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What is Domino Enterprise MLOps Platform?
The Domino Enterprise MLOps Platform enhances the efficiency, quality, and influence of data science on a large scale, providing data science teams with the tools they need for success. With its open and adaptable framework, Domino allows experienced data scientists to utilize their favorite tools and infrastructures seamlessly. Models developed within the platform transition to production swiftly and maintain optimal performance through cohesive workflows that integrate various processes. Additionally, Domino prioritizes essential security, governance, and compliance features that are critical for enterprise standards.
The Self-Service Infrastructure Portal further boosts the productivity of data science teams by granting them straightforward access to preferred tools, scalable computing resources, and a variety of data sets. By streamlining labor-intensive DevOps responsibilities, data scientists can dedicate more time to their core analytical tasks, enhancing overall efficiency.
The Integrated Model Factory offers a comprehensive workbench alongside model and application deployment capabilities, as well as integrated monitoring, enabling teams to swiftly experiment and deploy top-performing models while ensuring high performance and fostering collaboration throughout the entire data science process.
Finally, the System of Record is equipped with a robust reproducibility engine, search and knowledge management tools, and integrated project management features that allow teams to easily locate, reuse, reproduce, and build upon existing data science projects, thereby accelerating innovation and fostering a culture of continuous improvement. As a result, this comprehensive ecosystem not only streamlines workflows but also enhances collaboration among team members.
What is Datumize Zentral?
To successfully adapt to changing environments, organizations need to demonstrate flexibility and agility in their data strategies while also upholding strong data governance standards. Datumize Zentral (DZ) acts as a holistic self-service management platform that facilitates the creation, configuration, testing, deployment, and oversight of data pipelines, agents, and third-party integrations. Its user-friendly interface and API are designed to meet the diverse needs of both clients and partners. Additionally, DZ offers versatile hosting options, enabling deployment on Datumize Cloud, various other cloud services, or even on-premises servers. This adaptability allows businesses to customize their data solutions to align with their unique operational demands, ultimately enhancing their overall efficiency and effectiveness. Moreover, the platform’s comprehensive features empower organizations to optimize their data management processes seamlessly.
Integrations Supported
Amazon EC2 Trn2 Instances
Amazon SageMaker
Anaconda
Apache Zeppelin
Bitbucket
Dask
Flask
GitHub
GitLab
H2O.ai
Integrations Supported
Amazon EC2 Trn2 Instances
Amazon SageMaker
Anaconda
Apache Zeppelin
Bitbucket
Dask
Flask
GitHub
GitLab
H2O.ai
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Domino Data Lab
Date Founded
2013
Company Location
United States
Company Website
www.dominodatalab.com
Company Facts
Organization Name
Datumize
Date Founded
2014
Company Location
Spain
Company Website
www.datumize.com
Categories and Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Categories and Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge