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    By enabling both our advanced and low-code team members with a common platform to deliver AI and ML with Domino, we can accelerate the innovative use of our data across a wide variety of technical and non-technical data practitioners and data-adjacent parts of our business.

    Sean Otto, PhD., Director of Analytics at AES Corporation
    Upskill analysts and domain experts

    Close the talent gap

    The data science talent gap is ever-increasing. Domino empowers “low code” analysts and data scientists to work in R and Python alongside more advanced data scientists. That unlocks more capacity for your team, while upskilling your workforce.

    • Analysts who learn code can advance their careers into data science, improving recruitment and retention.
    • Data scientists can easily mentor and collaborate with analysts since everyone is speaking the same language(s).
    • Novice R and Python coders will rapidly gain skills using Domino Code Assist and a searchable repository.
    Provide professional tools for everyone

    Unify on a common platform

    Maximize the productivity and impact of your analysts and data scientists by enabling them to collaborate and work together on Domino. By using tools like Domino Code Assist, analysts can easily generate code in Python or R. They all get access to professional coding languages, packages, tools, and a unified compute infrastructure. All of the necessary data is easy to find, access, and manage. This unification eliminates silos across your team and avoids costly duplication of effort by easily standardizing and reusing code. Governance and security processes are consistently applied.

    • Novice coders can build on the work of experts with access to code libraries and examples.
    • Rapid code iteration and team collaboration lead to innovation and delivery of high-performing models and analyses.
    • Models are fully reproducible regardless of who built them and the data, languages, or tools used.
    Code is King

    Deliver higher business value

    Data and analytics leaders are under greater pressure to deliver value than ever before.  No-code options just haven't lived up to their promise, leading to siloed projects, limited talent pools, one-off insights, and POCs that never make it to production.  Leading organizations are shifting their focus to building a broad talent base of analysts with Python, R, and other coding skills.

    • Code is fast, flexible, transparent, and efficient to write, edit and reuse.
    • Python and R are the gold standards for analysis and data science.
    • Data science innovations are created with code.

    To address the growing AI skill shortage, 42% of organizations say they are upskilling/reskilling existing employees.

    S&P Global Market Intelligence, Highights from the VotE: AI and Machine Learning, January 2023

    Learn More

    Python is the New Excel
    It's becoming clear that the traditional "citizen data scientist" approach, focusing on no-code tools, has become an evolutionary dead end. Why? 
    A New Approach to Scaling Data Science and Analytics Talent
    A new path for companies to transform their data science talent strategies.

    Talk to a product expert

    Join a live demo today or talk to an expert to learn how Domino can help you democratize AI with code.