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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.identifier.isbn978-3-88579-635-0
dc.identifier.issn1617-5468
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.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
dc.pubPlaceBonn
mci.reference.pages483-492
mci.conference.locationHamburg
mci.conference.date2.-3. März 2015


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