This article explores the challenges and solutions related to data quality in the digital era, with a particular focus on the integration of AI and automation in the data management process. It highlights common issues such as incomplete, inconsistent, or inaccurate data and discusses the technologies that can help mitigate these problems. AI and automation offer new ways to enhance data collection, processing, and analysis, making it possible to handle large datasets more efficiently and accurately. The article reviews industry best practices for ensuring high data quality, stressing the importance of continuous improvement in data management practices.
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