Use OCR to Excel for converting scanned reports and other documents with tables to Microsoft Excel, Google Sheets and other spreadsheet formats.

Using OCR to capture data from tables and reports

Data that repeats over and over again in a document can be OCR’d to Microsoft Excel, Google Sheets and other spreadsheet formats, or a SQL Database like Access, SQL Server, MySQL and Oracle.

Inexpensive Desktop OCR products like FineReader, ReadIRIS and OmniPage can automatically convert data from tables to Excel and other spreadsheets, as long as the columns are standard and don’t “overlap” such that different field values appear in the same column area, like when one row of each record represents one set of columns and a second row has additional column data.

Converted data will require some clean-up before it is usable in any database or software application, and it is difficult to convert large numbers of documents in batches this way. But it’s a good way to produce structured data from large single reports or small batches of similar report data.

For more complex tables, tables with similar data but different formats on different documents (like Invoices), tables with nested structure like header and detail rows, Enterprise Forms Processing software is required to turn these documents into structured data like XML, JSON or SQL database tables.

Does ReadIRIS, FineReader or OmniPage support Zone OCR?

The “Pro” versions of most Desktop OCR applications support the creation of zone templates that can be used to OCR specific regions on batches of documents.

Most OCR applications have “Lite” versions that don’t have the ability to manually create zones so it’s important to get the correct version.

With these applications it is often not possible to output this data as “fields” in a structured data file like CSV, Excel or XML. What you typically get a text file for each document with a line of text for each zone. The zones are designed more for excluding regions you don’t want or manually overriding the detection of text, tables and images in the document.

If you need to capture specific data in multiple documents and output them to structured data files or a SQL database, Batch OCR Applications are the best option for this.

If you need to capture data formatted in tables and output to CSV or Excel, desktop OCR applications do this quite well as long as the tables have a regular format with well-defined columns.

To capture handprint, irregular tables, large numbers of data points, or data that doesn’t always appear in the same place on every page, Forms Processing software is what you need.

OCR to Database

Data is Everything. It does not matter in what field your company works, after all everything will be distilled into digits of data and accumulated in Database to be processed, stored, repurposed and reassembled again, again and again.  All organizations have database, that acts as a repository for all of their information. And you may survive with manual data entry, or using spreadsheets or just folders with documents for some time, but eventually just mare amount of Data will become overwhelming.

Luckily there are plenty of solutions for your Database. You can choose between SQL (MySQL, Access, Postgres, …) or NoSQL (Mongo, AWS, …) solutions for storing and processing Data, but there will be always an issue of how raw unprocessed digits get from images or texts into more structured form of your Database. Identifying and transferring all of this data can be a bit of a task. Misreading data or mismatching of data to fields could easily ruin your data processing system. Thus, precision of data character recognition becomes essential.

One of the solutions is to keep these processes of scanning and data transferring separate. You can use one software for character recognition and transferring data from image to PDF or text document. And then to use PDF (or text) to database converters to extract that data into your database format. The very obvious disadvantage of this approach is that it adds the whole extra step into your data processing. You will start accumulate additional errors, will add time for setting up additional conversion, will add time to data processing and will add time for inevitable error identifying and bug fixing. It may work for smaller companies, but on larger enterprise level it becomes cost prohibitive.

Another solution is OCR to Database direct approach. […]


SimpleIndex can bring speed and efficiency to your scanning or doc filing no matter the process. Even if all you are doing is hand keying a few basic details about a document, breaking those details into individual indexes and adding tools like drop down choice lists, automatic orientation, and blank page deletion ensure a smoother, more consistent process.


Here’s where things start to get interesting. From basic tasks like splitting individual documents within at stack of pages by spotting a blank page, a specific mark, or a barcode separator to capturing index data directly from the page or looking up additional details about a document in a database, SimpleIndex has a host of powerful tools to tame your piles of paper or drives full of digital files. Let’s look at a few.


Optical Character Recognition is the ability to take a scan, which is merely a picture of a page, and turn it into words that the computer can understand and use to index your files. SimpleIndex leverages the power of ABBYY FineReader, recognized as one of the best OCR engines on the market, to accurately capture names, dates, important numbers, document types, and other details about your file. Some products have you set a box and capture whatever information happens to fall in that zone. SimpleIndex takes it further with Dynamic Zone OCR to enable you to set an oversized zone that allows for shifting of the pages between scans, but still captures just the date you need by matching against templates, lists, or even Regular Expressions (RegEx). You can also skip the zones entirely and use the full text of a page to find matches for your index data.


OCR Software Guide

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