Domino for Data Science LeadersAccelerate Data Science Project Delivery
Let’s face it, empowering your team to scale data science is hard. Outdated tools and lots of manual work make for low morale and productivity. Models don’t get deployed, or make bad predictions. Teams duplicate work with low visibility to and reuse of other data science work. As a leader, you lack visibility to model portfolios and their performance. Without the right technology, data science remains experimental and ad hoc. In fact, our recent survey found that 68% of analytics professionals believe it’s “somewhat difficult” and 37% claim it’s “very to extremely difficult” to get models into production to impact business decisions.
Domino centralizes data science infrastructure so you can scale how you manage teams and projects, improve collaboration, and accelerate project delivery.
Open & Flexible Infrastructure
Empower your team and retain top talent with self-serve access to the latest tools and infrastructure.
Built for Team Productivity
Make all work easy to find and reproduce, foster collaboration, and track all aspects of data science work.
Automate the full lifecycle, enforce best practices, and speed up delivery of high-quality model.
“The Domino platform is at the core of our modern data science environment, which has helped maximize the efficiency, productivity, and output of our data science teams, helping us drive innovation in support of our customers’ mission.”
Chief Data & Analytics Officer for Enterprise Operations
Estimate Your ROI from Domino
Consider the numbers:
- Domino saves over 200 hours per year per data scientist
- A data scientist with Domino is productive in 1 day vs. 2 weeks
- Domino saves an average of 40 hours for each model validation
- Domino reduces rebuilding time by 60 hours per model
Answer 6 questions and get a high-level estimate of the value Domino can deliver to YOUR organization based on the results of the Forrester Total Economic Impact (TEI) of the Domino Enterprise MLOps platform.
Recommended Resources for Data Science Leaders
The Practical Guide to Accelerating the Data Science Lifecycle
The need to accelerate and optimize the Data Science Lifecycle (DSLC) to achieve high model velocity has always been important. It became absolutely critical for businesses in the wake of the pandemic. Understand the DSLC, learn how to accelerate it, and how MLOps plays a critical role.
Model Velocity: The Key to Accelerating Your Model-driven Business
Model Velocity measures your company's ability to traverse the end-to-end model development and deployment process rapidly, repeatedly, and consistently.
The Complete Guide to Enterprise MLOps
Explore the underlying technologies and guiding principles found in Enterprise MLOps, and get recommendations for removing technical and non-technical barriers to success.