In this article, the author provides a comprehensive guide on how to convert tabulated data from documents into Excel using either an Azure Function or Apache Spark within Azure Synapse for high-volume documents.
Often, important data, such as financial reports or purchase orders, exist in table format within documents. Extracting this data into a workable Excel file may be necessary for broader data analysis. The method proposed utilizes Form Recognizer's "General Document" model to extract tabulated data, with the output Excel file storing each document page's table(s) in a separate worksheet. The sheet's name corresponds to the document page number. One can also choose to include key-value pairs in this extraction.
The author also links to a public GIT repository that contains all the necessary resources - the Azure Function, the Synapse Spark Notebook, and sample data for practice. The repository also features a step-by-step guide on deploying these solutions.
This post provides valuable insights for anyone looking to learn more about data extraction and transformation, specifically concerning table data in documents. Those interested in advancing their understanding of this process can explore the provided GIT repository and learn how to implement the described method using Azure Functions and Synapse Spark in Azure Synapse Analytics.
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