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    You are at:Home » How OCR is Solving the Enigmas of Traditional Data Management
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    How OCR is Solving the Enigmas of Traditional Data Management

    Amir KhanBy Amir KhanSeptember 3, 2021Updated:July 29, 2022No Comments4 Mins Read
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    How OCR is Solving the Enigmas of Traditional Data Management
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    Last Updated on July 29, 2022 by rabiamuzaffar

    What are the Predicaments of Data?

    Data Searching 

    Just imagine a business had to search for a customer record or some person wanted to search for a specific statement in a book in the early 90s. This seems to be an easy task in the modern era, but at that time it was the most irritating and tedious task. It could take hours or even days if the data is not sorted. For instance, if ten customers demand their record in alternative timings, the tiresome searching process repeats for every request.

    Data Editing 

    Just imagine, a school has to update students’ age, what would be the process in hard documents? It may erase and cut the previous data or rewrite the whole data with updated age. Likewise, banks had to update customers’ account details from day today. That data modification not only damages the beauty of data but also creates trouble while reading.

    Data Storage

    Paper documents were taking huge resources of businesses because they had to arrange new pages for every new record. The physical storage of new records is another problem. Businesses have to manage new rooms after one is full.

    Data Security

    What if the data is infected by physical disasters like fire or rain? Once the data is gone there is no way to retrieve it back. There was no data restore option. Numerous businesses suffered, where they lost their data forever.

    So what was the solution that solves all the above problems? The answer is Optical Character Recognition Technology.

    What is OCR?

    This technology was not developed in a day. It keeps updating to give accurate results. The technology that converts hard papers into machine-readable, searchable, editable documents is called OCR. Simply OCR digitizes paper documents. The digitization is done by making segments of it first, then extracting features and classifying them at the end. The state-of-the-art OCR incorporates AI and ML for reading texts from images or documents. Below are types of data that OCR can understand

    Typewritten:

    Documents typed through typewriters or computer software are called typewritten documents.

    Manuscript:

    Documents written by hand are called manuscripts documents. 

    Machine-Readable Zone:

    It is a specific area in a document that is only readable by macing. It contains data in coded form, mostly used in travel documents. It comprises two to three lines. OCR decodes MRZ and gives the information in digital form.

    How Does OCR Assist in Data Extraction?

    The records can be digitized by just uploading the image in the OCR software. For instance, a user uploads the image of his ID card in the OCR software. It will explicitly identify and capture the name, DOB and address information from it. Once the data is digitized, it gives all the facilities a business can imagine. Data management and data processing become as easy as a walk in a park. Data processing greatly helps a business in decision making like tracking customer behavior.

    Now, a business can store all of its data in hard disks in just minutes. OCR can extract information from a document in just seconds. Capturing information from unstructured or semi-structured data was a tough task for traditional humans. This difficulty was also solved by OCR.

    Conclusion

    As far as today OCR is one of the reliable and accurate technologies for data extraction. OCR facility is available in both mobile apps and web applications. As OCR supports various languages, it can be used for all language papers. Today users get the help of OCR incorrect translation applications. They can extract and translate sentences in real-time. OCR heavily gives an advantage in resource-saving, as it will be cheaper to manipulate computerized data. It also eradicates manual intrusions in business processing.

    Read more: How Cloud Computing is Helping to Democratize Big Data?

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    Amir Khan

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