Text Analytics and Sentiment Mining Using SAS
There is a new version of this course. Please see Text Analytics and Sentiment Mining Using SAS.
Business Knowledge Series course
Presented by Goutam Chakraborty, Ph.D., professor of marketing and founder of the SAS and Oklahoma State University Data Mining Certificate Program
Big data: it's unstructured, it's coming at you fast, and there's a lot of it. In fact, the majority of big data is unstructured and text oriented, thanks to the proliferation of online sources such as blogs, e-mails, and social media. While the amount of textual data are increasing rapidly, businesses' ability to summarize, understand, and make sense of such data for making better business decisions remain challenging. No marketing or customer intelligence program can be effective today without thoroughly understanding how to analyze textual data. Emphasizing practical skills as well as providing theoretical knowledge, this hands-on course takes a comprehensive look at how to organize, manage, and mine textual data for extracting insightful information from large collections of documents and using such information for improving business operations and performance.Learn how to
Who should attendBusiness analysts, web analysts, BI professionals, customer intelligence professionals, data analysts, market researchers, marketing analysts, social media analysts, text analysts, and data miners who want to learn how to effectively use text data to generate customer insights and to understand and predict customer sentiments
Some experience with SAS and SAS Enterprise Miner is useful, but it is not mandatory. No experience with text analysis is necessary.
This course addresses SAS Enterprise Miner, SAS Text Miner, SAS Text Analytics Common Components software.
The demonstrations and exercises in this course primarily use SAS Enterprise Miner, SAS Text Miner, SAS Sentiment Analysis Studio, and SAS Content Categorization Studio.
Text Analytics and Sentiment Mining