How to Use SAP HANA's Analytics and Text Analysis Capabilities
- by Akash Kumar, Technical Consultant, SAP Labs
- March 4, 2015
See how to apply the SAP HANA analytics and text analysis feature on raw data to solve critical problems. Learn how to use text analytics to gain insight into content-specific values, such as emotions, sentiments, and relevance.
By reading the article you will know how to:
- Create both manual and automatic text indexes for search
- Upload data in SAP HANA using Python
- Use text analysis configuration and the dictionary
- Use sentiment analysis to analyze customer opinion
SAP HANA provides a single platform to extract and analyze massive amounts of structured and unstructured data in real time from multiple sources, such as social media, blogs, online reviews, emails, and discussion forums. The analyzed information helps you to answer specific questions, increase revenue, and make accurate and timely decisions.
Today, both the source and volume of data collected have exploded. It is now easy to analyze the structured data (such as your sales numbers), but more difficult to listen to your customer. SAP HANA allows you to convert unstructured customer feedback in multiple languages from multiple sources into actionable insight. The insight helps to create and modify campaigns, understand current sentiments and trends, launch new products, and correct the pricing of products.
The insight even helps to create targeted contents to increase sales, change customer sentiments for critical problems, and gauge customer feelings. One example of text analysis is the use of sentiment analysis in elections to understand voters’ feelings.
Text analysis involves pattern recognition; tagging or annotation; information extraction; data mining techniques, including link and association analysis; and visualization. The goal is to turn text into data for analysis.
Would you like to see this full item?