October 23 | 1:00 PM - 2:00 PM PT

(4:00 PM - 5:00 PM ET)

Level 300 | Use Case How To

Customer emails, support tickets, product reviews, call center conversations, and social media contain a rich amount of information about your business. However, because this type of data is unstructured and messy, it's hard to extract relevant and meaningful insights at scale. As a result, most of it goes unused. In this tech talk, you'll learn how to deploy a cost-effective, end-to-end solution for extracting meaningful insights from this unstructured data. The solution leverages Amazon Comprehend, a natural language processing (NLP) service that makes it easy to find insights and relationships in text, and Amazon Elasticsearch Service for indexing and analyzing unstructured text. Enjoy a live demo of a Kibana dashboard for visualization of extracted entities, key phrases, syntax, and sentiment from uploaded documentation and walk away with a CloudFormation template to deploy the solution on your own.

Learning Objectives

  • Deploy a cost-effective, end-to-end solution for extracting meaningful insights from unstructured data
  • Apply this to text data from customer calls, support tickets, or online customer feedback
  • Visualize the indexed data on the solution's pre-configured Kibana dashboard

Who Should Attend?

Developers, Amazon ElasticSearch Service users

Speakers

  • Sameer Karnik, Technical Product Manager, AWS
  • Yinxiao Zhang, Senior SDE, AWS

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