AI-powered data lineage. Automatically generates readable descriptions of how data was transformed both upstream and downstream, clarifying filters, joins, and calculations, so business users can ...

Chandrashekar Althati's patented multivariate classification revolutionizes real-time transaction analysis, driving fraud detection, customer insights, and compliance across industries.

The health system has seen big improvements in how it engages, retains and serves its consumers, including more than 200,000 ...

For the UK to realize its AI ambitions, both public and private sectors must prioritize building robust data foundations. Entity resolution, contextual intelligence, and graph analytics provide the ...

Analytical data: Analytical data derived from both transactional and master data, is processed and analyzed to provide insights for strategic decision-making. It helps identify trends, forecast demand ...

As artificial intelligence reshapes industries and workplaces at an unprecedented pace, the Ritchie School of Engineering and Computer Science is launching a new Master of Science in Applied Data ...

Legacy event streaming has been constrained by rigid architectures, operational complexity, and data silos that separate transactional and analytical workloads.

2. Master your transactional data Jon Grainger, CTO at the legal firm DWF, said there's no time like the present when it comes to creating a data strategy.

At its Ignite 2024 conference today, Microsoft announced a major step toward breaking down data silos separating transactional databases and analytical tools. The tech giant revealed that Azure ...

This data often includes names, addresses, contact details, aggregated customer transaction history and events, customer preferences, and summaries of customer interactions.

In this edition of Data Spotlight, our series showcasing insights derived from Bloomberg’s 8,000+ enterprise datasets we take a look at transaction data, and credit metrics and how they can help ...