Data is one of the most valuable resources for any business or organisation, but it can be difficult to ensure that the data is clean and accurate. Dirty data can cause serious problems for a business, including inaccurate analysis, financial losses, and decreased customer satisfaction. Preventing dirty data can be difficult for a variety of reasons, ranging from human error to technological issues.

Human Error

First and foremost, human error is a major factor in how dirty data can occur. People can make mistakes when entering data, such as entering it incorrectly or forgetting to enter it at all. Additionally, data can be corrupted or lost due to physical damage or theft. Even if the data is entered accurately, it can still be corrupted or incorrect if the person entering the data doesn’t understand the data or has a biassed view of it.

Technological Issues

In addition to human error, technological issues can also prevent data from being clean and accurate. Data can become corrupted or lost due to hardware or software failures, or it can be affected by malware or viruses. Data can also be lost or corrupted if it’s stored in an insecure environment or is transferred between systems without proper security measures in place.

High Volume Of Data

It can be difficult to prevent dirty data because of the sheer amount of data that is generated and stored. It can be difficult to track the accuracy of all data, and identifying and correcting errors can be time-consuming. Additionally, certain types of data, such as unstructured data, can be difficult to analyse and clean.

To conclude, preventing dirty data is a difficult task due to the factors mentioned earlier. Therefore it’s important to ensure that data is entered correctly and is stored in a secure environment, and to have processes in place to identify and correct errors. Additionally, businesses should invest in data management tools and use data cleansing techniques such as the ones AICA provides to ensure that their data is accurate and usable.