Fuzzy Data Warehousing For Performance Measurement

The numeric values retrieved from a data warehouse may be difficult for business users to interpret, and may even be interpreted incorrectly. Therefore, in order to better ​understand numeric values, business users may require an interpretation in meaningful, non-numeric terms. However, if the transition between non-numeric terms is crisp, true values cannot be measured and a smooth transition between classes may no longer be possible. This book addresses this problem by presenting a fuzzy classification-based approach for a data warehouses. Moreover, it introduces a modeling approach for fuzzy data warehouses that makes it possible to integrate fuzzy linguistic variables in a meta-table structure. The essence of this structure is that fuzzy concepts can be integrated into the dimensions and facts of an existing classical data warehouse without affecting its core. This allows a simultaneous analysis, both fuzzy and crisp. A case study of a movie rental company underlines and exemplifies the proposed approach.

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Data warehouse is one of the components of the overall business intelligence system. An enterprise has one data warehouse, and data marts source has their information from the data warehouse. The Data warehouse is a corporation of all data marts within the enterprise. Information is always accumulated in the dimensional model. In this paper, an intelligent data repository with soft computing is presented. It covers similarity metrics that are commonly used to improve the efficiency of data storages. It also covers multiple decision making methodologies to improve the efficiency of decision making.

"This book explores the possibilities and advantages created by fuzzy methods through the presentation of thorough research and case studies"--Provided by publisher.

Although the effort to involve women in engineering has risen in recent years with the creation of new initiatives and the promotion of inclusion in technical disciplines, the active participation of women in engineering professions is continuously lower than expected. While the need for engineers appears to be constantly increasing, women still do not fill most of this role and have a long way to go to even reach an equal split in the field. This gender gap has a significant impact how women in the STEM fields are perceived as well as their experiences in their education and careers. When it comes to Latin American women in IT, their contribution to science can go unnoticed, their participation levels in these fields are very low, and they often occupy lower-level positions than their male counterparts. These issues need to be discussed, and the experiences of women who work in the field must be shared. Latin American Women and Research Contributions to the IT Field highlights the important role of Latin American women in IT by collecting and disseminating their frontier-research contributions in order to provide more visibility and inspire greater participation of Latin American women within the major field of computer science. With chapters contributed by female authors from eight Latin American and Caribbean countries, the book provides a deep analysis of these women’s trajectory paths to high quality theoretical and applied relevant research in computer science and IT. While highlighting areas such as inclusivity and STEM education, along with advancements and achievements in topics that include nonverbal interaction in virtual reality, fuzzy logic applications in education, and ant colony optimization, this book is ideal for professionals, academics, students, and researchers working in the fields of information technologies and computer science as well as those interested in gender and women’s studies.

This edited book presents the state-of-the-art of applying fuzzy logic to managerial decision-making processes in areas such as fuzzy-based portfolio management, recommender systems, performance assessment and risk analysis, among others. Presenting the latest research, with a strong focus on applications and case studies, it is a valuable resource for researchers, practitioners, project leaders and managers wanting to apply or improve their fuzzy-based skills.