Molecula Included in 2021 Gartner® Hype Cycle™ for Data Science and Machine Learning Report

By: Molecula  |  August 23, 2021


Molecula, an operational AI company that enables businesses to deploy real-time analytics and AI in their applications through the adoption of a feature-first mindset, today announced it was mentioned as a Sample Vendor in 2021 Gartner Hype Cycle for Data Science and Machine Learning¹. Gartner identified Molecula as a Sample Vendor for feature stores. Feature stores are solutions built to address the need for data reusability, reproducability, and reliability in machine learning (ML) portfolios.

Each Hype Cycle breaks the technology lifecycle into five key phases: Innovation Trigger, Peak of Inflated Expectations, Trough of Disillusionment, Slope of Enlightenment, and Plateau of Productivity. Molecula was included within the Innovation Trigger phase.

Gartner notes, “Organizations want to expand their use of ML but find that data scientists spend more time sourcing and preparing data to create training and test datasets than developing the ML models.”

Continuing, “There can be considerable overlap in features used by ML models, and therefore, the ability to reuse these features across models would lead to faster development times. However, feature engineering within data science teams is typically a siloed practice, occurring on individual machines. Organizations need a mechanism to break down these analytical silos to enable the reusability of features across ML workloads.”

Molecula’s FeatureBase enables truly real-time use cases through the elimination of pre-processing, unlocking a wealth of opportunity for companies of all sizes to transform their investment in big data into tangible business outcomes.

“Our mission is to make features (not data) the foundation for real-time analytics and AI,” said Mandy Sadowski, SVP of Marketing at Molecula. “Our feature-first approach makes model-ready data accessible, usable, and re-usable across organizations, dramatically reducing the time and effort required to get models into production. We believe that being named by Gartner as a Sample Vendor in the Hype Cycle for Data Science and Machine Learning 2021 reinforces the value we’re delivering to customers as organizations strive to unlock the potential of AI.”

Molecula’s FeatureBase is a feature extraction and storage technology that enables real-time analytics and AI initiatives. FeatureBase is an overlay to conventional big data systems that automatically extracts features, not data, from each of the underlying data sources or data lakes and stores them in one centralized feature storage platform. FeatureBase maintains up-to-the-millisecond data updates with little to no upfront data preparation. This is achieved by reducing the dimensionality of the original data, effectively collapsing conventional data models (such as relational or star-schemas) into a highly optimized format.

¹ Gartner, “Hype Cycle for Data Science and Machine Learning,” by Analysts Farhan Choudhary, Alexander Linden, Jim Hare, Pieter den Hamer, Shubhangi Vashisth, August 2, 2021.


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