Advertisement
Published in:
2019 | OriginalPaper | Chapter
Data Exploration in the HIFUN Language
Authors : Nicolas Spyratos, Tsuyoshi Sugibuchi
Published in: Flexible Query Answering Systems
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
When big data sets are stored in databases and data warehouses data exploration usually involves ad hoc querying and data visualization to identify potential relationships or insights that may be hidden in the data. The objective of this work is to provide support for these activities in the context of HIFUN, a high level functional language of analytic queries proposed recently by the authors [5]. Our contributions are: (a) we show that HIFUN queries can be partially ordered and this allows the analyst to drill down or roll up from a given query during data exploration, and (b) we introduce a visualization algebra that allows the analyst to specify desirable visualizations of query results.