Apply Data Science Introduction, Applications and Projects /
Apply Data Science Introduction, Applications and Projects / [electronic resource] :
edited by Thomas Barton, Christian Müller.
- 1st ed. 2023.
- XIII, 232 p. 78 illus., 61 illus. in color. online resource.
Introduction -- Introduction to Data Science -- Systems, Tools and Methods -- Applications.
This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown. The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers. The Content Introduction to Data Science Systems, tools and methods Applications The target groups IT consultants and management consultants Project managers and project staff Students and teachers of business informatics, computer science and business administration The editors Prof. Dr Thomas Barton is a professor at Worms University of Applied Sciences. His focus is on the development of operational applications, e-business, cloud computing and data science. Prof. Dr Christian Müller is a professor at the Technical University of Wildau. His focus is on operations research, simulation of business processes and internet technologies.
9783658387983
10.1007/978-3-658-38798-3 doi
Artificial intelligence--Data processing.
Information storage and retrieval systems.
Data mining.
Business information services.
Business--Data processing.
Big data.
Data Science.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
IT in Business.
Business Informatics.
Big Data.
Q336
005.7
Introduction -- Introduction to Data Science -- Systems, Tools and Methods -- Applications.
This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown. The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers. The Content Introduction to Data Science Systems, tools and methods Applications The target groups IT consultants and management consultants Project managers and project staff Students and teachers of business informatics, computer science and business administration The editors Prof. Dr Thomas Barton is a professor at Worms University of Applied Sciences. His focus is on the development of operational applications, e-business, cloud computing and data science. Prof. Dr Christian Müller is a professor at the Technical University of Wildau. His focus is on operations research, simulation of business processes and internet technologies.
9783658387983
10.1007/978-3-658-38798-3 doi
Artificial intelligence--Data processing.
Information storage and retrieval systems.
Data mining.
Business information services.
Business--Data processing.
Big data.
Data Science.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
IT in Business.
Business Informatics.
Big Data.
Q336
005.7