Altair’s Acquisition of RapidMiner and the Frictionless Approach to AI Will Prevent Industrial and Manufacturing Firms from Being Distracted by the Hype around AI

Subscribe To Download This Insight

By Michael Larner | 3Q 2023 | IN-6996

Altair was ranked number one in ABI Research’s latest competitor ranking for data analytics (see Manufacturing Data Analytics). The addition of RapidMiner and a strategy to remove the barriers to using Artificial Intelligence (AI) should mean that Altair will help embed AI in a multitude of settings across industrial and manufacturing firms.

Registered users can unlock up to five pieces of premium content each month.

Log in or register to unlock this Insight.


RapidMiner Morphs into Altair RapidMiner


Altair acquired data analytics and Machine Learning (ML) firm RapidMiner in September 2022. Today, Altair’s data analytics suite is branded Altair RapidMiner and promoted as a single converged platform for data analytics and Artificial Intelligence (AI). In addition, Altair RapidMiner is positioned as offering customers Frictionless AI by removing barriers that prevent individuals and organizations from using AI, such as designing interfaces for use by novice users, rather than data scientists.

After firms are acquired, their branding is often dropped shortly thereafter. It’s the opposite in this case and testament to RapidMiner’s expertise and innovative business model. The addition of RapidMiner and focus on frictionless AI will build upon the firm’s number one ranking in ABI Research’s Manufacturing Data Analytics competitive ranking report published earlier this year). AI and data analytics are technology, but also about embedding insights into the workflows of staff across the organization, rather than just data scientists, and Altair looks set to continue to be a leader in the market.

Making AI Frictionless


The Altair RapidMiner platform helps individuals create and deploy ML models. Positioning the platform as providing frictionless AI relates to removing barriers to accessing the technology (Altair RapidMiner is available via the cloud and underpinned by Altair’s capabilities in High-Performance Computing (HPC)), barriers to using AI (by providing a low/no-code interface that enables departments, teams, and individuals to perform data analytics), and potential financial barriers (customers purchase Altair Units that provide access to all of Altair’s applications).

In detail, the Altair RapidMiner platform collects and catalogs data from innumerable sources. Embedded in the platform is Altair SLC, which is a ML software that can incorporate data from cloud services, data warehouses, databases, packages, such as SPSS and Microsoft Excel, as well as CSV files and other file-based data formats.

The low-code approach enables users to quickly develop predictive analytical models, receive findings in real time, and create visualizations. The no-code functionalities include a drag-and-drop interface for novice users, a workflow builder with code-optional functionalities for intermediate users, and full-code functionalities for experts. To avoid duplication of effort and identify insights, the platform enables users to monitor projects centrally.

When considering AI-related projects, industrial and manufacturing firms do not need big teams of data scientists. Instead, subject matter experts can collect data and build ML applications themselves.

Scaling AI Requires More than a User-Friendly Interface


Applications of data analytics and ML at industrial and manufacturing firms include machine learning to support quality assurance workflows, underpinning predictive maintenance programs, and incorporating AI when designing new products. Furthermore, AI can be used when identifying and proactively preparing for operational challenges (e.g., demand forecasting, understanding the raw material availability to support inventory management, optimizing the production line while identifying potential risks, and ensuring the supply chain can deliver to customers).

Data analytics and AI require a culture shift as much as technology shift. Altair and RapidMiner both realized this. To address this need, the Altair RapidMiner Academy provides self-paced, persona-based learning for users, including a module entitled AI for Execs. There is also a Center of Excellence (COE) program to help firms prioritize use cases and upskill employees. As Manufacturing Data Analytics shows, programs of this nature differentiate vendors in an increasingly crowded marketplace.

Organizations don’t have to hire dozens of data scientists and data engineers; instead, the people who experience problems can solve them on their own. Data scientists can, for example, focus on in-depth simulations prior to launching new products and/or performing what-if scenarios, putting plans in place to resolve operational challenges.

Vendors’ portfolios are rapidly expanding, Altair RapidMiner offers 73 different products across the entire suite. This includes access to more than 60 third-party software applications, which are part of the Altair Partner Alliance. With Altair Units, customers do not need to purchase licenses for individual applications. Instead, customers purchase a pool of units for using Altair’s applications.

An example of how this works in practice is the company’s work with Soltec, a solar equipment manufacturer based in Murcia, Spain. The company uses technologies from across Altair’s portfolio to support its Research and Development (R&D) division. The team uses Altair’s simulation, data analytics, and other capabilities to both design new equipment and determine how to best orient solar panels to capture the sunlight.

By focusing on the barriers to using data analytics, ML, and AI (especially when it comes to data collection, upskilling, and budgetary constraints for new applications), Altair RapidMiner is well placed to take advantage of organizations’ needs for improving their data-centric workflows.



Companies Mentioned