- AutorIn
- Wolfgang Lehner Technische Universität Dresden, Fakultät Informatik, Institut für Systemarchitektur, Professur Datenbanken
- Ulrike FischerTechnische Universität Dresden, Fakultät Informatik, Institut für Systemarchitektur, Dresden Database Research Group
- Frank RosenthalTechnische Universität Dresden, Fakultät Informatik, Institut für Systemarchitektur, Dresden Database Research Group
- Titel
- F2DB: The Flash-Forward Database System
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-817295
- Konferenz
- IEEE 28th International Conference on Data Engineering. Arlington, Virginia, 01.-05.04.2012
- Quellenangabe
- 2012 IEEE 28th International Conference on Data Engineering (ICDE 2012) : Proceedings
Erscheinungsort: New York, NY
Verlag: IEEE
Erscheinungsjahr: 2012
Seiten: 1245-1248 - Erstveröffentlichung
- 2012
- Abstract (EN)
- Forecasts are important to decision-making and risk assessment in many domains. Since current database systems do not provide integrated support for forecasting, it is usually done outside the database system by specially trained experts using forecast models. However, integrating model-based forecasting as a first-class citizen inside a DBMS speeds up the forecasting process by avoiding exporting the data and by applying database-related optimizations like reusing created forecast models. It especially allows subsequent processing of forecast results inside the database. In this demo, we present our prototype F2DB based on PostgreSQL, which allows for transparent processing of forecast queries. Our system automatically takes care of model maintenance when the underlying dataset changes. In addition, we offer optimizations to save maintenance costs and increase accuracy by using derivation schemes for multidimensional data. Our approach reduces the required expert knowledge by enabling arbitrary users to apply forecasting in a declarative way.
- Andere Ausgabe
- Link zum Artikel, der zuerst in der IEEE Xplore Digital Library erschienen ist
DOI: 10.1109/ICDE.2012.117 - Freie Schlagwörter (DE)
- Vorhersagemodelle, Mathematisches Modell, Zeitreihenanalyse, Wartungstechnik, Datenmodelle, Prognosen, Analytische Modelle
- Freie Schlagwörter (EN)
- Predictive models, Mathematical model, Time series analysis, Maintenance engineering, Data models, Forecasting, Analytical models
- Klassifikation (DDC)
- 005
- Verlag
- IEEE, New York, NY
- Förder- / Projektangaben
- Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-817295
- Veröffentlichungsdatum Qucosa
- 29.11.2022
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis