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Author Grossmann, Wilfried, 1948- author.

Title Fundamentals of business intelligence / Wilfried Grossmann, Stefanie Rinderle-Ma.

Publication Info. Heidelberg : Springer, 2015.


Location Call No. OPAC Message Status
 Axe Books 24x7 IT E-Book  Electronic Book    ---  Available
Description 1 online resource (xviii, 348 pages) : illustrations (some color).
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
Series Data-Centric Systems and Applications, 2197-9723
Data-centric systems and applications, 2197-9723
Bibliography Includes bibliographical references.
Note Online resource; title from PDF title page (SpringerLink, viewed June 12, 2015).
Contents 1 Introduction -- 2 Modeling in Business Intelligence -- 3 Data Provisioning -- 4 Data Description and Visualization -- 5 Data Mining for Cross-Sectional Data -- 6 Data Mining for Temporal Data -- 7 Process Analysis -- 8 Analysis of Multiple Business Perspectives -- 9 Summary -- A Survey on Business Intelligence Tools.
Summary This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques, and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described, and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided. The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples.
Language English.
Subject Data mining.
Management information systems.
Business intelligence.
Business intelligence. (OCoLC)fst00842723
Data mining. (OCoLC)fst00887946
Management information systems. (OCoLC)fst01007271
Computer Science.
Engineering & Applied Sciences.
Computer Science.
Data Mining and Knowledge Discovery.
Business Information Systems.
Computer Appl. in Administrative Data Processing.
Information Systems Applications (incl. Internet).
Business Process Management.
Genre/Form Electronic books.
Added Author Rinderle-Ma, Stefanie, author.
Other Form: Printed edition: 9783662465301
ISBN 9783662465318 (electronic bk.)
3662465310 (electronic bk.)
3662465302 (print)
9783662465301 (print)
Standard No. 10.1007/978-3-662-46531-8 doi
AU@ 000057665258
DKDLA 820120-katalog:000699938
NLGGC 395776929

Available items only