SAS® High-Performance Text Mining

Use all your data and boost model performance.

Analyze millions of social media posts, inquiries and transcripts to discover which topics are hot. Incorporate text-based variables to enrich customer segmentation and make more accurate predictions. Easily distill important insights from large, diverse content sources. With big data technologies from SAS, you can redefine the possibilities.


Make better decisions faster with automated processes.

Machine learning and natural language processing automate previously time-consuming, manual activities. With high-performance capabilities, you can evaluate even large collections quickly. And get comprehensive answers and insights faster than ever before.

Combine unstructured and structured data with advanced analytics.

Make more targeted, high-impact decisions by applying sophisticated analytics to all of your data – not just subsets or aggregates – for more accurate results. Combining structured data with text data enables you to uncover previously unknown relationships and improve model performance.

Improve predictive accuracy by including large-scale text documents.

Readily and automatically examine very large data sets – even billions of documents – to obtain more reliable results. Shrink analytical processing time with distributed, parallel processing. Analyzing more data faster makes your work all the more relevant to the business.

Test more ideas and scenarios to optimize model performance.

A multicore computing environment can reduce processing that used to take 30 minutes to less than a minute. Reduced run time means you can build more models and get results faster. Then, easily retrain your models using different parameters to quickly optimize model performance.



  • Natural language processing.
  • Text processing options.
  • Text filtering.
  • Topic generation.
  • Graphs and tabular output.
  • Available for Greenplum, Teradata and Oracle Exadata appliances, as well as on commodity hardware using Apache Hadoop or Cloudera.

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