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SAS Text Analytics Reveals Patterns, Sentiment and Relationships to Improve Decision Making

Originally published February 16, 2010

SAS Text Analytics, now shipping from the leader in business analytics, automates the time-consuming process of reading individual documents and manually extracting relevant information. Organizations are in constant need of powerful tools to manage proliferating data from social networks, call centers, customer surveys, claims forms and sales returns. SAS’ award-winning analytics mine, interpret and structure information to reveal patterns, sentiment and relationships to improve decision making.

“Our customers use text analytics for customer intelligence, risk management and fraud management,” said Fiona McNeill, Global Analytics Product Marketing Manager at SAS. “Those involved in enterprise content, Web content, document, records and knowledge management, enterprise search, article research and online marketing measurement can easily access and reuse information with SAS Text Analytics.”

Four SAS Text Analytics offerings

SAS’ suite harnesses the power and expertise of the Teragram technologies acquired in 2008:

SAS Enterprise Content Categorization applies natural language processing and advanced linguistic techniques to automatically categorize multilingual content. It parses and analyzes content for entities, facts and events to create metadata, develop taxonomies, and generate category rules and concept definitions to apply to large volumes of documents to trigger business processes.

SAS Sentiment Analysis derives positive and negative opinions, evaluations and emotions of customers and prospects from digital content sources, including blogs, tweets and Internet sites, as well as internal e-mails, call center notes and inquiries.

SAS Text Miner incorporates advanced linguistics into SAS’ core data mining solution, SAS Enterprise Miner. Consolidating structured data analysis with unstructured text provides more meaningful insights from predictive modeling. Automating manual exploration of text, incorporating interactive, drill-down reporting and delivering algorithms for rigorous advanced analyses help organizations grasp future trends and act on new opportunities more efficiently and with less risk.

SAS Ontology Management creates and maintains consistent and centralized metadata across document collections and textual repositories, so information search-and-retrieval engines can systematically identify common concepts. This provides meaningful responses to complex questions, even when answers are not explicitly stated in the text.

Customers rely on text analytics

The Associated Press, eBay, Factiva, Forbes.com, HP, NY Times Company, Reed Business Information, Sony, Tribune Interactive, washingtonpost.com, Wolters Kluwer, the World Bank and Yahoo! use SAS to analyze unstructured data and understand customers, market opportunities, internal operations and supply chains.

“Text analytics is the ‘Wild West’ of predictive analytics, with huge potential for gain,” said John Elder, CEO of Elder Research Inc. “SAS Text Analytics provides a rich toolset for solving unstructured text analysis challenges.”

“Thanks to SAS Text Analytics, our call center can now extract valuable intelligence from massive amounts of unstructured data,” said Patricia Lau, Deputy Head of the Efficiency Unit for the Chief Secretary for Administration’s Office in Hong Kong. “This enables us to be more proactive in addressing problems that matter to citizens. The complaint intelligence system is helping the Efficiency Unit improve public service delivery."

SAS Text Analytics solutions are part of the SAS Business Analytics Framework, backed by the industry’s most comprehensive range of consulting, training and support services, ensuring customers maximum return from their IT investments.

This BeyeNETWORK news item contains information from a recent press release by the company mentioned.