2016/07/18 by Jean‐Daniel Fekete, Fekete, Jean-Daniel, Romain Primet +1 · 2 citations
Computer Science · Decision Sciences · #Advanced Database Systems and Queries #Data Visualization and Analytics #FOS: Computer and information sciences #H.5.m #Human-Computer Interaction (cs.HC) #K.6.1 #K.7.m #Scientific Computing and Data Management
paper · pdf · doi:10.48550/arxiv.1607.05162
openalex publication_date 2016/07/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Exploring data requires a fast feedback loop from the analyst to the system, with a latency below about 10 seconds because of human cognitive limitations. When data becomes large or analysis becomes complex, sequential computations can no longer be completed in a few seconds and data exploration is severely hampered. This article describes a novel computation paradigm called Progressive Computation for Data Analysis or more concisely Progressive Analytics, that brings at the programming language level a low-latency guarantee by performing computations in a progressive fashion. Moving this progressive computation at the language level relieves the programmer of exploratory data analysis systems from implementing the whole analytics pipeline in a progressive way from scratch, streamlining the implementation of scalable exploratory data analysis systems. This article describes the new paradigm through a prototype implementation called ProgressiVis, and explains the requirements it implies through examples.