Data Science Resources

Featured Resource

Introducing the world’s first data science book for kids!

Florence the Data Scientist and Her Magical Bookmobile

Forrester: The Total Economic Impact of the Domino Enterprise MLOps Platform

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.

Model Monitoring Best Practices

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.

Organizing Enterprise Data Science

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.

The Pros and Cons of Spark in a Modern Enterprise Analytics Stack

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.

Managing Data Science at Scale

One of our most popular resources, this guide shares lessons from the field on managing data science projects and portfolios.

IT Evaluation Guide

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.

Guides and Reports

A Guide To Enterprise MLOps

Enterprise Machine Learning Operations (MLOps) allows organizations to scale data science by progressing through the data science lifecycle faster with enterprise capabilities that are required to do this safely and universally.

How to scale data science (when nobody else understands it)

Domino has partnered with DataIQ to survey their membership of data and analytics professionals to understand more about their approaches to data science.

Forrester Wave PAML 2020

See Why Forrester Named Domino a Leader in the Wave for the second time in a row.

Top 10 Questions for IT Leaders

This document provides IT leaders with the top 10 questions to ask of data science platforms.

451 Research Report - Security is a Vital Linchpin for Enterprise Data Science

See why security features headline a growing list of crucial components that you have to consider when selecting an enterprise data science platform.

What IT Leaders Need to Know About Data Science

Your Guide to Understanding Modern Data Science and Why IT is Critical to its Success

Succeeding with Data Science in Financial Services

Learn how organizations unleash innovation without sacrificing transparency or governance.

Data Science Manager Survey Report: Key Factors on the Journey to Become Model-Driven

Survey results from 250 data science leaders and practitioners across organizations of all sizes and a variety of industries.

Top 10 Pharma Analytics Solutions

This edition of Pharma Tech Outlook magazine brings you the “Top 10 Analytics Solution Providers – 2019.” Domino is featured as a leader.

451 Research on Domino

Read this report to get 451 Research's take on Domino Data Lab's product strategy.


Pump Up Data Science Productivity with a Modern Workbench

As data science practices scale, productivity suffers because workbenches aren’t built to leverage the work of large data science teams. Domino’s enterprise MLOps platform has been developed with unique workbench capabilities for data science productivity.

The True Cost of Building a Data Science Platform Whitepaper

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...

Kubernetes: The IT Standard for Data Science Workloads

Learn why Kubernetes is a great fit for data science workloads, and how it is becoming the platform infrastructure layer for the cloud. Explore the requirements for tailoring Kubernetes for data science.

Navigating the Life Sciences Journey to a Modern Statistical Computing Environment

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.

Model Risk Management in Domino

Model Risk Management is a framework that combines sound governance principles with end-to-end documentation in the design, development, validation and deployment of new models in the business.

Data Science Maturity Model Whitepaper

Identify capability gaps and direct future investment with this model.

Build or Buy? Understanding the True Costs of a Data Science Platform

This paper presents a framework to facilitate the decision process of building or buying a data science platform.

Attention, CIOs: Do You Know Where Your Data Scientists Are?

Learn how to wrangle data science tools and technologies, support your data scientists' compute needs in the cloud, and prevent shadow IT.

Model Management: A Framework to Build a Model-Driven Business

Learn how to leverage models for a competitive advantage and avoid the Model Myth.

Data Science in the Cloud

How to get the most out of moving data science to AWS.


Accelerate SAS Adoption with Domino

This paper illustrates in three simple steps how to use SAS for Containers on Domino for SAS research and model deployment.

Best Practices for Managing Your Team in Domino

Learn how leading organizations use Domino to manage their teams.

Domino Collaboration Brief

Lessons from the field on managing data science projects and portfolios.

Domino Control Center Brief

Learn how Domino Control Center helps data science and IT leaders govern how their organizations use critical compute and software resources.

Domino Lab Tech Brief

Learn how Domino Lab accelerates research and maximizes data science productivity.

Domino Launchpad Brief

Learn how Domino Launchpad addresses the operational challenges companies face getting models into production (ie, ModelOps).

Domino and AWS Tech Brief

Develop and deliver models faster, scale rapidly, and reduce regulatory and operational risk in the cloud.

Domino for Data Science Leaders Tech Brief

Learn how Domino helps you enable and scale a model-driven organization.

Domino for Data Scientists Tech Brief

Learn how Domino helps data scientists drive breakthrough research and deliver high-impact models.

