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Analyzing time interval data = intro...

Meisen, Philipp.

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Analyzing time interval data = introducing an information system for time interval data analysis /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analyzing time interval data/ by Philipp Meisen.
Reminder of title:	introducing an information system for time interval data analysis /
Author:	Meisen, Philipp.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden : : 2016.,
Description:	xxxi, 232 p. :ill., digital ;24 cm.
[NT 15003449]:	Modeling Time Interval Data -- Querying for Time Interval Data -- Similarity of Time Interval Data -- An Information System for Time Interval Data Analysis.
Contained By:	Springer eBooks
Subject:	System analysis - Data processing. -
Online resource:	http://dx.doi.org/10.1007/978-3-658-15728-9
ISBN:	9783658157289$q(electronic bk.)

Analyzing time interval data = introducing an information system for time interval data analysis /
Meisen, Philipp.

Analyzing time interval dataintroducing an information system for time interval data analysis /[electronic resource] :by Philipp Meisen. - Wiesbaden :Springer Fachmedien Wiesbaden :2016. - xxxi, 232 p. :ill., digital ;24 cm.

Modeling Time Interval Data -- Querying for Time Interval Data -- Similarity of Time Interval Data -- An Information System for Time Interval Data Analysis.

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 Author 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.

ISBN: 9783658157289$q(electronic bk.)

Standard No.: 10.1007/978-3-658-15728-9doiSubjects--Topical Terms:

813117
System analysis
--Data processing.

LC Class. No.: QA402

Dewey Class. No.: 519.5

Analyzing time interval data = introducing an information system for time interval data analysis /
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245 1 0 $a Analyzing time interval data $h [electronic resource] : $b introducing an information system for time interval data analysis / $c by Philipp Meisen.
260 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Vieweg, $c 2016.
300 $a xxxi, 232 p. : $b ill., digital ; $c 24 cm.
505 0 $a Modeling Time Interval Data -- Querying for Time Interval Data -- Similarity of Time Interval Data -- An Information System for Time Interval Data Analysis.
520 $a 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 Author 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.
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650 2 4 $a Data Structures, Cryptology and Information Theory. $3 891008
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