Azure Cognitive Services: Form Recognizer
Author: Ronald Fung
Creation Date: 31 May 2023
Next Modified Date: 31 May 2024
A. Introduction
Azure Form Recognizer is a cloud-based Azure Applied AI Service that enables you to build intelligent document processing solutions. Massive amounts of data, spanning a wide variety of data types, are stored in forms and documents. Form Recognizer enables you to effectively manage the velocity at which data is collected and processed and is key to improved operations, informed data-driven decisions, and enlightened innovation.
B. How is it used at Seagen
As a biopharma research company that uses Microsoft Azure, you can use Azure Cognitive Services: Form Recognizer to extract structured data from unstructured documents relevant to your research. Here are some ways you can use Azure Cognitive Services: Form Recognizer:
Invoice processing: You can use Azure Cognitive Services: Form Recognizer to extract information from invoices, such as supplier names, purchase order numbers, and line item details, which can be used to automate and streamline your accounting processes.
Receipt processing: You can use Azure Cognitive Services: Form Recognizer to extract information from receipts, such as purchase dates, item descriptions, and prices, which can be used to automate and streamline your expense reporting processes.
Application processing: You can use Azure Cognitive Services: Form Recognizer to extract information from job applications, such as candidate names, contact information, and work experience, which can be used to automate and streamline your hiring processes.
Legal document processing: You can use Azure Cognitive Services: Form Recognizer to extract information from legal documents, such as contracts, agreements, and leases, which can be used to automate and streamline your legal processes.
Customization: Azure Cognitive Services: Form Recognizer allows you to customize the document recognition models and criteria to meet your specific needs, ensuring that the service accurately recognizes and extracts data based on your unique requirements.
Integration: Azure Cognitive Services: Form Recognizer can be easily integrated with other Azure services, such as Azure Blob Storage and Azure Functions, as well as third-party services and tools.
Scalability: Azure Cognitive Services: Form Recognizer is highly scalable, allowing you to process large volumes of documents and data quickly and efficiently.
Overall, Azure Cognitive Services: Form Recognizer provides a powerful and flexible tool for extracting structured data from unstructured documents relevant to your research or business. By leveraging the machine learning and AI capabilities of the service, you can quickly and accurately extract information from your documents, and gain insights into the key data points and trends relevant to your research or business.
C. Features
Azure Cognitive Services: Form Recognizer is a machine learning-based service that enables you to extract structured data from unstructured documents relevant to your research or business. Here are some of the key features of Azure Cognitive Services: Form Recognizer:
Document recognition: Azure Cognitive Services: Form Recognizer allows you to recognize and extract data from a wide range of documents, including invoices, receipts, forms, and more.
Customization: Azure Cognitive Services: Form Recognizer allows you to customize the document recognition models and criteria to meet your specific needs, ensuring that the service accurately recognizes and extracts data based on your unique requirements.
Integration: Azure Cognitive Services: Form Recognizer can be easily integrated with other Azure services, such as Azure Blob Storage and Azure Functions, as well as third-party services and tools.
Scalability: Azure Cognitive Services: Form Recognizer is highly scalable, allowing you to process large volumes of documents and data quickly and efficiently.
Data extraction: Azure Cognitive Services: Form Recognizer allows you to extract structured data from unstructured documents, such as text, tables, and key-value pairs, which can be used to automate and streamline your business processes.
Confidence scoring: Azure Cognitive Services: Form Recognizer provides confidence scores for each extracted data point, allowing you to assess the accuracy and reliability of the extracted data.
Language support: Azure Cognitive Services: Form Recognizer supports a wide range of languages, including English, French, German, Spanish, and more.
Training data: Azure Cognitive Services: Form Recognizer requires a large amount of high-quality training data to accurately recognize and extract data from documents, which can be difficult to obtain and may require significant time and resources.
Overall, Azure Cognitive Services: Form Recognizer provides a powerful and flexible tool for extracting structured data from unstructured documents relevant to your research or business. By leveraging the machine learning and AI capabilities of the service, you can quickly and accurately extract information from your documents, and gain insights into the key data points and trends relevant to your research or business.
