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.
N. Spyratos—Work conducted while the first author was visiting at FORTH Institute of Computer Science, Crete, Greece (https://www.ics.forth.gr/).
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Spyratos, N., Sugibuchi, T. (2019). Data Exploration in the HIFUN Language. In: Cuzzocrea, A., Greco, S., Larsen, H., Saccà, D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2019. Lecture Notes in Computer Science(), vol 11529. Springer, Cham. https://doi.org/10.1007/978-3-030-27629-4_18
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DOI: https://doi.org/10.1007/978-3-030-27629-4_18
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