Principles of Database Management: The Practical Guide to Storing, Managing and Analyzing Big and Small Data - Couverture rigide

Lemahieu, Wilfried; Vanden Broucke, Seppe; Baesens, Bart

Couverture rigide

ISBN 10 : 1107186129 ISBN 13 : 9781107186125

Editeur : Cambridge University Press, 2018

Synopsis

This comprehensive textbook teaches the fundamentals of database design, modeling, systems, data storage, and the evolving world of data warehousing, governance and more. Written by experienced educators and experts in big data, analytics, data quality, and data integration, it provides an up-to-date approach to database management. This full-color, illustrated text has a balanced theory-practice focus, covering essential topics, from established database technologies to recent trends, like Big Data, NoSQL, and more. Fundamental concepts are supported by real-world examples, query and code walkthroughs, and figures, making it perfect for introductory courses for advanced undergraduates and graduate students in information systems or computer science. These examples are further supported by an online playground with multiple learning environments, including MySQL, MongoDB, Neo4j Cypher, and tree structure visualization. This combined learning approach connects key concepts throughout the text to the important, practical tools to get started in database management.

A propos du livre

À propos des auteurs

Wilfried Lemahieu is a professor at KU Leuven, Belgium, Faculty of Economics and Business, where he also holds the position of Dean. His teaching, for which he was awarded a 'best teacher recognition' includes courses on database management, enterprise information management and management informatics. His research focuses on big data storage and integration, data quality, business process management and service-oriented architectures. In this context, he collaborates extensively with a variety of industry partners, both local and international. His research is published in renowned international journals and he is a frequent lecturer for both academic and industry audiences.

Seppe vanden Broucke works as an assistant professor at the Faculty of Economics and Business, KU Leuven, Belgium. His research interests include business data mining and analytics, machine learning, process management and process mining. His work has been published in well-known international journals and presented at top conferences. He is also author of the book Beginning Java Programming (2015) of which more than 4000 copies were sold and which was also translated in Russian. Seppe's teaching includes advanced analytics, big data and information management courses. He also frequently teaches for industry and business audiences.

Bart Baesens is a professor of Big Data and Analytics at KU Leuven, Belgium and a lecturer at the University of Southampton. He has done extensive research on big data and analytics, credit risk modeling, fraud detection and marketing analytics. He has written more than 200 scientific papers some of which have been published in well-known international journals (e.g. MIS Quarterly, Machine Learning, Management Science, MIT Sloan Management Review and IEEE Transactions on Knowledge and Data Engineering) and presented at international top conferences (e.g. ICIS, KDD, CAISE). He received various best paper and best speaker awards. Bart is the author of 6 books: Credit Risk Management: Basic Concepts (2009), Analytics in a Big Data World (2014), Beginning Java Programming (2015), Fraud Analytics using Descriptive, Predictive and Social Network Techniques (2015), Credit Risk Analytics (2016) and Profit-Driven Business Analytics (2017). He sold more than 15.000 copies of these books worldwide, some of which have been translated in Chinese, Russian and Korean.

Détails de l'édition

• Éditeur: Cambridge University Press
• Date d'édition: 2018
• Langue: anglais
• ISBN 10: 1107186129
• ISBN 13: 9781107186125
• Reliure: Relié
• Numéro d'édition: 1
• Nombre de pages: 808
• Coordonnées du fabricant: non disponible
• Personne responsable: Avery; https://www.avery.fr/; ; chemin des peupliers 27; Dardilly; France