5c03e07ded
Simpler story (slide decks unread -> three-bullet status email), proper Claude-chat look with avatars and bubbles on both sides. Canonical trigger prompt switched to English everywhere (homepage, architecture, both adapter generators rebuilt) - V7 consistency green, all checks pass. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PDKeXvpT6tENSvyQGLV1Uq
1.1 KiB
esco_uri, esco_label, relation, onet_soc, source, confidence, qa_count, generator, generated
| esco_uri | esco_label | relation | onet_soc | source | confidence | qa_count | generator | generated |
|---|---|---|---|---|---|---|---|---|
| http://data.europa.eu/esco/skill/3f4dab51-572b-4e2c-85ef-3b4c3f7094e1 | XQuery | optional | 15-2051.00 | model-knowledge | medium | 0 | gemma3:27b (prompt-designed and spot-checked by Claude) | 2026-07-10 |
XQuery — Data Scientist
As a Data Scientist, XQuery isn't about replacing SQL or Python for most data analysis. It’s a niche but powerful skill when dealing with semi-structured data – think XML and JSON documents stored in databases like MarkLogic or BaseX. You might encounter this when integrating with legacy systems that heavily use XML for configuration or data exchange, or when working with content management systems where data isn't neatly tabular. Typical tasks involve extracting specific information from these complex document structures; for example, pulling product details (name, price, features) from a large catalog of XML product descriptions, or parsing log files stored as JSON.
Weitere Anreicherung
Stage-2 source for future practitioner grounding: arXiv cs.LG/stat.ML (ML preprints).