See why Forrester Consulting projects that organizations that use Domino will realize nearly $30 million in value over a three-year period, with an ROI of 542% and a payback in less than six months.
Too often, companies run models in production without adequately managing the risk of model drift. Or to manage it, they rely on data scientists doing manual and time-consuming work, distracting resources from future research and innovation. This whitepaper describes the common reasons and types of drift, and provides an overview of best practices for mitigating the risk of drift and monitoring to detect drift early.
While the necessity to embed AI into the business is clear, the road to get there isn’t. One question many data science leaders wrestle with is how to organize data science teams to achieve the greatest impact. (Is a Data Science Center of Excellence, or COE, the right approach?) In our conversations with nearly a dozen industry leaders building model-driven businesses, we found that there’s no one-size-fits-all answer. In this report, we break down best practices for enterprise data science across three areas (discipline, process, technology) that these leaders of high-performing global data science teams shared with us. Whether you’re early in your journey or well underway and seeking to strengthen the impact of existing efforts, their insights can help you chart the right course for your organization.
Spark is a distributed computing framework that has skyrocketed in popularity over the last several years for data engineering and analytics use cases. This paper provides a brief overview of Spark’s strengths and weaknesses in the context of data science and machine learning workflows.
One of our most popular resources, this guide shares lessons from the field on managing data science projects and portfolios.
This paper highlights how the Domino data science platform addresses governance, security, infrastructure monitoring, and other important criteria during an IT evaluation of data science solutions.
Scaling data science is the key to unlocking business value but it’s not easy to scale and most organizations haven’t figured out how to do it effectively. Get a complete understanding of the capabilities needed for enterprise data science and the level of effort needed to build a data science...
Learn 4 milestones of digital transformation for health and life sciences organizations, 6 common challenges to reaching those milestones, and best practices that high-performing research and data science teams have adopted for dismantling these challenges.
During this fireside chat, we'll talk with executives in IT and Analytics who will share first-hand experiences centralizing Data Science -- whether those efforts focused on people, process, and/or technology. They'll talk about their "before" state, where communication was lacking or processes were bottlenecked, and the steps they took to...
The chance for IT to lead in SaaS? Big data? Hadoop? Those ships have already left the port. But for enterprise data science, the time is now. CIOs have a unique opportunity to take the reins, but you need to start educating yourself right now.
Join this exclusive session for partners to see how Domino's leading data science platform is meeting the market with an open approach to help enterprises deliver data science at scale. This session will feature a lively presentation from Domino's Chief Data Scientist, Josh Poduska, as well as updates on Domino's...
Join Antoine Ly, head of Data Science at world-leading reinsurer SCOR, along with the Domino Data Lab team, to uncover how SCOR is delivering data science at scale, and how they use the Domino enterprise data science platform.
Model ethics, interpretability, and trust will be seminal issues in data science in the coming decade. This technical talk discusses traditional and modern approaches for interpreting black box models. Additionally, we will review cutting edge research coming out of academia and industry.
Join Forrester analyst Dr. Kjell Carlsson and our panel of IT and data science leaders to uncover the best practices that unlock the innovation of data science teams while simultaneously enabling IT to scale and govern their organization’s AI journey.
In this technical webinar, we address the key challenges every data science team faces when training and operationalising complex AI models at scale. Nikolay and Adam will share how Domino Data Lab facilitates knowledge discovery and collaboration in teams, enabling data scientists to use their favourite tools with a lightning-fast...
Learn how global pharmaceutical research leader Janssen Research & Development has accelerated model training on multi-GPU machines, allowing them to more quickly and accurately diagnose and characterize cancer cells through whole-slide image analysis.
Watch this webinar, hosted by Domino's Samit Thange and Bob Laurent, to learn more about the factors that can cause model performance to decrease, as well as some of the leading indicators to predict when it's time to re-train or re-build a model.
Join this webinar to experience new capabilities like on-demand Spark clusters, enhanced project management with Jira integration, ability to export models to Amazon SageMaker and Microsoft AKS certification first-hand via live demos and discussion.