The database on tools for preventing and combating hate crime aims to map available resources for the implementation of Recommendation CM/Rec (2024)4 on Combating Hate Crime, which are publicly ...

We systematically review the data-driven innovation (DDI) literature spanning 2009–2022, analyzing key studies, assessing the current state of DDI research in information systems and operations ...

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire ...

The CLEAN framework is a structured, five-step methodology for data cleaning: Conceptualize, Locate, Evaluate, Augment, and Note, aimed at addressing data issues systematically and transparently.

Organizations using data analytics for benefit design save an average of 7.2% on healthcare costs while building programs that truly meet employee needs.

Data analytics is the science of analyzing raw data in order to make conclusions about that information. It helps businesses perform more efficiently and maximize profit.

The developed conceptual framework is presented from substantive and process points of view. A conceptual framework will be built for coaching DM in conventional poly-structural sports; however, the ...

With vast amounts of data, asset managers need sophisticated data analytics to derive insights. Here’s how to build a business case for advanced use cases.