apache Spark™ made a big step towards this goal. Databricks makes Spark easy through a cloud-based integrated workspace.

8.3

Composite
Score

+92

Emotional
Footprint

87%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

Vendor Capability Awards

Availability and Quality of Training

MathWorks Matlab

Breadth of Features

MathWorks Matlab

Business Value Created

MathWorks Matlab

Ease of Customization

Google Cloud Machine Learning Engine

Ease of Data Integration

RapidMiner

Ease of IT Administration

DataRobot AI Cloud

Ease of Implementation

Google Cloud Machine Learning Engine

Product Strategy and Rate of Improvement

Databricks

Quality of Features

Dataiku Data Science Studio (DSS)

Usability and Intuitiveness

Dataiku Data Science Studio (DSS)

Vendor Support

Dataiku Data Science Studio (DSS)

Vendor Capability Awards

Availability and Quality of Training

MathWorks Matlab

Breadth of Features

MathWorks Matlab

Business Value Created

MathWorks Matlab

Ease of Customization

Google Cloud Machine Learning Engine

Ease of Data Integration

RapidMiner

Ease of IT Administration

DataRobot AI Cloud

Ease of Implementation

Google Cloud Machine Learning Engine

Product Strategy and Rate of Improvement

Databricks

Quality of Features

Dataiku Data Science Studio (DSS)

Usability and Intuitiveness

Dataiku Data Science Studio (DSS)

Vendor Support

Dataiku Data Science Studio (DSS)

Other Evaluated Vendors

27Reviews

Google

Google Cloud Machine Learning Engine

Cloud Machine Learning Engine is a managed service that lets developers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually. It has been used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails. The training and prediction services within ML Engine are now referred to as AI Platform Training and AI Platform Prediction.

8.2

Composite
Score

+84

Emotional
Footprint

87%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

17Reviews

DataRobot, Inc.

DataRobot AI Cloud

The DataRobot Enterprise AI platform includes two independent but fully integrable machine learning model building products, and each can be deployed in multiple ways to match your business needs and IT requirements. All configurations feature a constantly expanding set of diverse, best-in-class algorithms from R, Python, H2O, Spark, and other sources, giving you the best set of tools for your machine learning and AI projects.

8.1

Composite
Score

+76

Emotional
Footprint

88%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

14Reviews

RapidMiner

Built for analytics teams, RapidMiner unifies the entire data science lifecycle from data prep to machine learning to predictive model operations.

8.0

Composite
Score

+80

Emotional
Footprint

83%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

14Reviews

KNIME

Knime

At KNIME, we build software to create and productionize data science using one easy and intuitive environment, enabling every stakeholder in the data science process to focus on what they do best. One enterprise-grade software platform, two complementary tools. Open source KNIME Analytics Platform for creating data science and commercial KNIME Server for productionizing data science.

8.0

Composite
Score

+80

Emotional
Footprint

87%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

17Reviews

Alteryx, Inc.

Alteryx

Alteryx provides a single workflow for data blending, analytics, and reporting. This workflow allows the seamless blending of internal, third party and cloud-based data, and simple analysis using 60+ prebuilt tools for spatial and predictive analytics.

8.0

Composite
Score

+86

Emotional
Footprint

81%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

16Reviews

Altair Engineering, Inc.

Altair Data Analytics Suite

Altair Data Analytics enables organizations worldwide to compete more effectively by operationalizing data analytics and AI with secure, governed, and scalable strategies. We deliver world-class, self-service analytics solutions for data preparation, predictive modeling, stream processing, visualization and more. Our solutions are designed for many different skill sets: from data scientists and engineers to MLOps specialists to business analysts to executives. With a no-code, cloud-ready interface, organizations can harness the full power of analytics and AI throughout its complete data lifecycle, driving next-level business results.

6.9

Composite
Score

+64

Emotional
Footprint

75%

Likeliness to
Recommend

Likeliness
to Recommend

Write a Review

Product Report

15+
pages

For the full list of vendors in this space, click here.

SoftwareReviews Gold Medal Awards recognize outstanding vendors in the technology marketplace as evaluated by their users. Gold Medals are the capstone of an in-depth software evaluation report, and awarded using a proprietary, transparent methodology based on a composite satisfaction score that averages four different areas of evaluation: Net Emotional Footprint, Vendor Capabilities, Product Features, and Likeliness to Recommend. The Net Emotional Footprint Score measures user emotional response ratings of the vendor (e.g. trustworthy, respectful, fair).

Software Reports present comprehensive evaluations of software vendors on the above elements. Software buyers can use this data to make more informed, data-driven software purchasing and renewal decisions.