Create a document lake using large-scale text extraction from documents with Amazon Textract

This blog post discusses methods for extracting text from large collections of documents (images or PDFs) using Amazon Textract, and storing the extracted text in an Amazon S3 data lake.

Specifically, the article covers:

• Solution 1: Using a Python script to detect text in documents, process them in parallel using Amazon Textract, and store the extracted text in S3
• Solution 2: Using AWS CDK constructs to deploy a serverless pipeline with AWS Step Functions and Lambda functions to orchestrate text extraction and storage
• Prerequisites, walkthroughs, and cleanup steps for both solutions
• Conclusion highlighting use cases like using the extracted text for generative AI models or search applications