Which combination of actions should be performed to extract data from invoices using Form Recognizer?

• A. Train a model and get result data
• B. Analyze invoice and retrieve labels
• C. Analyze invoice and get analysis results
• D. Submit a model and get field data

Answer: (C)

To successfully extract data from invoices using Form Recognizer, analyzing the invoice and retrieving the analysis results is a crucial step. Form Recognizer uses machine learning to understand the layout and contents of documents like invoices. When you analyze an invoice, the service processes the document and identifies various key components such as invoice number, date, and total amount due.

By selecting to analyze the invoice and get the analysis results, the user can access structured data that has been extracted based on the model's understanding of the document's format. This step essentially provides rich insights into the document, showing extracted entities and their corresponding values in a structured format that can easily be used in applications or further processed.

This approach is aligned with the capabilities of Form Recognizer, which is designed for optical character recognition (OCR) and specific data extraction tasks. The analysis results generated include valuable metadata about the content and layout of the invoice, ensuring that all relevant information has been accounted for in the extraction process.