Data Science Resources

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.

2020 Gartner Critical Capabilities for Data Science and Machine Learning Platforms

Read Gartner’s report for insights and recommendations that gathered through a variety of customer interactions on the critical capabilities for data science and machine learning platforms.

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.

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.

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.

Guides and Reports

Forrester Wave PAML 2020

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

2020 Gartner Magic Quadrant Data Science and Machine Learning Platforms

Gartner defines the Data Science and Machine Learning Platform (DSML) category and the evolution of the market. Get the report.

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

Gartner: 15 Insights for Managing Data Science Teams

Building and managing data science teams is hard. This report from Gartner tries to make it easier. Get 15 actionable recommendations.

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.

Whitepapers

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.

Briefs

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.

Tools

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

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...

INTIENT Virtual Summit

The interactive INTIENT Virtual Summit will bring together thought leaders from your peers at the world’s leading pharmaceutical companies, experts from the Accenture INTIENT team, leaders from Google Cloud, and executives from innovative INTIENT Network partners.

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 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. The team from Lockheed Martin will talk about how Domino and NVIDIA have enabled engineers to streamline the build and deployment of machine learning capabilities…from AI competitions such...

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