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Analyzing Time Interval Data: Introducing an Information System for Time Interval Data Analysis - Hardcover
Synopsis
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.
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About 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.
From the Back Cover
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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Analyzing Time Interval Data
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Springer Fachmedien Wiesbaden Sep 2016, 2016
ISBN 10: 3658157275
ISBN 13: 9783658157272
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 264 pp. Englisch. Seller Inventory # 9783658157272
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Analyzing Time Interval Data : Introducing an Information System for Time Interval Data Analysis
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Analyzing Time Interval Data : Introducing an Information System for Time Interval Data Analysis
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Springer Fachmedien Wiesbaden, 2016
ISBN 10: 3658157275
ISBN 13: 9783658157272
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783658157272
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Analyzing Time Interval Data
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ISBN 13: 9783658157272
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Buch. Condition: Neu. Neuware -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.Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Straße 46, 65189 Wiesbaden 264 pp. Englisch. Seller Inventory # 9783658157272
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