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Publisher ‏ : ‎ Academic Press; 1st edition (February 11, 2022)
Language ‏ : ‎ English
Paperback ‏ : ‎ 352 pages
ISBN-10 ‏ : ‎ 0128217375
ISBN-13 ‏ : ‎ 978-0128217375
Item Weight ‏ : ‎ 1.65 pounds
Dimensions ‏ : ‎ 7.52 x 0.8 x 9.25 inches

In today’s data-driven world, ensuring high-quality data is essential for making informed business decisions. However, managing data quality can be a complex and challenging task. From data entry errors to inconsistencies in data formats, there are many obstacles that organizations face when it comes to maintaining data quality.

One of the key challenges of data quality management is ensuring data accuracy. This involves detecting and correcting errors in data, such as missing values, duplicate entries, and outdated information. Implementing data validation processes and regular data audits can help organizations identify and resolve inaccuracies in their data.

Another challenge is ensuring data consistency. This involves making sure that data is uniform and standardized across different systems and sources. Data integration tools and data governance policies can help organizations establish consistent data standards and ensure that data is accurate and reliable.

Data completeness is another important aspect of data quality management. Organizations need to ensure that all relevant data is captured and stored properly. Implementing data quality checks and data profiling tools can help organizations identify gaps in their data and take steps to fill them.

In addition to these challenges, organizations also need to address issues related to data security and privacy. Protecting sensitive data from unauthorized access and maintaining compliance with regulations such as GDPR and HIPAA are crucial aspects of data quality management.

Overall, meeting the challenges of data quality management requires a combination of technical tools, data governance policies, and a commitment to continuous improvement. By implementing robust data quality processes and investing in data management technologies, organizations can ensure that their data is accurate, consistent, and reliable, enabling them to make better decisions and drive business success.
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