Sebastian Kaiser – författare

Events Management 1e

John Beech, Sebastian Kaiser and Robert Kaspar

The Business of Events Management provides an accessible and lively introduction to the practice of managing an event, festival, conference or congress. Written by a team of international experts, the book incorporates the latest thinking in events management and highlights key theories, concepts and models by using a range of case studies and examples. 

This book will enable you to:

Manage the financial aspects of events management Understand the impact of events on built and natural environments Explain the role of volunteers in an event and understand the challenges that managing them involves Understand the key issues in planning and designing a venue

Each chapter features a real-life case study to illustrate key concepts and place theory in a practical context, as well as preparing students to tackle any challenges they may face in managing events. Case studies include the Edinburgh International Festival, the 2010 Winter Olympics and Indian Premier League Cricket.

Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix.The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.

Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix.The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.