Towards interactive data exploration
Author(s)
Date
2019Source Title
Lecture Notes in Business Information Processing
Print ISSN
1865-1348
Publisher
Springer
Volume
337
Pages
177 - 190
Language
English
Type
Conference PaperItem Usage Stats
150
views
views
290
downloads
downloads
Book Title
Real-time business intelligence and analytics
Abstract
Enabling interactive visualization over new datasets at “human speed” is key to democratizing data science and maximizing human productivity. In this work, we first argue why existing analytics infrastructures do not support interactive data exploration and outline the challenges and opportunities of building a system specifically designed for interactive data exploration. Furthermore, we present the results of building IDEA, a new type of system for interactive data exploration that is specifically designed to integrate seamlessly with existing data management landscapes and allow users to explore their data instantly without expensive data preparation costs. Finally, we discuss other important considerations for interactive data exploration systems including benchmarking, natural language interfaces, as well as interactive machine learning.
Keywords
Big dataInteractive data exploration
Interactive visualization
IDEA
Interactive machine learning
Data analytics
Permalink
http://hdl.handle.net/11693/53434Published Version (Please cite this version)
https://dx.doi.org/10.1007/978-3-030-24124-7_11https://doi.org/10.1007/978-3-030-24124-7