Find out why recognizing data integrity issues early in the acquisition process of an M&A transaction can save time and money. Data integrity is broken down into three attributes: accuracy, ...

Our Food, Drug & Device/FDA Group breaks down the new Food and Drug Administration guidance on data integrity for current good manufacturing practices (CGMPs) and what it means for the drug industry.

Biomedical research is entering a new era—one in which human biology is no longer treated as the final validation step but as the foundation for the entire process. Advances in access to human tissue, ...

The US Food and Drug Administration (FDA) has issued four warning letters to companies in China, India, and the US for various violations of good manufacturing practices (GMPs) related to the ...

It’s no secret that data is being created at an ever increasing rate. According to IDC, the amount of data created and replicated grew even more in 2020 due to the sudden increase in the number of ...

The term "data integrity" can mean different things to different people, but the most difficult and pervasive problem facing organizations these days is the semantic integrity of the data. As ...

Many cybercriminals are rich. They might drive expensive cars and live in mansions, making millions annually. Some are funded by governments that use ransomware for cyber warfare, but most cyber ...

Artificial intelligence is no longer an emerging technology—it is an embedded reality shaping the way we live, govern and do business. From predictive healthcare to autonomous defense systems, AI is ...

Kaoru Sakabe was academic publishing’s version of an in-house detective. In 2017, she and editors at the Journal of Biological Chemistry (JBC) conducted a pilot study looking for image manipulation in ...

Latest news on numerous data integrity violations exposed by governing bodies has generated a great deal of interest and has been a matter of concern for companies that actively operate in regulated ...

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Learn the definition of data quality and discover best practices for maintaining accurate and reliable data. Data quality refers to the reliability, accuracy, consistency, and validity of your data.