Domino for IT Leaders Tech Brief

Learn how Domino addresses key pain points for IT leaders so they can deliver and govern high-impact models with confidence.

Answers to Top 10 Questions for IT Leaders

This document provides IT leaders with answers to how Domino addresses the top 10 questions to ask of data science platforms.

NVIDIA DGX-Ready Software Solution

Domino and NVIDIA together make NVIDIA GPU resources available on the NVIDIA certified Domino enterprise data science platform.

Data Science Innovation in Credit and Finance Analytics

Domino on AWS provides an efficient, scalable, and secure data science platform.

SAS for Containers on Domino

Accelerate SAS and save on CapEx — take it to the cloud.

How to Evaluate a Data Science Platform

IT and Analytics Leaders: Thinking too narrowly about your data science platform can prove costly.


Data Science Management Kit

Resource bundle for current and aspiring data science leaders.

Data Science Hiring and Onboarding

This hiring and onboarding plan template walks data science leaders through key questions to help find and train new data scientists on your team.

Pre-Flight Project Checklist

This pre-flight project checklist walks data scientists and data science leaders through an ideal set of upfront actions.

Top Data Science Articles

Our most popular articles for data scientists. Learn techniques from insights, tips, and tutorials.

Videos and Webinars

Unlock 542% ROI for Customers - Learn about Domino's Partner Program | Partner Webinar #2

Join this session for both current and prospective channel partners to see how Domino's leading enterprise MLOps platform is enabling model-driven businesses to accelerate the development and deployment of data science work while increasing collaboration and governance.

Forrester TEI Webinar: Driving 542% ROI with the Domino Enterprise MLOps Platform

Join us for a live webinar where Dr. Kjell Carlsson, Principal Analyst, Forrester, will describe some of the key challenges organizations face when scaling data science.

Running complex workloads using on-demand GPU-accelerated Spark/RAPIDS clusters

We'll present an integrated solution based on the Domino Data Science Platform, NVIDIA NGC containers, and RAPIDS Accelerator for Apache Spark, which enables data scientists to easily provision a Spark/RAPIDS cluster with an arbitrary number of GPU-accelerated workers, and access it through their favorite integrated development environment.

How Johnson & Johnson is embedding data science across their business

Johnson & Johnson’s CIO Jim Swanson and Domino CEO Nick Elprin discuss building an MLOps strategy to achieve model velocity.

How AES went from zero to 50 deployed models in two years

In <2 years, AES built out a global team, its underlying infrastructure, and they’ve built and deployed 50+ models to date.

Domino Data Lab and Amazon SageMaker: Model management and monitoring for the Enterprise.

Join this session to learn about real-world, industry-specific scenarios with data science experts from AWS and Domino Data Lab as they discuss the importance of a “single pane of glass”.

Succeeding in the Digital Age - How Can Data Science Leaders Play a Critical Role in Their Organisation’s Modernisation Journey?

Watch this session to hear industry-leading CDAOs discuss all about digital transformation.

View the Keynote Address by Daniel Kahneman: The Psychology of Intuitive Judgment & Choices

Insights from Dr. Kahneman on how his research applies to today’s analytical professionals.

Don't Miss the Boat, CIOs — Lead Your Team to AI Excellence

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...

Accelerating Data Science: Unlock Model Velocity

How do you measure the impact of data science? In this fireside chat, we’ll discuss a new way to frame and benchmark the ROI of your data science team’s work: Model Velocity.

Don't Miss the Boat, CIOs ― Lead Your Team to AI Excellence

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.

UBS’s Modern Data Science Stack

How their risk modeling platform on Domino blends SAS & open source analytics software for a fast path to the cloud.

Unlock Enterprise Data Science and MLOps at Scale with Domino: Partner Webinar

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...

SCOR's Creation of Data Science Center of Excellence to Enhance Model Deployment

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.

A Data Science Playbook for Explainable AI - Navigating Predictive and Interpretable Models

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.

Reaching Across the Aisle: Data Science & IT Build a Better Enterprise

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.

How to Simply Run Complex AI Training & Inference Workloads with Domino & NVIDIA

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...

Seamless Virtual Collaboration Across Life Sciences

Today, many organizations are looking to determine the optimal way for organizing their data science talent.

Fireside Chat: Building Your Best Data Science Team

These are some of the topics we'll dig into during this fireside chat between two long-time analytics team leaders – John Thompson and Dave Cole.

