SAS Viya

SAS Viya

SAS Viya is an advanced data science software designed to streamline the analytics life cycle, enabling users to integrate data from diverse sources effortlessly. Its intuitive interface supports both visual and programming approaches, facilitating collaboration among data scientists. Automated insights and model governance enhance decision-making, optimizing performance across various environments.

Top SAS Viya Alternatives

1

SAS Visual Data Science

SAS Visual Data Science empowers users to seamlessly access, explore, and prepare data while uncovering trends.

2

Cloudera Data Science Workbench

Cloudera Data Science Workbench empowers data scientists to effortlessly manage their analytics pipelines with integrated scheduling, monitoring, and alerting features.

3

SAS Data Science Programming

SAS Data Science Programming empowers data scientists to seamlessly navigate the analytics life cycle through a programmatic approach.

4

FICO Analytics Workbench

FICO Analytics Workbench empowers data scientists to develop and deploy advanced predictive AI models, enhancing decision-making with transactional data.

5

Wolfram Data Science Platform

The Wolfram Data Science Platform enhances data analysis by seamlessly converting structured and unstructured data into actionable insights.

6

Deepnote

Deepnote revolutionizes data analysis with its intuitive notebook interface, allowing users to describe their goals and receive automated insights without any coding required.

7

NVIDIA Merlin

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Knoldus

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IBM ILOG CPLEX Optimization Studio

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dotData

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11

Oracle Machine Learning

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Daft

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Oracle Cloud Infrastructure Data Integration

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Kedro

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Microsoft R Open

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Top SAS Viya Features

  • End-to-end data and AI platform
  • Intuitive visual interfaces
  • Centralized collaboration hub
  • AI-driven automation features
  • Comprehensive machine learning tools
  • Automated feature engineering capabilities
  • Visual and programming interfaces
  • Model performance tuning tournaments
  • Seamless data access and integration
  • Data governance and lineage tracking
  • Operational model deployment
  • Real-time event detection
  • What-if scenario analysis
  • Open-source algorithm integration
  • Natural language generation reports
  • Data pipeline building capabilities
  • Embedded open-source code support
  • Cloud deployment flexibility
  • Automated insights generation
  • Scale for large datasets