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  1. Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP (DOLAP '11)
  2. Interactive exploration and visualization of OLAP cubes
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A rule-based tool for gradual granular data aggregation
Easy and effective parallel programmable ETL
Column-oriented query processing for row stores
Analytics over large-scale multidimensional data: the big data revolution!
Enforcing strictness in integration of dimensions: beyond instance matching
A model-driven framework for ETL process development
Data visualization on web-based OLAP
Building cubes with MapReduce
Building a display of missing information in a data sieve
Interactive exploration and visualization of OLAP cubes
Incremental integration of data warehouses: the hetero-homogeneous approach
Optimization of operator partitions in stream data warehouse
Analyzing continuous fields with OLAP cubes
Towards a more straightforward and more expressive metamodel for SDW modeling
Cascading top-k keyword search over relational databases

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Proceeding

Interactive exploration and visualization of OLAP cubes

Content Provider ACM Digital Library
Author García-García, Javier Ordonez, Carlos Chen, Zhibo
Abstract An OLAP cube is typically explored with multiple aggregations selecting different subsets of cube dimensions to analyze trends or to discover unexpected results. Unfortunately, such analytic process is generally manual and fails to statistically explain results. In this work, we propose to combine dimension lattice traversal and parametric statistical tests to identify significant metric differences between cube cells. We present a 2D interactive visualization of the OLAP cube based on a checkerboard that enables isolating and interpreting significant measure differences between two similar cuboids, which differ in one dimension and have the same values on the remaining dimensions. Cube exploration and visualization is performed by automatically generated SQL queries. An experimental evaluation with a medical data set presents statistically significant results and interactive visualizations, which link risk factors and degree of disease.
Starting Page 83
Ending Page 88
Page Count 6
File Format PDF
ISBN 9781450309639
DOI 10.1145/2064676.2064691
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2011-10-28
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Aggregation Visualization Cube Olap
Content Type Text
Resource Type Article
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