Name: Unleash Data Science Across Hybrid and Multi-Cloud with Domino Nexus
Uploaded: 2022-10-04T21:39:30.000Z
Duration: 3 min
Description: Domino Nexus is a single pane of glass used to run data science and machine learning workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, providing one place to build, deploy, and monitor models.

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Spotfire, formerly known as TIBCO Spotfire, is a visual data science platform that combines visual analytics, data science, and data wrangling, so users can analyze data at-rest and at-scale to solve complex industry-specific problems.

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Domino Enterprise MLOps Platform

Data Science

Demo of the Domino Enterprise MLOps Platform

The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality and impact of data science at scale.

The Self-Service Infrastructure Portal makes data science teams more productive with access to their preferred tools, scalable compute, and diverse data sets. By automating time-consuming DevOps tasks, data scientists can focus on the tasks at hand.

The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle.

The System of Record has a reproducibility engine, search and knowledge management, and integrated project management. Teams can find, reuse, reproduce, and build on any data science work to amplify innovation.

Model monitoring capabilities ensure that all production models maintain peak performance. Automated alerts provide notification when data and quality drift occurs so users can re-train, rebuild, and re-publish the model.

Nexus is a single pane of glass to run data science and ML workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, providing one place to build, deploy, and monitor models.

Domino Data Lab powers model-driven businesses with its leading Enterprise MLOps platform that accelerates the development and deployment of data science work while increasing collaboration and governance. More than 20 percent of the Fortune 100 count on Domino to help scale data science, turning it into a competitive advantage. Founded in 2013, Domino is backed by Sequoia Capital and other leading investors.

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Domino Enterprise MLOps Platform datasheet (2-pages)

Domino Enterprise MLOps Platform overview (4-pages)

The Domino Enterprise MLOps platform helps to improve the speed, quality, and impact of data science at scale. Domino helps organizations mature data science from ad hoc experiments to a holistic system to unleash data science.

The Leader in Enterprise MLOps | Domino Data Lab

Data science done right promises organizations new levels of innovation, efficiency and growth. The Domino Enterprise MLOps platform improves the speed, quality, and impact of data science at scale. Trusted by more than 20 percent of the Fortune 100, Domino helps organizations mature data science from ad hoc experiments to a holistic system that unleashes data science.

This demo of the Domino Enterprise MLOps Platform shows how it can eliminate infrastructure friction, foster collaboration, and improve model velocity.

The Domino Enterprise MLOps Platform demo - see how you can eliminate infrastructure friction, foster collaboration, and improve model velocity.

Domino Nexus is a single pane of glass used to run data science and machine learning workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, providing one place to build, deploy, and monitor models.

Unleash Data Science Across Hybrid and Multi-Cloud with Domino Nexus

Domino Nexus is a single pane of glass that lets you run data science and machine learning workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, so you have one place to build, deploy, and monitor models.

With Domino Nexus you can:

Protect Data Sovereignty. Instead of wasting time (and money) moving data across regions to access compute resources, Nexus will bring the compute to where the data resides — a powerful paradigm shift that helps deal with data gravity in complex infrastructure. By restricting access to data by region you’ll have greater control to enforce data localization regulations, such as GDPR.

Reduce Compute Spend. Nexus will give users the choice over where workloads are processed, so you can get the right performance at the lowest possible cost. For example, you can re-direct computationally intensive workloads to on-premises infrastructure (e.g., GPU hardware clusters) to reduce monthly cloud infrastructure costs.

Future Proof Infrastructure. No company wants to be locked into a single cloud vendor, especially when recent outages expose significant business risks. With Nexus, you get the piece of mind that comes with having a hybrid/multi-cloud strategy, implemented in a way that allows you to maintain consistent operations.
 
Get more information about Nexus at https://www.dominodatalab.com/nexus.

Platform Connectivity

Ability to connect to a wide variety of data sources

Connect to Multiple Data Sources

Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion

Extend Existing Data Sources

Use R or Python to create custom connectors for any APIs or databases

Automatic Data Format Detection

Automatic detection of data formats and schemas

MDM Integration

Integration with MDM and metadata dictionaries

Data Exploration

Ability to explore data and develop insights

Visualization

The product’s support and tooling for analysis and visualization of data.

Interactive Data Analysis

Ability to analyze data interactively using Python or R Notebooks

Data Preparation

Interactive Data Cleaning and Enrichment

Access to visual processors for data wrangling

Data Transformations

Use visual tools for standard transformations

Data Encryption

Built-in Processors

Library of processors for data quality checks

Platform Data Modeling

Multiple Model Development Languages and Tools

Access to multiple popular languages, tools, and packages such as R, Python, SAS, Jupyter, RStudio, etc.

Automated Machine Learning

Tools to help automate algorithm development

Single platform for multiple model development

Single place to build, validate, deliver, and monitor many different models

Self-Service Model Delivery

Multiple model delivery modes to comply with existing workflows

Model Deployment

Tools for deploying models into production

Flexible Model Publishing Options

Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.

Security, Governance, and Cost Controls

Built-in controls to mitigate compliance and audit risk with user activity tracking

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Domino Enterprise MLOps Platform

Overview

What is Domino Enterprise MLOps Platform?