SQL & NoSQL Databases: Models, Languages, Consistency Options and Architectures for Big Data Management

Author:   Andreas Meier ,  Michael Kaufmann
Publisher:   Springer Fachmedien Wiesbaden
Edition:   1st ed. 2019
ISBN:  

9783658245481


Pages:   229
Publication Date:   16 July 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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SQL & NoSQL Databases: Models, Languages, Consistency Options and Architectures for Big Data Management


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Author:   Andreas Meier ,  Michael Kaufmann
Publisher:   Springer Fachmedien Wiesbaden
Imprint:   Springer Vieweg
Edition:   1st ed. 2019
Dimensions:   Width: 16.80cm , Height: 1.30cm , Length: 24.00cm
Weight:   0.454kg
ISBN:  

9783658245481


ISBN 10:   3658245484
Pages:   229
Publication Date:   16 July 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.
Language:   English

Table of Contents

Data Management.- Data Modeling.- Database Languages.- Ensuring Data Consistency.- System Architecture.- Post-Relational Databases.- NoSQL Databases.

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Author Information

Andreas Meier is a former member of the Faculty of Economics and Social Science and was a professor of Information Technology at the University of Fribourg. He specializes in electronic business, electronic government, and information management. He is member of the GI (Gesellschaft für Informatik), IEEE Computer Society, and ACM. After studying music in Vienna, he graduated with a degree in mathematics at the Federal Institute of Technology (ETH) in Zurich, studied his doctorate, and qualified as a university lecture at the Institute of Computer Science. He was a systems engineer at the IBM research lab in San José, California, director of an international bank, and a member of the executive board of an insurance company.  Michael Kaufmann is a Professor of Data Science and Big Data at the School of Information Technology, Lucerne University of Applied Sciences and Arts.  He is also the coordinator of the university´s DataIntelligence research team, which develops and studies methods and technologies for intelligent data management. Michael Kaufmann studied computer science, law and psychology at the University of Fribourg. With extra-occupational doctoral studies, he received his Ph.D. in computer science on the topic of inductive fuzzy classification in marketing analytics. He worked at PostFinance as a data warehouse poweruser in corporate development; Later on at Mobiliar Insurance as a data architect in the enterprise architecture unit; and as a business analyst at FIVE Informatik AG, where he initiated and led a research project and started teaching as a part time lecturer at Kalaidos University of Applied Science. Since 2014 he has been working at the Lucerne University of Applied Sciences and Arts in teaching and research as a lecturer for databases, where he founded and successfully funded the research team data intelligence. 

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