Data science is one of the fastest growing segments of the tech industry, and Alteryx, Inc. is front and center in the data revolution. The Alteryx Platform provides a collaborative, governed platform to quickly and efficiently search, analyze and use pertinent data.

To continue accelerating innovation, Alteryx announced it has purchased a startup with roots in the Massachusetts Institute of Technology (MIT). Feature Labs “automates feature engineering for machine learning and artificial intelligence (AI) applications.”

Combining the two companies’ platforms and engineering will result in faster time-to-insight and time-to-value for data scientists and analysts. Feature Labs’ algorithms are designed to “optimize the manual, time-consuming and error-prone process required to build machine learning models.”

Feature Labs makes its open-source libraries available to data scientists around the world. In what is no doubt welcome news, Alteryx has already committed to continued support of the open-source community.

From the Press Release:

“Feature Labs’ vision to help both data scientists and business analysts easily gain insight and understand the factors driving their business matches the Alteryx DNA. Together, we are helping customers address the skills gap by putting more powerful advanced analytic capabilities directly into the hands of those responsible for making faster decisions and accelerating results. We are excited to welcome the Feature Labs team and to add an engineering hub in Boston,” said Dean Stoecker, co-founder and CEO of Alteryx.

“Alteryx maintains its leadership in the market by continuing to evolve its best-in-class, code-free and code-friendly platform to anticipate and meet the demands of the 54 million data workers worldwide2. With the addition of our unique capabilities, we expect to empower more businesses to build machine learning algorithms faster and operationalize data science,” said Max Kanter, co-founder and CEO of Feature Labs. “Feature engineering is often a time-consuming and manual process and we help companies automate this process and deploy impactful machine learning models.”