SAS in Artificial Intelligence Platform

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North Carolina, USA
$1BN to $5BN
73 Buyers Negotiating


SAS Visual Data Mining and Machine Learning offers an innovative solution that combines the most advanced analytics, data prep, visualization, model assessment and model deployment in a single environment. It also supports programming from popular open source languages. This reliable, collective environment produces desired outcomes, helping improve organizational procedures and discover new opportunities for growth.

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SAS embeds AI capabilities in software to deliver more intelligent, automated solutions that help oneboost productivity and unlock new possibilities. From machine learning, to computer vision, to natural language processing (NLP), to forecasting and optimization,the AI technologies support diverse environments and scale to meet changing business needs.

Key Features:

Interactive programming in a web-based development environment

  • Visual interface for the entire analytical life cycle process.
  • Drag-and-drop interactive interface requires no coding, though coding is an option.
  • Supports automated code creation at each node in the pipeline.
  • Best practice templates (basic, intermediate or advanced) help users get started quickly with machine learning tasks.
  • Interpretability reports.
  • Explore data from within Model Studio and launch directly into SAS Visual Analytics.
  • View data within each node in Model Studio.
  • Run SAS® Enterprise Miner ™ 14.3 batch code within Model Studio.
  • Provides a collaborative environment for easy sharing of data, code snippets and best practices between different personas.
Highly scalable, distributed in-memory analytical processing

• Distributed, in-memory processing of complex analytical calculations on large data
sets provides low-latency answers.
• Analytical tasks are chained together as a single, in-memory job without having to
reload the data or write out intermediate results to disks.
• Concurrent access to the same data in memory by many users improves efficiency.
• Data and intermediate results are held in memory as long as required, reducing latency.
• Built-in workload management ensures efficient use of compute resources.
• Built-in failover management guarantees submitted jobs always finish.
• Automated I/O disk spillover for improved memory management.

Model development with modern machine learning algorithms
• Decision forests:
• Automated ensemble of decision trees to predict a single target.
• Automated distribution of independent training runs.
• Supports intelligent autotuning of model parameters.
• Automated generation of SAS code for production scoring.


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“I am looking for a Artificial Intelligence Platform in north America. My budget is $50,000. Looking to buy in 15 days.”
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  • +13
    Full Time Equivalent
  • +8
    Large Enterprises (Revenue> 500 Million)
  • +11
    Machine Learning
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    Medium sized enterprises
  • +10
    Natural Language Processing
  • +5
    Per User Basis
  • +6
    Small Enterprise (Revenue< 100 Million)
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    Subscription / Licensing
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    Customer Support
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    Sales Support
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    Technical Support
  • +12
    Other Support Services
  • +14
    Chatbots or Robots
  • +13
    Forecasts and Prescriptive Models
  • +5
    Speech Recognition
  • +6
    Text Recognition
  • +14
    Breadth and Depth of Product Offering
  • +5
    Enhance Customer base
  • +7
    Enhance year on year growth
  • +6
    Focus on Product Innovation
  • -13
    Articles and Blogs
  • -12
    Email Branding
  • -9
    Mobile Apps
  • -10
    Offlne campaigns
  • -8
    Social Media Platforms
  • -11
    Word of Mouth strategy
  • -5
    Professional Services
  • -6
    R&D Spend
  • -8
    Customer testimonials
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  • -14
    Managed Services
  • -9
  • -7
    New Product Launches
  • -6
    Product Upgradation
  • -14
    No. of Innovations
  • -10
    Brand Recognition
  • -6
    Solutions Offered
  • -12
    Other tools, please specify
  • -7
    Other Product Features Offered
  • -14
    Other Branding Platform(s)

SAS Reviews



Sep 24, 2019

“Data Science and Machine Learning”

SAS embeds AI capabilities into business applications to help deliver intelligent, automated solutions that help boost productivity. SAS AI technologies support diverse environments, including machine learning, computer vision, natural language processing, forecasting, and optimization.
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SAS Presence in Artificial Intelligence Platform
Identifying and focusing on regions which are adapting machine learning and AI at higher rates has been the strategy for growth at SAS. SAS essentially covers a wide range of industries and helps firms at various levels for Aiand Machine learning adaptation. The growth of firms also depends on the increased adaptation of cloud platforms. SAS’ investment in risk management is paying off, as new sales in these regions grew by 35 percent – an indicator that more companies see value in creating a risk-aware culture to meet regulatory demands and anticipate the impact of their investments.
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