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    Become a Data Science Superhero

    Suppose you find it tough getting access to the tools and technology you require to explore, 实验, and solve the big questions inside your organization. Or, can’t find and reuse past work so you always feel like you’re “reinventing the wheel” with each new project. If you’re tired of DevOps challenges and other technical issues keeping you from doing productive data science work, Domino's Enterprise MLOps platform is the solution for you.

    Domino has been designed and built by data scientists to help accelerate your research, give you the tools and other infrastructure you want to use at your fingertips, and eliminate the mundane manual tasks you need to perform when solving data science problems.

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    • Get the flexibility you need to use the tools that best suit your problem (e.g., Jupyter, RStudio, 情景应用程序, MATLAB, Spark) in an integrated environment that eliminates distractions so you can focus on solving problems.

    • Collaborate at scale with other data scientists across your organization through knowledge sharing, 实验 management, and reproducibility capabilities that supercharge your ability to work in a team.
    • Gain the benefit of a single platform that provides consistent patterns and practices on how you access data, unlock the compute resources you require, and shift a model into production at the click of a button.
     

    Three challenges that get in the way of solving data science problems

    • 筒仓: Data Science grows organically in most organizations. This means fragmented infrastructure and disconnected teams that often have no visibility or understanding into what other data scientists are working on inside the business. You end up wasting time duplicating efforts and dealing with inefficient processes.  The same thing happens in every team across the organization.

    • Friction in the data science lifecycle: You need the freedom and flexibility to explore, 实验, and ultimately solve your companies biggest challenges. You shouldn't be spending more time on technical problems related to consistent access to data, compute and production equipment than on solving the business challenge at hand.

    • Chaotic infrastructure: When you have a wild west of data science tools and infrastructure you are forced to do DevOps work for much of your day. It is impossible to collaborate with others or quickly get models into production. 和, when new packages and libraries become available, its a struggle to get them integrated into your analytic infrastructure.

    Unleash your data science superpowers

    With Domino’s Enterprise MLOps platform you can overcome DevOps and collaboration challenges.

    自由
    操作

    Self-service sandboxes give you power and flexibility while also allowing IT to centralize and govern infrastructure.

    协作
    research at scale

    Reproducibility and collaboration capabilities allow you to find and build on past work and freely collaborate to unlock new ideas and drive disruption.

    部署模型
    easily at scale

    Consistent and integrated workflows increase model velocity and provide clear patterns and practices to reduce guesswork around deployment.

    Domino 5.0 Layered Screens

    Introducing Domino 5.0

    The latest release of our Enterprise MLOps platform accelerates the end-to-end data science lifecycle – unleashing model velocity to grow revenue, improve the customer experience, and outcompete your peers.

    Learn 更多的 about 5.0

    资源 for data scientists

    博客
    Increasing Model Velocity for Complex Models
    白皮书
    Model Monitoring Best Practices

    Ready to get started with Domino?

    Dive deeper into the powerful innovations and unique benefits of the Domino Enterprise MLOps 平台 and see why over 20% of the Fortune 100 has chosen Domino.