The main advantages of the Office Open XML format

Source: Internet
Author: User
Tags file size zip

or write a concise blog post to share the benefits of Microsoft Office 2007 and 2010 's new Open XML format to our documents.

First, the open XML format will help reduce the size of the document, because it is a compressed format in itself, you can change the *.docx/*.xlsx/*.pptx These file name suffixes to the. zip format and double hit the zip document, and you'll see that the contents are completely readable. , and the entire compressed document greatly reduces the file size for Web transfer and storage. As shown in the following figure, the same Excel workbook is saved in the. xlsx format and the. xls format, and the first picture shows the. xlsx format, the size is 29.3K, and the second picture shows the old. xls format, which is 54.5K, and can be found, compressed by nearly half:

Second, the new Open XML format will help restore partially corrupted and unreadable content in the document. In the case of an older file format, you may be unable to open the entire document because the file is damaged a little bit, and the new format will help you recover the unreadable content in the damaged file and do your best to fix the document and let you open it. For example, the PivotTable report in my Excel workbook is corrupted, so when you open the damaged document, Excel 2010 prompts you to:

When you click Yes, Excel 2010 tries to automatically repair your document and give a report when it is finished. After you fix it, you can see the contents of the damaged part of the file and the original content that was not corrupted.

As shown in the figure above, the first illustration shows the original file before the worksheet that contains the PivotTable report is corrupted, and the second is the case of the same worksheet that was damaged and repaired. You can see that although the PivotTable report is missing, but the original data is still intact, you just need to take a moment to redo the PivotTable report without the heavy cost of gathering every raw data.

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