Streamline the model life cycle. Deploy models everywhere. Connect data scientists and IT. And get the most value from your analytics investments.
Ensure model governance and transparency.
A centralized, searchable repository for all types of models and analytical assets gives you complete visibility into your analytical processes, ensuring traceability and governance. The solution simplifies model management with life cycle templates and version control, enabling you to track project history through each step of the model management process and get a unified view of each model’s currency, definition and value. Using open REST APIs to access models and model-score artifacts streamlines IT work.
Easily validate models to ensure high-quality predictions.
SAS Model Manager automatically generates executable scoring code for Python-based models. You can easily test models, validating model scoring logic before models are pushed into production using a precise methodology and a system that automatically records each test the scoring engine performs.
Build once, deploy everywhere – no additional testing required.
Efficiently move your analytical models from the innovation lab into your chosen production environment one click. This eliminates having to recode models written in various languages for deployment, testing the results to ensure they perform as expected, then repeating that cycle next time the model needs to be refreshed. Rapid, automated model deployment enabless you to easily deploy models into your business processes – in batch or real time, in the cloud or at the edge.
Automatically monitor model performance to keep them performing as expected.
SAS Model Manager automatically monitors model performance from inception, to usage, to retirement, regardless of the language used to create them. Performance benchmarking reports display the champion model’s scoring performance and document conformity to required standards. Alerts are generated to indicate model decay. As models are used across different departments, the solution produces extensive tracking, validation and auditing reports, and marks champion models for use in other applications. Ongoing monitoring lets you know when it’s time to refine or retire a model.
Increase efficiency by adapting models to reflect internal or external changes.
Continuously update models to keep pace with changing market and business conditions. You can retrain the existing model on new data, or revise the model using feature engineering or new data elements. Model retraining integrates with the model pipeline processing environment for greater efficiency.
Save time and resources by automating the model life cycle using a CI/CD approach.
SAS Model Manager enables you to integrate multiple environments, tools and applications using open REST APIs. You can automate the analytic life cycle by creating custom workflows that match your business requirements and processes.
Simplify model collection creation and management with a web-based interface that easily automates the model management process.
Data access, preparation & quality
Access, profile, cleanse and transform data using an intuitive interface that provides self-service data preparation capabilities with embedded AI.
Custom chatbot creation
Create and deploy custom, natural language chatbots via an intuitive, low-code visual interface for chatbot-enabled insights and conversational user experiences.
Data visualization
Visually explore data, and create and share smart visualizations and interactive reports through a single, self-service interface. Augmented analytics and advanced capabilities accelerate insights and help you uncover stories hidden in your data.
Centralized & searchable model repository
Easily manage analytical models via a centralized, secure web-based repository. Prebuilt model life cycle templates let you manage projects collaboratively.
Task automation with custom workflows
Define and track custom workflows for model life cycle management, including all phases – from problem-statement creation to model development and utilization.
Build once, deploy everywhere
Easily deploy models into your business processes in just a few clicks with rapid, automated model deployment – in batch or real time, in the cloud or at the edge.
Programming only interaction through REST APIs
Lets you use REST APIs to access, compare, assess and score models.
Powered by SAS® Viya®
SAS Viya has a completely redesigned architecture that is compact, cloud native and fast. Whether you prefer to use the SAS Cloud or a public or private cloud provider, you'll be able to make the most of your cloud investment.
Get to Know SAS® Model Manager
SAS Model Manager helps you get faster value from your analytic investments by taking a ModelOps approach to getting analytics out of the lab and into use.
CLOUD PROVIDER
Ottieni il successo da tutte le tue sfide analitiche, da quelle sperimentali a quelle mission critical, grazie a decisioni più rapide in cloud. L'ultima versione di SAS Viya è ora disponibile su questi cloud provider.
Explore More on SAS® Model Manager & Beyond
WHITE PAPER
Managing the Analytics Life Cycle for Decisions at Scale
Discover how the analytics life cycle takes you from raw data to predictive modeling to automated decisions as quickly as possible.
CUSTOMER STORY
Building Materials Leader Optimizes Production Using Analytics
Find out how USG Corporation uses SAS to tackle modern manufacturing challenges for improved efficiency.
WEBINAR
Model Deployment & Management: What You Didn’t Learn About Machine Learning in School
Learn how to get the most value from machine learning with automated, collaborative model management and governance.
E-BOOK
Mastering the Model Life Cycle Orchestration Journey
Learn about best practices for machine learning in production.
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