The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

This work presents a maturity model for assessing catalogues of semantic artefacts, one of the keystones that permit semantic interoperability of systems. We defined the dimensions and related ...

Several challenges prevent extracting knowledge from biomedical resources, including data heterogeneity and the difficulty to obtain and collaborate on data and annotations by medical doctors.

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Over the years, we've seen a couple of different organizational models for delivering analytics to the business. While both models have their advantages, each model has some severe drawbacks that make ...

Quest Software Inc., the former Dell Technologies Inc. business unit that’s focused on enterprise data management and security, today announced a major update to its popular erwin Data Intelligence ...

Data modeling is the procedure of crafting a visual representation of an entire information system or portions of it in order to convey connections between data points and structures. The objective is ...

Disparate BI, analytics, and data science tools result in discrepancies in data interpretation, business logic, and definitions among user groups. A universal semantic layer resolves those ...

Identify which data modeling tools are right for your business. Discover the top tools of 2022 now. Data modeling tools play an important role in business, representing how data flows through an ...

More than any other technology, the fast-advancing field of semantic, or tag-based, building data analytics is changing how we design, construct, and operate high-performance buildings. Increased ...