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StarRing Big Data Open Lab
StarRing Big Data Open Lab
Aug 25, 2017 · Big Data

How to Optimize OLAP Cubes with Rubik: Dimensional Reduction Strategies Explained

This article walks through Rubik's OLAP cube reduction techniques—including aggregation groups, required, combined, derived, hierarchical, and partial cubes—by designing and implementing buyers and suppliers cubes with six tables, demonstrating performance gains through pre‑computed queries and SQL examples.

CubeData WarehouseDimensional Reduction
0 likes · 10 min read
How to Optimize OLAP Cubes with Rubik: Dimensional Reduction Strategies Explained
StarRing Big Data Open Lab
StarRing Big Data Open Lab
Aug 18, 2017 · Big Data

Cut OLAP Cube Storage Explosions: Proven Dimensionality Reduction Tricks with Rubik

This article explains why raw OLAP Cubes consume exponential storage, then details six practical dimensionality‑reduction methods—Aggregation Group, Mandatory Dimension, Joint Dimension, Derived Dimension, Hierarchy Dimension, and Partial Cube—showing how each can dramatically shrink materialized tables while preserving query performance.

Cube OptimizationData WarehousingOLAP
0 likes · 10 min read
Cut OLAP Cube Storage Explosions: Proven Dimensionality Reduction Tricks with Rubik