Domo Introduces the Domo Business Automation Engine, the First-of-its kind Orchestration Layer Across All Data, Systems and People in an Organization

Taps the Power of the Domo Platform and Machine Learning to Close the Gap from Insights to Action

Silicon Slopes, UT – Domopalooza 2019 – March 20, 2019 –Today Domo (Nasdaq: DOMO) announced the Domo Business Automation Engine (BAE), an orchestration layer in the Domo platform that leverages machine learning and advanced alerting capabilities to help organizations coordinate intelligent, event-based workflows and shorten the time from insights to action. Domo BAE is the first-of-its-kind orchestration layer to work across all data, systems and people in an organization.

“Data only has business value if organizations are able to do something with it and those that move quickly create a competitive edge,” said Adam Landefeld, senior vice president of product, Domo. “Domo puts data into the hands of everyone across the organization and now the Domo Business Automation Engine helps turns that data into action more quickly than ever before possible.”

The Domo BAE goes beyond notification-style alerting to deliver suggested tailored actions directly into the hands of individual employees and allows them to initiate those actions directly from their phones.  Through this process, Domo’s advanced alerting engine can generate customized links to third-party systems where those actions can take place or link back into Domo. It also can kick off third-party workflows or even write data into another system of record – all based on the triggered alert.

As more data, systems and people get connected into the Domo platform, the more intelligent the Domo BAE becomes about connecting individuals with their specific actions that can drive the business forward.

A retailer, for example, might have its data scientists use Domo’s Data Science Suite to create a data model that predicts changes to loyalty buying behavior. These predictions would then be analyzed by Domo’s alert engine. When there is a predicted change in behavior, the retailer’s product buyers would receive an alert that would give them a clear picture of what is happening in the business and help drive them toward the best actions to take. When the prediction is up, for example, the system might automatically provide a link to the inventory control system to let the buyer know that more of a particular product may be needed. When the prediction is down, the buyer might receive a custom-built link that triggers an action in the marketing promotion software to launch a promotion to spark more buyer interest.

The Domo BAE is one of three new machine-learning capabilities announced today at Domopalooza to accelerate predictions and advanced insights that drive business value. These new features put the power of machines to work on data, allowing data scientists to spend less time on the manual, time-consuming tasks of finding and cleansing data and more time applying their skills and talents to building models, as they were trained to do.

“Significant investments have been made gathering data into systems, data lakes and data warehouses and that data is always growing, yet most organizations haven’t been able to extract its full value,” said Catherine Wong, chief product officer and EVP of engineering, Domo. “Domo puts the power of machine learning across all of your data, no matter where it comes. You simply just have to connect it.”

Two additional data science features announced today at Domopalooza include the following:

Did You Know

Did You Know, a part of Mr. Roboto, is a new capability that surfaces automated insights, personalized to the user, based on all the data that has been connected to the Domo platform. The power of Did You Know increases as more data gets brought into the Domo platform. It uses machine learning to constantly scan all incoming data to automatically learn and create data classifications for that data that are used to detect trends, relationships, anomalies or correlations that otherwise would be humanly impossible to detect in a useful timeframe. Did You Know allows the user to validate the impact of suggested insights with a simple training feedback loop of “useful vs. not-useful” signals, which is then used to refine the personalization of the offered insights. This is the first platform working to create data classification on any structured or unstructured data.

New Domo Data Science Suite Integrations with Jupyter and Amazon SageMaker

Domo today announced two new integrations to help customers easily take advantage of data science for their business. These integrations allow customers to apply predictions from these two industry-leading offerings directly into Domo’s data pipeline. The first integration is with Jupyter, a collaboration tool for writing and sharing code and text. It allows data scientists to leverage all their Domo datasets in their Jupyter notebooks. Though this integration, data scientists no longer have to pull data out into a separate data store, find insights and then pipe the insights back into Domo. The second integration is with Amazon SageMaker, a leading, fully-managed service that enables data scientists and developers to quickly and easily build, train and deploy machine learning models at any scale. This new integration with Amazon SageMaker provides an easy way for data scientists to apply models, as well as visualize and distribute predictions and insights found through SageMaker, directly in Domo. For more information on the SageMaker integration, see today’s press release: https://www.domo.com/news/press/domo-amazon-sagemaker-integration/.

These announcements build on AI/ML capabilities that Domo released earlier this year to automate business tasks, enhance customers’ experience with the Domo platform and make it easier for organizations to tap into the unique skills of data scientists to implement their own AI technologies and make data a living breathing part of their IT stack. Some of these advancements introduced in the last year include:

• Narrative Insights – a feature which leverages Natural Language Generation technology to surface text-based insights about data;
• Automatic DataSet Statistics, which provide algorithms on every column in DataSets with interactive controls to allow on-the-fly filtering and segmentation; and,
• The Domo Data Science Suite – tools that provide in-platform functionality with new R and Python scripting components as well we pre-packaged Data Science action tiles for common Data Science functions.

For more information about the Domo’s Data Science Suite, AI and Machine Learning capabilities, visit: https://www.domo.com/apps/data-science-suite.

About Domo
Domo’s mission is to be the operating system for business, digitally connecting all your people, your data and your systems, empowering them to collaborate better, make better decisions and be more efficient, right from their phones. Domo works with many of the world’s leading and most progressive brands across multiple industries including retail, media and entertainment, manufacturing, finance and more. For more information about Domo (Nasdaq: DOMO), visit www.domo.com. You can also follow Domo on Twitter, Facebook and LinkedIn.

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This press release contains forward-looking statements as defined within the meaning of the U.S. federal securities laws, including statements regarding the results and benefits from using the new Domo Business Automation Engine, the Did you Know feature, and Domo Data Science Suite integrations, and how such new features may accelerate predictions and advanced insights that drive business value, the expected increased utilization by Domo customers of the Domo platform, empowerment of Domo customers to monetize, share, and otherwise better leverage their data, and related anticipated results. These statements are based on information, expectations and assumptions as of the time of this press release with respect to future events and business performance and are subject to risks and uncertainties that may cause actual performance or results to differ materially from those expressed in or suggested by the forward-looking statements, including but not limited to the risks set forth in our Registration Statement on Form S-1, as amended, and our other filings with the U.S. Securities and Exchange Commission. Forward-looking statements should not be read as a guarantee of future performance or results, and they will not necessarily be accurate indications of the times at, or by, which such performance or results will be achieved, if at all. We do not undertake any obligation to publicly update or revise any forward-looking statement, whether as a result of new information, future developments or otherwise.

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