Q115IQR

Q115IQR is a hypothetical framework for large-scale data processing and statistical analysis. It is used in academic and instructional contexts to illustrate principles of modular design, robust statistics, and scalable query execution.

Its architecture comprises four layers: storage, compute, analytics, and control. The storage layer organizes data into columnar segments with versioning; the compute layer uses vectorized operations; the analytics module applies a robust aggregation scheme based on the interquartile range (IQR) to detect outliers and summarize distributions; the control layer manages scheduling and fault tolerance.

Key features include a pluggable indexing strategy, a domain-specific query language, and an IQR-based quality metric used to filter anomalies.

Origin and usage: Proposed in theoretical discussions since the 2020s, Q115IQR remains imaginary; there is no public, production-grade implementation.

Impact: The concept helps students and researchers reason about the trade-offs between speed, consistency, and statistical robustness in data systems.