Tag: datamodelling
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The Potential of XBRL as a Semantic Layer
Enterprises are increasingly adopting cloud-native platforms, data lakes, lakehouses, and mesh networks to transform raw business data into actionable insights. A key component in these modern architectures is the semantic layer, which makes complex data understandable to humans. In regulatory…
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Digital Reporting and XBRL Multi Target Documents
The UK Financial Reporting Council’s UKSEF framework combines multiple XBRL taxonomies using a rare approach – Multi Target Document (MTD). This unusual choice appears to create headaches for software vendors and data analysts, pushing problems down the supply chain instead…
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What links Datapoints, Label Encoding, XBRL, and AI?
The notion that abstract encoding is bad for Large Language Models (LLMs), leads to the assumption that it must be unhelpful for human understanding. Generating encoded labels for various IT applications is essential, however it introduces special challenges for how…
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Improving XBRL for Data Modelling
There is a fundamental conflict between the modelling approaches of XBRL and the Data Point Methodology (DPM). The EBA and EIOPA use both. This raises the questions of they use both, is there a weakness in one of the approaches,…