Automated, comprehensive analytics
Offers a rich mix of rules, machine learning and integrated deep learning. Provides quick start pipelines and uses industry taxonomies to support predictive and prescriptive analytics.
Offers a wide variety of modeling approaches to help you get the most value from unstructured data.
Embedded data preparation & visualization
Accesses, integrates, profiles, cleanses and transforms data. Imports text from more than 35 data connectors. Includes self-service data visualization for exploring and understanding text data.
Multiuser environment
Provides workspace for sharing best-practice pipelines and methods, encouraging teamwork and collaboration. Seamlessly integrates with existing systems and open source technologies.
Machine-generated topic detection
Derives topics from your documents automatically using two unsupervised machine-learning methods – singular value decomposition and latent Dirichlet allocation.
NLP & NLU
Uses natural language processing to analyze and transform text into formal representations for text processing. Natural language understanding enables contextual understanding of content.
Contextual extraction
Detects and extracts data elements and relationships from unstructured text using predefined concepts, or you can create custom concepts and definitions.
Flexible deployment
Deploy models in batch, Hadoop, in stream and via APIs. Runs models closer to where data is collected to reduce data movement and score new data faster.
Native support for 32 languages
Eliminates need to translate prior to analysis with proprietary language packs that enable native language analysis using dictionaries and linguistic assets created by native language experts.
Sentiment analysis
Identifies and analyzes terms, phrases and character strings that imply tone or attitude (positive, negative, neutral) expressed through text.
Open APIs
Seamlessly integrates with existing systems and open source technologies. Add SAS Analytics to other applications using SAS® Viya® REST APIs.
Scale the human act of reading, organizing and extracting useful information from huge volumes of textual data.
Detect emerging trends and hidden opportunities.
Automatically convert unstructured data into meaningful insights that feed machine learning and predictive models, so you can surface new opportunities – and act on them – quickly. The software combines machine-learning methods with a rules-based approach that's essential for understanding the subtle nuances of language and inferring intention. You can also add subject-matter expertise to further increase the accuracy of your text models.
Drive faster results with automation.
Intelligent algorithms and NLP techniques automatically identify relationships and patterns in text data, eliminating time-consuming manual analysis. Identifying and extracting important topics in free-form text produces new variables that enhance predictive models, reports, and search or filtering applications. A rich mix of rules, machine learning and integrated deep learning provides analytic breadth and depth. The solution includes quick start pipelines and add-on industry taxonomies, and readily supports both predictive and prescriptive analytics.
Go from data to decisions faster.
Empower decision making at the source of the data, and reduce the gap between when information is received and when it's acted on. If someone leaves a comment or clicks through an app on a mobile device, SAS Visual Text Analytics analyzes the data immediately using in-memory, in-database and in-stream technologies. Analyzing real-time streaming text data dramatically speeds up the data-to-decision timeline. The solution also fosters collaboration by enabling users to share best practice pipelines and methods. SAS also seamlessly integrates with existing systems and open source technologies.
Foster collaboration and information sharing in an open ecosystem.
SAS Visual Text Analytics provides a flexible environment that supports the entire analytical life cycle – from data preparation and visual exploration to analysis and deployment. You can tackle and experiment with a variety of analytical use cases to support a single initiative. Collaboration is possible at all levels, whether you’re a data scientist preparing data, a domain expert applying linguistic rules or an IT person deploying models. This unified solution also integrates seamlessly with existing systems and open source technologies.
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