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Data Quality Explained

Revenue lost due to poor data quality.

Data quality is a measure of the overall integrity of data in a database or system.

It is a crucial concept in fields such as business, healthcare, and government where decision-making relies on having accurate data. There are many factors that can affect data quality – inaccuracies, inconsistencies, incomplete data, errors in data entry, poor collections methods, incorrect data analysis, and more.Understanding your data quality is important because it can impact the usability of the data for decision-making purposes. An impact of inaccurate data is incorrect conclusions. An impact of incomplete data is that it can bias the results of the analyses. These simple examples highlight the importance of ensuring data is of high quality before using it for any purpose. It is also critical to ensure there are strong data management practices in place. By paying attention to data quality through better practices, organizations can make better decisions and avoid costly mistakes.

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