Build an End-to-End Data Capture Pipeline using Document AI | Automate Data Capture at Scale
Build an End-to-End Data Capture Pipeline using Document AI | Automate Data Capture at Scale
The Document AI API is a document understanding solution that takes unstructured data, such as documents and emails, and makes the data easier to understand, analyze, and consume.
In this lab, you will create a document processing pipeline that will automatically process documents that are uploaded to Cloud Storage. The pipeline consists of a primary Cloud Function that processes new files that are uploaded to Cloud Storage using a Document AI form processor and then saves form data detected in those files to BigQuery. If the form data includes any address fields the address data is then written to a Pub/Sub topic that in turn triggers a second Cloud Function that uses to Geocoding API to provide geographic coordinate data for the address that is also written to BigQuery.
In this lab, you will learn how to:
Enable the Document AI API.
Deploy Cloud Functions that use the Document AI, BigQuery, Cloud Storage, and Pub/Sub APIs.
Configure a Cloud Function to trigger when documents are uploaded to Cloud Storage.
Configure a Cloud Function to use the Document AI client library for Python.
Configure a Cloud Function to trigger when a Pub/Sub message is created.
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