Where do data quality issues come from?

Data quality issues can arise from various sources throughout the data life cycle. Some common origins of data quality issues include the following:

• Data entry errors: Mistakes made during manual data entry processes can introduce errors such as typos, misspellings, or incorrect values. Human error, lack of training, or inadequate validation mechanisms can contribute to data entry issues.
• Incomplete or missing data: Data may be incomplete or have missing values due to various reasons, such as data collection processes that fail to capture all required information, data entry omissions, or system limitations that prevent data collection.
• Data integration challenges: When combining data from multiple sources or systems, inconsistencies can arise due to differences in data formats, naming conventions, or data structures. Mismatched or incompatible data elements can lead to data quality issues.
• Data transformation and manipulation...