It can be tough to manage data manually, and doing so can sometimes lead to errors or inefficiencies. Spreadsheets can get overly complex, and data quality can suffer. This has become a large enough ...

The Government Accountability Office (GAO) has just confirmed for the public what we in the healthcare industry have known and struggled with for years: how hard it is to correctly identify and match ...

Managing, moving, transforming and governing data for business applications and data analytics purposes has always been an important part of IT operations. But those chores have taken on a new level ...

Cloud platforms have reshaped how organizations store, process, and share information, but they also introduce new risks to business data. Misconfigured storage, weak credentials, and unmanaged access ...

On a mission to lighten the workload for data scientists, Google LLC’s cloud division today announced a wave of new artificial intelligence tools designed to help them build the next generation of AI ...

The outlook for digital transformation appears bleak, and there’s no indication it's improving. While 90% of C-level leaders surveyed by McKinsey say their companies have undergone a digital ...

The rapid evolution of mass spectrometry (MS) has established proteomics as a cornerstone of functional genomics, necessitating sophisticated proteomics data analysis and bioinformatics tools to ...

Customer data management is undergoing a rapid transformation, driven by a new wave of tools and technologies designed to handle the growing complexity of data ecosystems. In 2025, businesses are ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Engineers leverage both device-specific and tool-level data to identify a process “sweet spot.” Tight, frequent tool-to-tool matching enables greater yield and fab flexibility. Machine learning helps ...