TL;DR 1. Descriptive Analytics (What Happened?) Objective: Provides insights into past events by summarizing raw data into actionable information. Examples: Repo
Updated Jul 2026Bloom UnderstandDigComp Information & data literacyTypeConceptDepth FoundationalDifficulty FoundationalRead ~1 minBloom UnderstandConcepts 8 linkedCluster Cluster AMode Chat-ready
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Objective: Recommends actions based on predictive insights to achieve desired outcomes.
Examples: Optimization algorithms, recommendation systems, and automated decision-making in supply chain planning or financial management.
Summary of the Continuum:49 words
Summary of the Continuum:
The framework starts from understanding what happened (descriptive), moves to why it happened (diagnostic), progresses to what will happen (predictive), and finally focuses on how to make it happen (prescriptive).
Advanced analytics blends these approaches with sophisticated algorithms, enabling better decision-making and automation, especially relevant for large-scale IoT data.
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