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Alteryx Helps Accelerate Deployment and Management of Machine Learning Models on Amazon Web Services

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Alteryx Demonstrates Proven Customer Success and Technology Proficiency in Machine Learning

IRVINE, Calif. (Nov 29, 2017) — Alteryx, Inc. (NYSE: AYX), a leader in self-service data analytics, today announced that customers can take advantage of one-click, self-service predictive model deployment capabilities of the Alteryx solution on Amazon Web Services (AWS). Alteryx has also achieved Amazon Web Services (AWS) Machine Learning (ML) Competency status. The designation recognizes Alteryx for providing business analysts, data scientists and ML practitioners with automated, cutting-edge tools to create and deploy predictive models on AWS.

Deployment of predictive models continues to be a major challenge for many companies, with only 13% of data scientists surveyed by Rexer Analytics saying their models always get deployed. Alteryx Promote was designed to help customers address the labor-intensive process of getting models into production by providing an end-to-end data science system for developing, deploying and managing predictive models and real-time decision APIs. Alteryx Promote was also designed to allow data scientists and analytics teams to build, manage and deploy predictive models to production faster — and more reliably — without the need for writing any custom deployment code.

"Our analytics team was losing ownership of our predictive models and we wanted something that was easy to deploy, reliable, and worked within our AWS production environment," said Mark Gately, director of decision science at Tendril, Inc. "The Alteryx solution allows Tendril's Data Analytics team to control models through the entire data science lifecycle, from prototyping through to development and retraining."

The AWS Competency program highlights AWS Partner Network (APN) members that have passed a rigorous audit of their security, architecture and customer adoption.  Alteryx has exhibited proven success in the ML category, which recognizes solutions that give data scientists and ML practitioners the tools to take their data to the next level as actionable predictive models.

"Clean and annotated training data is the foundation of modern machine learning," said Joseph Spisak, global lead for machine learning partnerships, Amazon Web Services, Inc. "It fuels state of the art algorithms in computer vision and natural language understanding; however, acquiring it takes time and resources. We are very excited to have Alteryx join the Machine Learning Competency Program to help our customers spend less time preparing their data and more time creating intelligence."

"So many of our customers are turning to AWS to increase agility, scalability and performance as organizations integrate data and analytics into the very fabric of their business," said Ashley Kramer, vice president of product management at Alteryx. "We're thrilled to have achieved AWS ML Competency status and look forward to serving our customers with ML capabilities on AWS."

About Alteryx, Inc.

Alteryx Inc., headquartered in Irvine, CA, offers a quick-to-implement, self-service analytics that empowers business analysts and data scientists alike to break data barriers and deliver game-changing insights that are solving big business problems. The Alteryx solution is self-serve, click, drag-and-drop for hundreds of thousands of people in leading enterprises all over the world. Visit or call 1-888-836-4274.

Alteryx is a registered trademark of Alteryx, Inc. All other product and brand names may be trademarks or registered trademarks of their respective owners.

Safe Harbor Statement

This press release contains forward-looking statements that involve risks and uncertainties, including statements regarding its product, Alteryx Promote, which is anticipated to be generally available in 2018, and its anticipated capabilities, including the development, deployment and management of predictive models and real-time decision-making. These forward-looking statements are only predictions and may differ materially from actual results due to a variety of factors including, but not limited to: our ability to develop and release product and service enhancements and new products and services to respond to rapid technological change in a timely and cost-effective manner; intense and increasing competition in our market; and other general market, political, economic, and business conditions.

Additional risks and uncertainties that could affect our business are included in the Risk Factors section of our Quarterly Report on Form 10-Q for the six months ended September 30, 2017. All forward-looking statements contained herein are based on information available to us as of the date hereof and we do not assume any obligation to update these statements as a result of new information or future events.