In this special guest feature, David Abramson, Director of Product Management at Logi Analytics, discusses how the advent of new and disparate data sources means we must rethink the way we manage data ...

As AI technologies continue to advance, the demand for relevant and accurate data has intensified, pushing organizations to capture, integrate, and harness data from many different sources. However, ...

Systems that adhere to strong formal definitions like differential privacy provide protection that is robust to a wide range of potential privacy attacks, provides provable privacy guarantees with ...

Collecting and combining diverse data types from different manufacturing processes can play a significant role in improving semiconductor yield, quality, and reliability, but making that happen ...

Data science has become an important catalyst for innovation. With this, businesses can analyze massive amounts of data to derive insights, anticipate trends and make informed choices. But data ...

Vast amounts of data related to climate change are being compiled by researchers worldwide with varying climate projections. This requires combining information across data sets to arrive at a ...

Genomic sequencing is no longer a novelty, but gene function annotation remains a key challenge in modern biology. A variety of functional genomics experimental techniques are available, from classic ...

Data migration vs data integration: What’s the difference? Your email has been sent As much as data migration and data integration are understood as interchangeable, the two data strategies play very ...

The validity of dietary assessment in large-scale cohort studies has been questioned. Combining data sources for the estimation of usual intake in a blended approach may enhance the validity of ...

Posts from this topic will be added to your daily email digest and your homepage feed. is a senior reporter who has covered AI, robotics, and more for eight years at The Verge. Germany’s national ...