Deploy a cost-effective, end-to-end solution for data ingestion and text analysis - Text Analysis with Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) and Amazon Comprehend

Deploy a cost-effective, end-to-end solution for data ingestion and text analysis

Publication date: September 2019 (last update: September 2021)

Many companies have large volumes of unstructured data such as customer calls, support tickets, and online customer feedback. But setting up a data pipeline and a natural language processing (NLP) engine to extract meaningful insights from this data can be a costly, labor-intensive process.

To help customers more easily set up a data pipeline and NLP engine, AWS offers Text Analysis with Amazon OpenSearch Service and Amazon Comprehend. This automated reference implementation deploys a cost-effective, end-to-end solution for data ingestion and text analysis. The solution leverages Amazon Comprehend, an NLP service that uses machine learning for text analysis, and Amazon OpenSearch Service for indexing and analyzing unstructured text.

The solution also creates a pre-configured Kibana dashboard for the visualization of extracted entities, key phrases, syntax, and sentiment from uploaded documentation.

This implementation guide discusses architectural considerations and configuration steps for deploying the Text Analysis with Amazon OpenSearch Service and Amazon Comprehend solution in the Amazon Web Services (AWS) Cloud. It includes a link to an AWS CloudFormation template that launches and configures the AWS services required to deploy this solution using AWS best practices for security and availability.

The guide is intended for IT infrastructure architects, administrators, and DevOps professionals who have practical experience architecting in the AWS Cloud.