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Forecasting in Database Systems

dc.contributor.authorFischer, Ulrike
dc.contributor.editorSeidl, Thomas
dc.contributor.editorRitter, Norbert
dc.contributor.editorSchöning, Harald
dc.contributor.editorSattler, Kai-Uwe
dc.contributor.editorHärder, Theo
dc.contributor.editorFriedrich, Steffen
dc.contributor.editorWingerath, Wolfram
dc.date.accessioned2017-06-30T11:40:47Z
dc.date.available2017-06-30T11:40:47Z
dc.date.issued2015
dc.description.abstractTime series forecasting is crucial in a number of domains such as production planning and energy load balancing. In these areas, forecasts are often required by non-expert users on large multi-dimensional data sets expecting short response times. However, as current traditional database systems support forecasting only in a limited and non-declarative way, it is performed outside the database system by specially trained experts. We introduce a novel approach that seamlessly integrates time series forecasting into an existing database management system. In contrast to flash-back queries that allow a view on the data in the past, we have developed a Flash-Forward Database System (F2DB) that provides a view on the data in the future. It supports a new query type - a forecast query - that enables forecasting of time series data for any user and is automatically processed by the core engine of an existing DBMS. Ween
dc.identifier.isbn978-3-88579-635-0
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2015)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-241
dc.titleForecasting in Database Systemsen
dc.typeText/Conference Paper
gi.citation.endPage492
gi.citation.publisherPlaceBonn
gi.citation.startPage483
gi.conference.date2.-3. März 2015
gi.conference.locationHamburg

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