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Common Mistakes in Data Entry Jobs

Filed under data entry jobs information, October 3rd, 2008 by admin

Data entry jobs may seem simple at first. How can one go wrong if all that you need is on hand and all you have to do is input data? This is a big misconception. Data entry jobs are one of the most meticulous computing jobs you can get. There is little room for error in data entry jobs. Else, you can get penalized for it, in terms of pay deduction. Worse case, you can lose your client. Companies are dependent on data entry companies and its employees to provide precise and timely services.

Spelling errors

The most common error in data entry jobs is getting the wrong term, or misspelling. This is particularly true for projects that require transcription. Often, these transcription jobs are of medical or legal nature. Untrained ears might not always get the correct terminologies used. At the same time, the client’s slang or accent can get in the way of fully understanding what was said. For this, those who do data entry refer to medical or legal dictionaries to confirm terminologies. They would have to go back and forth through the recording and their transcription to ensure that terms are correct. One cannot afford to just carelessly let these mistakes slip. Spelling errors also happen when the data entry work concerns transferring from one platform to another manually. Sometimes, copy and paste features of the word processing program cannot be used; and mistyping information happens.

Grammatical errors

Another common mistake is the grammatical errors. While transcription work requires typing data from the recorder to the document, it does not necessarily follow that the doctor’s grammatical errors should also reach the document. A good data entry personnel should be able to correct dictation errors.

Data input errors

Likewise, mistaken input is another common mistake. In data entry work that requires moving information from one platform or format to another, mistakes can be made on the input fields. This is understandable, given the huge amount of data. However, care should be taken to minimize the occurrence of these mistakes.

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