Domo Partners with AI Leader to Help Customers Gain Greater Insights from Their Data

R. Bhattacharyya

Summary Bullets:

  • Many data analytics companies are beginning to embed artificial intelligence (AI) capabilities directly into their software, allowing users to reap the benefits of AI-driven insights without developing the machine learning algorithms themselves.
  • Domo is taking a different approach from some of its peers by working closely with AWS to add automatic machine learning, recommended actions, and drag-and-drop predictive model deployment in the Domo Business Cloud.

Many businesses are eager to reap the productivity and efficiency-enhancing benefits of AI. They have collected and stored vast amounts of data but face challenges when it comes to uncovering the nuggets of insight that can improve operations, enhance customer service, and speed faster and more informed decision-making. One of the biggest hurdles to AI adoption is a lack of resources. Building, training, tuning, and deploying machine learning models is a lengthy process that requires the expertise of expensive data scientists and AI experts. Many businesses don’t have these resources readily available; nor do they have the time or money to invest in acquiring them.

In response, many data analytics companies are beginning to embed AI capabilities directly into their software. This allows users to reap the benefits of AI-driven insights without spending the time or money to develop the machine learning algorithms themselves. Early movers such as SAP and Salesforce built their own AI platforms to power their solutions. For example, in addition to offering its SAP Data Intelligence platform (which includes data orchestration as well as AI model development and management for AI-experts), SAP also offers pre-trained and re-trainable AI services. The pre-built AI services are either directly embedded into its products to provide easily accessible intelligence or are available as standalone APIs. They include SAP Customer Retention, SAP Cash Application, SAP Document Information Extraction, SAP Invoice Processing, and several others, including industry-specific solutions.

Similarly, Salesforce developed and operates its Einstein AI platform. Einstein’s automated machine learning services are built into Salesforce apps and are largely configurable by a Salesforce admin who is unskilled in machine learning. The data is already in Salesforce, so no heavy data prep is required; and Salesforce’s AutoML automatically chooses the algorithm and hyperparameters, so no data scientist is required. The platform automatically generates insights, real-time predictions, and recommendations. It also powers AI-driven insights in Salesforce solutions such as Einstein Recommendation Builder, Field Service Analytics, Fundraising Analytics, Pipeline Analytics, and many more.

More recently, at the Domopalooza 2020 customer event, Domo unveiled that it would also be offering AI-driven insights on its platform. On March 19, Domo announced that it was adding new capabilities in the Domo Business Cloud, including automatic machine learning, recommended actions, and drag-and-drop predictive model deployment. Noteworthy is that the company is taking a different approach from some of its peers, opting to work closely with AWS instead of developing its own platform from the ground up. Domo’s AI-driven insights will be powered by Amazon SageMaker Autopilot. The service automatically trains and tunes machine learning models; after inspecting customers’ Domo data sets, SageMaker Autopilot determines the optimal data preprocessing steps, machine learning algorithms, and hyperparameters to train a prediction pipeline.

The move by Domo to partner with AWS is a wise one; it speeds Domo’s time to market with new capabilities and leverages the expertise of a well-known leader in the AI space. It enables users to more easily and quickly uncover the insights in their data and brings the learnings of AI to a broader audience. Furthermore, knowing that the results are driven by a solution from AWS will inspire greater confidence in the findings and, in turn, will be more likely to lead to action. (Similarly, AWS users can benefit from Domo’s strength in making data more understandable and shareable by lines of business.) Additionally, the time is right. Users increasingly expect AI to be brought to them, as evidenced by the proliferation and popularity of operationalized AI-driven solutions. There will always be those organizations that require an in-house team of machine learning experts to develop and manage customized applications, but for many, solutions already embedded with AI capabilities are exactly what they need.

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