Keywords: Ambiguous Data, Data Entry Errors, Data Quality, Data Transformation Errors, Duplicate Data, Information Gaps, OCR Errors, Operating Systems
Author: Christopher Tozzi
Publisher: Precisely
Publication Year: 2022
Summary: The following article discuses how data quality is the data set’s ability to serve a business for its intended use. Data quality is essential because It allows a company to use data to reach its customers effectively. Data quality can be problematic if not dealt with appropriately. The common types of data quality problems are: Manual data entry errors, OCR errors, lack of complete information, ambiguous data, duplicate data, and data transformation errors. Errors are prone to happen because they are inevitable. They can be solved by having better data quality tools and implementing continuous improvements in operating systems.