D. Where Implemented
E. How it is tested
Testing Azure Cognitive Services: Form Recognizer involves verifying that the service is properly configured, that the document recognition models are accurately trained, and that the service can accurately extract structured data from unstructured documents relevant to your research or business. Here are some steps you can take to test Azure Cognitive Services: Form Recognizer:
Verify configuration: Verify that Azure Cognitive Services: Form Recognizer is properly configured and integrated with your Azure account and resources.
Test document recognition: Test Azure Cognitive Services: Form Recognizer by submitting sample documents that contain known data points, such as invoices or receipts, and verifying that the service accurately recognizes and extracts the data points from the documents.
Test customization: Test the customization capabilities of Azure Cognitive Services: Form Recognizer by configuring the document recognition models and criteria to meet your specific needs, and verifying that the service accurately recognizes and extracts data based on your unique requirements.
Test integration: Test the integration capabilities of Azure Cognitive Services: Form Recognizer by integrating it with other Azure services or third-party tools, and verifying that the service works seamlessly with your existing workflows and platforms.
Test scalability: Test the scalability of Azure Cognitive Services: Form Recognizer by submitting large volumes of documents and verifying that the service can process them quickly and efficiently.
Test confidence scoring: Test the confidence scoring capabilities of Azure Cognitive Services: Form Recognizer by verifying that the service provides accurate confidence scores for each extracted data point, allowing you to assess the accuracy and reliability of the extracted data.
Test documentation: Test the documentation of Azure Cognitive Services: Form Recognizer by verifying that it is up-to-date, accurate, and comprehensive.
Overall, testing Azure Cognitive Services: Form Recognizer involves verifying that the service is properly configured and functioning as expected, testing document recognition, customization, integration, scalability, confidence scoring, and documentation. By testing Azure Cognitive Services: Form Recognizer, you can ensure that you are effectively using the service to extract structured data from unstructured documents relevant to your research or business, and that you are benefiting from the accuracy, flexibility, and scalability it provides.
F. 2023 Roadmap
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G. 2024 Roadmap
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H. Known Issues
As with any software or service, there may be known issues or limitations that users should be aware of when using Azure Cognitive Services: Form Recognizer. Here are some of the known issues for Azure Cognitive Services: Form Recognizer:
Limited accuracy: While Azure Cognitive Services: Form Recognizer provides accurate results in many cases, it may not always accurately recognize and extract data from unstructured documents, particularly in cases where the documents are of low quality or contain subtle nuances.
Limited customization: Azure Cognitive Services: Form Recognizer has limited customization options, which can limit the ability of users to configure the service to their specific needs.
Limited training data: Azure Cognitive Services: Form Recognizer requires a large amount of high-quality training data to accurately recognize and extract data from documents, which can be difficult to obtain and may require significant time and resources.
Limited integration: Azure Cognitive Services: Form Recognizer has limited integration with third-party tools and services, which can limit the ability of users to incorporate it into their existing workflows.
Cost: Azure Cognitive Services: Form Recognizer can be expensive for users with limited budgets, particularly if they use it frequently or for large volumes of data.
Limited language support: Azure Cognitive Services: Form Recognizer has limited language support, which can limit its usefulness for users who work with documents in languages other than English.
Overall, while Azure Cognitive Services: Form Recognizer offers a powerful and flexible tool for extracting structured data from unstructured documents relevant to your research or business, users must be aware of these known issues and take steps to mitigate their impact. This may include carefully configuring the service to meet the specific needs of their data, carefully monitoring the cost and accuracy of the service to ensure that it is a good fit for their budget and data requirements, and carefully integrating the service into their existing workflows to ensure that it is effectively utilized. By taking these steps, users can ensure that they are effectively using Azure Cognitive Services: Form Recognizer to extract structured data from unstructured documents relevant to their research or business, and that they are benefiting from the accuracy, flexibility, and scalability it provides.
[x] Reviewed by Enterprise Architecture
[x] Reviewed by Application Development
[x] Reviewed by Data Architecture