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SAS Visual Text Analytics

Paid
text analyticsnlpmachine learningdata miningsentiment analysistopic modelingenterprise softwarebusiness intelligencesas

SAS Visual Text Analytics uses machine learning, NLP, and linguistic rules to help organizations analyze unstructured text data, identify emerging trends, and extract actionable insights for faster, data-driven decision-making.


SAS Visual Text Analytics is a comprehensive enterprise solution for deriving insights from large volumes of unstructured text. As part of the broader SAS Viya platform, it empowers data scientists and business analysts to process data from sources like social media, reviews, and call center logs. The software merges modern machine learning with traditional rule-based linguistics through an interactive, visual interface. This allows users to build and manage sophisticated text models for topic discovery, sentiment analysis, and categorization without extensive coding. Its key value proposition is embedding powerful, scalable text mining capabilities within the trusted SAS analytics ecosystem, blending accessibility for analysts with the depth required by expert data scientists.

Pros

  • Highly scalable architecture built on the SAS Viya platform to handle massive datasets.
  • Combines multiple analytical approaches, including machine learning, statistical modeling, and user-defined linguistic rules.
  • Intuitive visual workflow interface simplifies the process of building complex text analysis pipelines.
  • Robust support for a wide range of languages, essential for global text analysis initiatives.
  • Seamless integration with the broader SAS analytics suite for end-to-end data processing and visualization.

Cons

  • Opaque, enterprise-only pricing model makes it inaccessible for individuals, startups, and small businesses.
  • Steep learning curve for users who are not already familiar with the SAS ecosystem.
  • Requires significant computational resources, whether deployed on-premise or in the cloud.
  • Can be less flexible for integration with non-SAS, open-source tools compared to API-first competitors or Python libraries.

Key features

  • Automated topic discovery and extraction
  • Sentiment analysis with customizable models
  • Text categorization and classification
  • Natural Language Processing (NLP) for parsing and entity extraction
  • Interactive, visual model building and data exploration
  • Ability to define custom linguistic rules and import dictionaries
  • Support for analyzing text from diverse sources like documents, databases, and social media

Integrations

SAS ViyaSAS Visual AnalyticsSAS Model ManagerSAS Data PreparationREST APIs for custom applicationsHadoopOracle DatabaseTeradata

Target audience

Data scientists, business analysts, market researchers, customer experience professionals, and compliance officers in medium to large enterprises.


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Founded

1976

Headquarters

Cary, USA

Pricing Tiers

Enterprise License

Pricing is available via a custom quote from the SAS sales team. The license is tailored to the organization's needs, based on factors like CPU cores, number of users, and the specific analytics modules required.

Custom


Frequently Asked Questions


Top Alternatives to SAS Visual Text Analytics

IBM Watson Natural Language Understanding

An excellent alternative for developers seeking powerful, API-driven NLP services to embed directly into custom applications and workflows.

Google Cloud Natural Language API

Ideal for organizations already invested in the Google Cloud Platform, offering seamless integration and a flexible, pay-as-you-go pricing model.

Open-source (Python with spaCy/NLTK)

The best choice for data science teams with strong programming skills who require complete control, maximum flexibility, and no licensing costs.

KNIME Text Processing

A strong open-source competitor for those who prefer a visual workflow platform, offering extensive text mining extensions and a large community.

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