QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data - Ding, Rui; Han, Shi; Xu, Yong; Zhang, Haidong; Zhang, Dongmei (Proceedings of the 2019 ACM International Conference on Management of Data (SIGMOD'19 industrial track), 2019)
Discovering interesting data patterns is a common and important analytical need in data analysis and exploration, with increasing user demand for automated discovery abilities. However, automatically discovering interesting patterns from multi-dimensional data remains challenging. Existing techniques focus on mining individual types of patterns. There is a lack of unified formulation for different pattern types, as well as general mining frameworks to derive them effectively and efficiently. We present a novel technique QuickInsights, which quickly and automatically discovers interesting patterns from multi-dimensional data. QuickInsights proposes a unified formulation of interesting patterns, called insights, and designs a systematic mining framework to discover high-quality insights efficiently. We demonstrate the effectiveness and efficiency of QuickInsights through our evaluation on 447 real datasets as well as user studies on both expert users and non-expert users. QuickInsights is released in Microsoft Power BI.