How Janssen R&D Accelerated Model Training on Multi-GPU Machines for Faster Cancer Cell Identification

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.

How Lockheed Martin is Pushing the Boundaries of Rocket Science with Data Science

Our missions are some of the most important and challenging in the world...from protecting our citizens to advancing the boundaries of science.

Data Science Leadership Exchange: Best Practices for Driving Outcomes

Despite an increasing awareness of the role data science plays in successful business outcomes, data science leaders still struggle to organize, implement and communicate effective data science initiatives.

DataOps, the Secret Weapon for Delivering AI, Data Science, and Business Intelligence Value at Speed

In this session, Moneysupermarket Group’s Chief Data Officer Harvinder Atwal will discuss how he’s implemented a DataOps approach at Moneysupermarket.

A Strong Data Science Community in a Decentralized Org

Today, many organizations are looking to determine the optimal way for organizing their data science talent.

Monitor the Health of All Your Models: Introducing Domino Model Monitor

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.

Explore the Future of Enterprise Data Science: What’s New in Domino 4.2

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.

Increasing Model Efficiency: Model Risk Management

In this live webinar, David Bloch and Nikolay Manchev present the missing piece of Model Risk Management solutions: a multi-language reproducibility engine for model development efficiency.

Solving Expert Problems With NLP Algorithms In Insurance

During this session, Topdanmark’s Head of Machine Learning Stig Pedersen will discuss his team’s journey into machine learning, and will describe how they orchestrated their data lake and data science environment to build and deploy models.

Modernize Your Statistical Computing Environment

In this live webinar, Domino Data Lab’s general manager for Health and Life Sciences will discuss challenges we’ve encountered across global health and life sciences research teams.

How Dell & Domino Are Helping IT Govern the AI/ML Ecosystem

Learn how Dell and Domino created a refreshingly simple, building-block-based approach to help companies get their data science teams--and the technologies they need--up and running faster, with an easy path to scale.

Generative Adversarial Networks (GANs): A Distilled Hands-On Tutorial

Learn about the GAN framework, how to implement a basic GAN model, how to generate training samples, and more.

Monitoring Models at Scale

Join this webinar to learn how Domino can help you monitor your models at scale.

Towards Predictive Accuracy

In this code webinar, Dr. Mark Fenner covers: Building a pipeline for automating ML workflow; Core concepts, incl cross-validation; How to select and tune hyperparameters.

Machine Learning Vital Signs

Donald Miner details the tracking of machine learning models in production to ensure model reliability, consistency, and performance into the future.

Turbo-Charging Data Science with AutoML

In this webinar, we will dive into popular open source and proprietary AutoML tools such as auto-sklearn, TPOT, MLBox, AutoKeras, and H2O Driverless AI.

Best Practices for Getting Data Science Web Apps in Production

In this webinar we’ll review the pros and cons of the top data science web app frameworks (Shiny, Dash, Flask, etc.)

A Data Science Playbook for Explainable ML/AI

This technical talk discusses traditional and modern approaches for interpreting black box models.

Providing Unprecedented Transparency into the Health of Data Science Teams

Learn how Domino 3.5 allows data science managers to define their own data science project life cycle, and easily track and manage projects

Data-driven to Model-driven

In this webinar, Forrester Research and Domino will demystify the model-driven business.

Data Science Leaders Summit

Two days of practical sessions, thought-provoking discussions, and forward-looking solutions. Enjoy the entire conference on demand for free.

Webinar: Accelerating the Impact of Data Science Teams

Join this 30 minute webinar to learn how Domino 3.4 accelerates the impact of data science teams with: Datasets, Experiment Manager, Activity Feed

Solving ModelOps (Video)

Data science and the impact it will have on business and society has never been more hyped. Yet the reality is very few organizations today are getting business value from their data science (or AI) investments.

SAS Demo

Watch how SAS, Domino Data Lab, and AWS have teamed up to deliver SAS for Containers on Domino.

Managing Data Science at Scale (Video)

In this webinar, we'll share learnings and how we see the market approach challenges in data science.

GPU Computing for Data Science (Video)

Ways to incorporate GPU computing for computationally intensive tasks.

Apps in Domino (Video)

Watch this webinar to review a survey of the landscape of interactive visualization (Shiny, Dash, etc) tools and learn some best practices for publishing them within Domino.

Moody's on Domino and AWS

Learn how Moody’s Analytics is pushing the envelope in the financial services market.

Dun & Bradstreet seal