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    Domino is a Leader in The Forrester Wave™: Notebook-Based Predictive Analytics And Machine Learning

    September 10, 2020   6 min read

    Today, we’re excited to announce that Domino has been named a Leader in The Forrester Wave™: Notebook-Based Predictive Analytics And Machine Learning, Q3 2020. This report evaluates 12 vendors against 26 criteria, which Forrester has grouped into three high-level categories: current offering, strategy, and market presence. According to the report:

    “Domino provides an enterprise data science platform that supports the diversity of ML options that users need in today’s rapidly expanding PAML ecosystem, with repeatability discipline and governance.”

    Built by data scientists, for data scientists

    Faced with severe competitive and other threats amplified by the events of 2020, many organizations are currently (or planning to) invest heavily in data science. They’re looking for trusted partners who can help them solve the mysteries around data science and generate the superior ROI that many vendors promise, but few deliver. For some, this urgency creates a unique opportunity to lock organizations into a walled garden to support a higher goal of selling metered compute and storage. Their closed ecosystem of developer-focused tools gives individual users the ability to solve individual data science projects, while much of the true cost of data science is buried in IT bills and DevOps headcount.

    In contrast, Domino is built by data scientists, for data scientists. We believe that our position as a Leader in this Wave reflects a unique approach that is rooted in collaboration, reproducibility, and openness. Our data science platform not only gives data scientists all the tools they want to use, but also the ability to freely collaborate as a team to unlock even greater benefits. Receiving the highest score possible in the ‘Collaboration’ criterion in this Wave underscores, in our opinion, the rich capabilities that we provide to build data science expertise at scale and apply it throughout an organization. The report states:

    “Domino tames the chaos, bringing all your different PAML tools together and binding them in a common, governed platform. It lets your data scientists use the tools they want, whether it be Domino’s own Jupyter, RStudio, and Zeppelin notebooks and integrated development environments (IDEs) or third-party tools like AWS SageMaker, DataRobot, MATLAB, and SAS.”

    Solving the last mile of data science

    But having an efficient way to build and train models is only half of the battle. Getting a model into production is also the most challenging for many organizations. In fact, Forrester recommends that “notebook-based PAML customers should look for providers that help you…operationalize AI models at scale with ModelOps”.

    Domino offers a variety of ways to deploy models into production – from apps that let business users interact with underlying models to support critical decisions, to robust APIs that allow models to be embedded into critical business systems and processes. And earlier this year we introduced Domino Model Monitor – a new kind of product that allows organizations to track the performance of all production models across an entire organization to ensure they continue to provide accurate and trusted information as the world around them changes. We believe that our innovation in this area is why we received the highest score (tied) in the ‘Model operations/ModelOps’ criterion in this report.

    Looking back and ahead to the future

    We invented the data science platform in 2014 as the enabling technology to support a greater vision – to make data science an integral part of how organizations operate all aspects of their business. Making good on that mission starts with re-thinking and optimizing the end-to-end workflow for how data science progresses from an idea to experimentation and eventually to production. It takes more than just making the process more efficient for data scientists. You also have to consider the unique needs of all of the other participants in the data science process. Failure to consider all constituents can mean the difference between data science being thought of as a misunderstood skill that helps you solve a single problem, and a first-class corporate function with a prominent place in the boardroom.

    Today, we are pleased to support data science at scale at over 20% of the Fortune 100. We have a unique vision for where notebook-based predictive analytics and machine learning platforms need to go next, and we’re looking forward to bringing that vision to our customers. We believe that Forrester feels as we do by giving Domino the highest scores possible in the ‘Solution roadmap’, ‘Ability to execute’, and ‘Enablement’ criteria.

    Download the Forrester Wave

    We’re pleased to offer a complimentary copy of this important research so you can learn more about the rapid pace of innovation that’s happening in this market, and see why Domino has been recognized as a Leader.

    Domino Data Lab

    Domino powers model-driven businesses with its leading Enterprise MLOps platform that accelerates the development and deployment of data science work while increasing collaboration and governance. More than 20 percent of the Fortune 100 count on Domino to help scale data science, turning it into a competitive advantage. Founded in 2013, Domino is backed by Sequoia Capital and other leading investors.

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