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Background

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Comparing two datasets by eye only can get problematic when the reviewer has hundreds or thousands of rows to compare. Imagine having a dataset that contains a list of names, addresses and telephone numbers that needs to be compared and reviewed against a more recent one. This is often performed manually by eye, row by row or in a haphazard approach in Excel. This ends up being very inefficient and potentially error-prone. For critical datasets such as medical or financial records this would be an unacceptable method.

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This is one big area where Excel users come unstuck - comparing seemingly two identical sheets. Many users still compare manually which will quickly lead to inefficient working practices. Imagine how many times in the workplace there is a need to reconcile or compare two different datasets. One may be a review that was performed 3 months ago and now another almost identical sheet has been located which forces the user to play 'spot the difference'. But how how is this possible when you have over 30,000 rows to compare? That's where this latest tool from Apples and Oranges can save you quite a bit of time! 

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ExCompare can do this task in seconds and quickly showing the user what any differences there are between the two datasets. The tool helps the user by:

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• Preventing the need for double data review of the same data from different timepoints (Temporal data)

• Flagging NEW data (e.g. insertion of complete new records)

• Flagging DELETED data (e.g. a datapoint in one or more records has been deleted)

• Flagging CHANGED data (e.g. some records in the file may have been edited, but the reviewer doesn't know which ones)

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Functionality

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• Selection criteria (identify columns that have unique identifier(s)) and locate 'header row'

• Easy two-file upload technique

• The tool will compare changes between the two files (e.g. records removed, added or changed)

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See below videos for a better understanding of how the tool can help you!

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The tool can be used to any industry: Pharmaceuticals (clinical research data: patient data listings such as adverse events, concomitant medication...), IT, Geo-physics, Financials, Healthcare, Human Resources.....

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