There are a few things more frustrating for a spreadsheet worker than having an untidy spreadsheet. Problems occur during PDF to XML conversions and exports into Excel. This guide reveals the reasons for such problems and provides solutions.
Both methods require converters to assume structure that does not exist in PDF files. This leads to the same common mistakes occurring time and time again.
Text in a PDF document is stored in loose fragments rather than rows and columns. Converters typically move cells, merge adjacent columns, or even eliminate rows without giving any notice to the user. Thus, a nicely arranged table can become a mess when placed in Excel.
Excel is usually known to treat numbers, dates, and currency symbols as plain text post-export. This causes calculations not to work, wrong totals, and even funny sorting results. Formatting in terms of fonts, color, and borders of cells is also often lost.
A scanned PDF consists of an image of text, and therefore the converter will need to use OCR technology. Yet, with blurred scans, skewed pages, and strange fonts, mistakes are likely to occur rapidly. For instance, the letter “O” turns into a “0,” while a dot disappears entirely.
Correct PDF to XML conversion requires the existence of well-defined tags; however, there are no such tags in PDF documents to provide a guide for this process. Footnotes, headers, and some special characters will get lost or will end up in the wrong tag. Moreover, improper nesting may render the document invalid.
Multi-columned documents, tables within tables, and inline images are very difficult for automated extractors to handle during the initial scan. In addition, tables that occupy multiple pages are split into distinct fragments with duplicate table headers. Thus, lengthy documents require much more verification than just one-page invoices.
A review of the issues in the PDF to Excel conversion errors and fixes process can help to avoid most errors. The following are the processes one should undertake from initial extraction to validation.
Begin with the optical character recognition of all the scanned documents and select the proper language for each of the documents. After that, mark the boundaries of the table wherever the tool fails to identify it. High-resolution input files can further improve recognition rates.
Once the conversion process is completed, do a row-by-row comparison between the spreadsheet and the original PDF. Next, change the numbers that have been entered as text into numeric format and set up the proper date formats. Lastly, unmerge cells and align the columns properly.
Perform simple tests such as checking column totals and record counts against the source. For XML documents, validate the document against the schema, since any errors will be revealed before sending it. In other words, a 10-minute review is less expensive than cleaning up corrupted data within a running application.
Divide large documents into several small portions so that the software will process each portion more accurately. Also, ensure that the software repeats header rows and merges tables spanning more than one page. Afterwards, reassemble the portions and check for page breaks since they are where most missing rows occur.
In case of large volumes or high accuracy needs, a team of professionals may take care of extraction, tagging, and validation. A reliable PDF to XML converter that features human verification also works with multilingual documents and special characters. Additionally, such companies provide conversions of PDF documents to HTML, text, images, or MS Access.
Conversions using PDFs fail as a result of a lack of structure in the files, poor scans, and guesswork by the tools used. Yet, OCR settings, proper formatting, validation, and shorter document sections can avoid most problems. Thus, consider each conversion to be a rough draft until verified.
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