Description: Data quality assessment is a critical process within data governance that focuses on determining whether data meets the required standards for effective use. This process involves a systematic review of data to identify issues such as inaccuracy, incompleteness, inconsistency, and lack of timeliness. Data quality is fundamental for informed decision-making, as low-quality data can lead to erroneous conclusions and ineffective decisions. The main characteristics of data quality assessment include accuracy, completeness, consistency, validity, and timeliness. The relevance of this process has increased in the era of big data, where organizations rely on large volumes of data to drive their business strategies. Data quality assessment not only helps improve trust in data but also optimizes operational processes and reduces costs associated with managing defective data. In summary, data quality assessment is an essential component of data governance that ensures data is fit for purpose and used effectively in decision-making.
