Data integrity program: Hierarchy In Massingham's company, there is very senior management sponsorship from the top of the company throughout the organization. There is a formal quality council that ...

Sponsors should consider best practices for maintaining data generated during sample analysis and instrument maintenance.

Successful digital transformation is the primary differentiator in today’s business landscape, and yet many organizations are struggling with the digitization.

For example, a 2013 FDA draft guidance on bioanalytical methods (6), which revises a 2001 guidance, gives broader acceptance criteria (e.g., for accuracy and precision) for ligand-binding assays, ...

The definition of bad data can vary - from data that does not fit the existing business model to basic relational data integrity being broken. If, for example, in a database only logical relational ...

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 ...

In this interview, AZoM talks to Simon Taylor from Mettler Toledo's Titration product group, about data integrity, boosting it in Karl Fischer titration and why it's important to do so.

Sharing data is often a bit like passing round a message in miscommunication - small change and errors can ultimately ruin the data and render it unfit for purpose. Here, we look at data integrity in ...

The real problem is identity, compounded by the lack of quality and integrity put into verifying audience data. If the industry put more effort into verifying identity and audience data, not only ...

The focus of this article is to outline the data integrity requirements of near infrared spectroscopy and how to implement them.