---
esco_uri: http://data.europa.eu/esco/skill/1b7c716e-af95-4cda-a42f-6479c8b139f5
esco_label: "MDX"
relation: optional
onet_soc: 15-2051.00
source: model-knowledge
confidence: medium
qa_count: 0
generator: gemma3:27b (prompt-designed and spot-checked by Claude)
generated: 2026-07-10
---

# MDX — Data Scientist

For Data Scientists, MDX isn't about general database querying like SQL; it’s *specifically* for working with multi-dimensional data – think OLAP cubes built in tools like Microsoft Analysis Services or similar platforms (e.g., Mondrian). Daily tasks involve slicing and dicing these cubes to answer business questions that SQL struggles with efficiently. You'll use MDX to pull aggregated metrics (sales by region, profit margin trends) *across multiple dimensions* simultaneously – something SQL often requires complex joins and subqueries for. It’s less about raw data access and more about pre-aggregated insights.

## Weitere Anreicherung

Stage-2 source for future practitioner grounding: arXiv cs.LG/stat.ML (ML preprints).
