Description
SAS Visual Text Analytics is a comprehensive solution designed to help organizations uncover insights from massive volumes of textual data. Utilizing advanced natural language processing (NLP) techniques, it enables users to discover important information hidden within unstructured data. Key features include large language model (LLM)-based classification, trend analysis, and information extraction. The solution supports hybrid modeling approaches and offers native support for 33 languages, making it versatile for global applications.
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The platform provides a user-friendly interface that facilitates data preparation and visualization. Users can ingest, cleanse, and transform data from various sources, including local or remote file systems, relational databases, and cloud storage. The intuitive interface also supports localization and accessibility, ensuring a seamless user experience.
SAS Visual Text Analytics offers powerful text parsing capabilities, including tokenization, lemmatization, and part-of-speech tagging. These features enable users to process and analyze text data efficiently. The solution also includes automatic topic discovery using unsupervised machine learning methods, allowing users to group documents based on common themes.
In addition to its robust NLP capabilities, the platform provides sentiment analysis tools that identify and label subjective information as positive, negative, or neutral. This information is visually depicted through sentiment indicator displays, providing users with a clear understanding of sentiment trends within their data.
SAS Visual Text Analytics is designed for flexible deployment, with support for various programming languages such as SAS, Python, R, Java, Scala, and Lua. It integrates seamlessly with existing systems and open-source technologies, offering REST APIs for easy integration. The platform's open architecture allows users to publish text analytics models to Microanalytics services (MAS) APIs, enabling on-demand categorization and concept extraction.
- CategoryNatural Language Processing Tools
- Pricing ModelContact sales
- DeploymentFlexible
- PlatformsCloud
SAS Visual Text Analytics Solutions's Core Features
LLM-based classification
Trend analysis
Information extraction
Hybrid modeling approaches
Native support for 33 languages
Data preparation & visualization
Automatic topic discovery
Sentiment analysis
How to use SAS Visual Text Analytics Solutions?
Configure: Set up data sources and parameters
Use: Analyze text data using NLP features
Optimize: Refine models and improve accuracy
Deploy: Integrate with existing systems
SAS Visual Text Analytics Solutions's Use Cases
- Sentiment Analysis
- Trend Analysis
- Information Extraction
- Topic Discovery
- Multilingual Analysis
