Altair Named a Leader in the June 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms

Altair with its data analytics and AI/ML platform RapidMiner has been ranked among the industry leaders by Gartner Inc.

Gartner Inc. is a recognized consulting company that tracks and evaluates technology trends and compares the approaches of each major vendor in their respective disciplines. It has become famous for its so-called Magic Quadrant, where it graphically ranks vendors and their position in the market. It tracks the completeness of their vision and ability to execute and implement solutions. These parameters then form the axes of the resulting graph. By comparing each other, the individual companies compared then fall into quadrants: the Leaders score highest in both vision and implementation capability. Challengers have well-established products, and a strong market position, but lack the size and influence of Leaders. Visionaries have interesting products but cannot achieve smooth operations, financial stability, or gain significant market share. Niche Players are typically smaller players with a specialized, established solution, often dedicated to a market segment or vertical. However, there can also be large companies that are just adapting their existing product for new markets.

Gartner defines a data science and machine learning platform as an integrated set of tools and libraries that support independent use and foster collaboration between data scientists and their “business” and IT counterparts at all stages of the data science lifecycle. Thus, DSML platforms should support both a visual low-code/no-code environment for the less experienced and an advanced toolset for advanced coders developing specific features.

The required models must be able to be built on all types of structured and unstructured data, including tables, images, video, and text for applications that require computer vision or natural language processing.

Supported machine learning techniques range from classical regression or decision trees to more complex deep learning, reinforced learning, and GenAI. The models created using these techniques can be used for tasks within a variety of business processes such as credit scoring, churn prediction, predictive maintenance, quality management, or image classification.

A proper DSML platform must also support the post-implementation phase of the models. Models deployed into production need to be tested, updated, adapted, or discarded when input conditions change.

And how does Altair stand in the discipline of Data Science & Machine Learning?

According to Gartner, Altair is in the Leaders quadrant. The RapidMiner platform, with products like AI Hub, AI Studio and others, accelerates access to data insights and predictive models by enabling collaboration between data specialists and business teams.  Altair’s operations are geographically diversified, and its clients tend to be midsize to large enterprises in industries across industries. It is investing in the development of conversational interfaces for an even greater ability to engage users from business teams. It addresses the use of AI, particularly in the enterprise sphere, developing solutions for IoT and HPC, and betting on the convergence and synergy of these technologies and their other products. Altair has traditionally been strong in industrial solutions, particularly in engineering and manufacturing.

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