Analyzing Time Interval Data

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Introducing an Information System for Time Interval Data Analysis

ISBN: 365821516X
ISBN 13: 9783658215163
Autor: Meisen, Philipp
Verlag: Springer Vieweg
Umfang: xxxi, 232 S., 57 s/w Illustr., 8 farbige Illustr., 232 p. 65 illus., 8 illus. in color.
Erscheinungsdatum: 16.06.2018
Auflage: 1/2016
Produktform: Kartoniert
Einband: Kartoniert

Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on several bitmap-based indexes, which enable the system to handle huge amounts of time interval data. Contents Modeling Time Interval Data Querying for Time Interval Data Similarity of Time Interval Data An Information System for Time Interval Data Analysis Target Groups – Researchers and students in the field of information management Business analysts and dispatchers in the fields of online analytical processing (OLAP), data warehousing (DW), business intelligence (BI), workforce management, and data science The AuthorPhilipp Meisen holds a doctoral degree from RWTH Aachen, where he was a research group leader at the Chair of Information Management in Mechanical Engineering.

Artikelnummer: 5452519 Kategorie:

Beschreibung

Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on several bitmap-based indexes, which enable the system to handle huge amounts of time interval data.

Autorenporträt

Philipp Meisen holds a doctoral degree from RWTH Aachen, where he was a research group leader at the Chair of Information Management in Mechanical Engineering.

Herstellerkennzeichnung:


Springer Vieweg in Springer Science + Business Media
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65189 Wiesbaden
DE

E-Mail: juergen.hartmann@springer.com

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