This occurs when different departments or groups within an organization use other systems or formats for storing and tracking data.įor example, one department might use all uppercase letters while another uses all lowercase letters. Lack of data standardizationĪnother common cause of data inaccuracy is the lack of data standardization. In addition, the market is flooded with tools to reduce the chances of such errors. That is why it’s crucial to have systems to check for errors, such as spell checkers and data validation rules. Likewise, even the most careful and detail-oriented person can make mistakes when transcribing data. When information is entered manually, there is always the potential for errors. Manual data entryĭata entry is one of the most common causes of data inaccuracy. There are many causes for inaccurate data. So next time you’re staring at a screen full of numbers, take a closer look – you might find an inaccuracy that needs to be corrected. Whatever the cause, inaccurate data can lead to wrong decisions being made, which can have serious consequences. Data inaccuracy is defined as “ incorrect or imprecise data.” It can be caused by human error, incorrect assumptions, poorly calibrated equipment, or bad luck.
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