Explore DocHub’s ChatGPT-assisted features to Extract Data from Reports with AI in Technology industry

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Aug 6th, 2022
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01. Upload a document from your computer or cloud storage service.
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02. Modify your document or let the ai PDF editor summarize, rewrite, or proofread your PDF.
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03. Sign your document online in a few clicks.
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04. Send, export, fax, download, or print out your document.

How to use DocHub’s functionality to Extract Data from Reports using AI in Technology industry

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Standard online editors can help specialists in Technology industry with basic document management tasks. However, an up-to-date AI-driven solution like DocHub offers more capabilities and helps accomplish your work faster. Choose our ChatGPT-powered tool to Extract Data from Reports along with other business paperwork - you’ll get the results you require within minutes!

Discover the quick guide below to Extract Data from Reports with AI in Technology sector:

  1. Create an account in DocHub and sign in after its verification.
  2. Add the Reports to the editor using one of the available upload methods.
  3. Start the ChatGPT assistant and choose the tool that lets you Extract Data from your document.
  4. Look through the updates recommended by Artificial Intelligence.
  5. Make edits where necessary, and check at least once more prior to submitting.
  6. Create your signature and request it from others if your form requires approval.
  7. Click on Menu to download, export, or share your professional paperwork.

Whatever your document management needs, you can rely on our progressive solution and complete your tasks in a snap. Give it a try now!

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Got questions?

Below are some common questions from our customers that may provide you with the answer you're looking for. If you can't find an answer to your question, please don't hesitate to reach out to us.
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The real value of document automation comes from its ability to combine data from multiple sources such as CRM, analytics software, content repositories, and bring that information together to assemble relevant assets.
There are broadly two ways to extract data from heterogeneous sources: logical extraction and physical extraction. Both methods involve crawling and retrieving data, but they differ in how the data is collected and processed.
Document data extraction refers to the process of extracting relevant information from various types of documents, whether digital or in print. It involves identifying and retrieving specific data points such as invoice and purchase order (PO) numbers, names, and addresses among others.
Data extraction is the process of obtaining raw data from a source and replicating that data somewhere else. The raw data can come from various sources, such as a database, Excel spreadsheet, an SaaS platform, web scraping, or others.
Document Automation extraction is based on object detection. During document processing, the extraction engine identifies objects, or key-value pairs of the field and associated value.
Use OCR technology: OCR technology can help to extract text from scanned PDFs, making it possible to extract data from documents that were not originally created digitally. OCR can extract data from PDFs produced from scanned handwritten notes or typed documents.
Data extraction is used to retrieve data from multiple sources like relational databases, SaaS applications, legacy systems, web pages, and unstructured data file formats(such as PDFs or text files) in order to analyze, manipulate, or store the information for various purposes.
Artificial intelligence (AI) plays an important role in web data collection, especially when it comes to processing large amounts of data quickly and efficiently. One way AI is used in web data collection is through web scraping. Web scraping involves using automated bots or scripts to extract data from websites.

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