Altair Engineering, Inc.

Altair Data Analytics & AI

Composite Score

6.9 /10

CX Score

7.1 /10

22 Reviews Write a Review

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What is Altair Data Analytics & AI?

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.

Company Details

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Altair Data Analytics & AI Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Altair Data Analytics & AI.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

80 Likeliness to Recommend

6
Since last award

92 Plan to Renew

6
Since last award

69 Satisfaction of Cost Relative to Value

7
Since last award

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+80 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love Altair Data Analytics & AI?

10% Negative

14% Neutral

76% Positive

Pros

Performance Enhancing
Efficient Service
Acts with Integrity
Includes Product Enhancements

Feature Ratings

Average 75

Explainability

Feature Engineering

Algorithm Recommendation

Data Exploration and Visualization

Openness and Flexibility

Algorithm Diversity

Model Monitoring and Management

Pre-Packaged AI/ML Services

Data Ingestion

Data Labeling

Model Training

Vendor Capability Ratings

Average 72

Availability and Quality of Training

Business Value Created

Breadth of Features

Ease of Data Integration

Vendor Support

Ease of Customization

Ease of Implementation

Quality of Features

Usability and Intuitiveness

Product Strategy and Rate of Improvement

Ease of IT Administration

Altair Data Analytics & AI Reviews

mahesh m.

Role: Student Academic
Industry: Education
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Apr 2022

Very Good Product

Likeliness to Recommend

9 /10

What differentiates Altair Data Analytics & AI from other similar products?

Good performance

What is your favorite aspect of this product?

graphical user interface

What do you dislike most about this product?

till now not found any

What recommendations would you give to someone considering this product?

try and use

Pros

Saves Time
Reliable
Performance Enhancing
Enables Productivity

Role: Vendor Management
Industry: Engineering
Involvement: End User of Application

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Great product with okay features!

Likeliness to Recommend

8 /10

Pros

Inspires Innovation
Continually Improving Product
Performance Enhancing
Efficient Service

Cons

Less Reliable
Vendor Friendly Policies
Commodity Features

Role: Consultant
Industry: Other
Involvement: End User of Application

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Not Applicable

Likeliness to Recommend

8 /10

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Altair Data Analytics & AI

What is Altair Data Analytics & AI?

Company Details

Need Assistance?

Altair Data Analytics & AI Ratings

80 Likeliness to Recommend

6 Since last award

92 Plan to Renew

6 Since last award

69 Satisfaction of Cost Relative to Value

7 Since last award

Emotional Footprint Overview

+80 Net Emotional Footprint

How much do users love Altair Data Analytics & AI?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Explainability Ability to explain/ visualize the model.

Feature Engineering Ability to extract and build features from raw data.

Algorithm Recommendation Ability to recommend a best ML algorithm to use based on dataset characteristics.

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

Algorithm Diversity Provides multiple diverse ready-to-use machine learning algorithms out-of-the-box.

Model Monitoring and Management Ability to monitor model use and performance in production, incl. identifying models for refresh and/or replacement.

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

Data Labeling Ability to annotate/ label data to create a training data set.

Model Training Ability to train a model with a range of data sets that you provide.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Altair Data Analytics & AI Reviews

mahesh m.

Very Good Product

Likeliness to Recommend

Pros

Great product with okay features!

Likeliness to Recommend

Pros

Cons

Not Applicable

Likeliness to Recommend

Pros

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Feature Ratings

Explainability

Feature Engineering

Algorithm Recommendation

Data Exploration and Visualization

Openness and Flexibility

Algorithm Diversity

Model Monitoring and Management

Pre-Packaged AI/ML Services

Data Ingestion

Data Labeling

Model Training

Vendor Capability Ratings

Availability and Quality of Training

Business Value Created

Breadth of Features

Ease of Data Integration

Vendor Support

Ease of Customization

Ease of Implementation

Quality of Features

Usability and Intuitiveness

Product Strategy and Rate of Improvement

Ease of IT Administration