Business Intelligence

Business Intelligence PDF Author: Carlo Vercellis
Publisher: John Wiley & Sons
ISBN: 1119965470
Category : Mathematics
Languages : en
Pages : 314

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Book Description
Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.

Business Intelligence

Business Intelligence PDF Author: Carlo Vercellis
Publisher: John Wiley & Sons
ISBN: 1119965470
Category : Mathematics
Languages : en
Pages : 314

Get Book Here

Book Description
Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.

Optimization Based Data Mining: Theory and Applications

Optimization Based Data Mining: Theory and Applications PDF Author: Yong Shi
Publisher: Springer Science & Business Media
ISBN: 0857295047
Category : Computers
Languages : en
Pages : 314

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Book Description
Optimization techniques have been widely adopted to implement various data mining algorithms. In addition to well-known Support Vector Machines (SVMs) (which are based on quadratic programming), different versions of Multiple Criteria Programming (MCP) have been extensively used in data separations. Since optimization based data mining methods differ from statistics, decision tree induction, and neural networks, their theoretical inspiration has attracted many researchers who are interested in algorithm development of data mining. Optimization based Data Mining: Theory and Applications, mainly focuses on MCP and SVM especially their recent theoretical progress and real-life applications in various fields. These include finance, web services, bio-informatics and petroleum engineering, which has triggered the interest of practitioners who look for new methods to improve the results of data mining for knowledge discovery. Most of the material in this book is directly from the research and application activities that the authors’ research group has conducted over the last ten years. Aimed at practitioners and graduates who have a fundamental knowledge in data mining, it demonstrates the basic concepts and foundations on how to use optimization techniques to deal with data mining problems.

Data and Decision Sciences - Recent Advances and Applications

Data and Decision Sciences - Recent Advances and Applications PDF Author:
Publisher: BoD – Books on Demand
ISBN: 1803562870
Category : Computers
Languages : en
Pages : 132

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Book Description
This book provides an overview of Data and Decision Sciences (DDS) and recent advances and applications in space-based systems and business, medical, and agriculture processes, decision optimization modeling, and cognitive decision-making. Written by experts, this volume is organized into four sections and seven chapters. It is a valuable resource for educators, engineers, scientists, and researchers in the field of DDS.

Introduction to XXXX

Introduction to XXXX PDF Author: Gilad James, PhD
Publisher: Gilad James Mystery School
ISBN: 7414399656
Category : Education
Languages : en
Pages : 51

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Book Description
Introduction to XXXX is an introductory course aimed at teaching students foundational knowledge and skills in the field of XXXX. The course is designed to provide a comprehensive overview of the key concepts, theories, and practices in XXXX, and equip students with the tools needed to engage with the subject at a deeper level. Throughout the course, students will be introduced to a range of topics, including the history and evolution of XXXX, the main branches of the discipline, and the various methodologies and techniques used in the field. The course is structured around a series of lectures, readings, and assignments, each of which is designed to build upon the previous ones. Lectures will be delivered by experts in the field, while readings will be drawn from a range of academic texts and online resources. Assignments will include both written work and practical exercises, such as data analysis and experiments. By the end of the course, students should have developed a solid understanding of the fundamentals of XXXX, and be able to apply this knowledge to a range of real-world situations.

New Fundamental Technologies in Data Mining

New Fundamental Technologies in Data Mining PDF Author: Kimito Funatsu
Publisher: BoD – Books on Demand
ISBN: 9533075473
Category : Computers
Languages : en
Pages : 600

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Book Description
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining PDF Author: Hassan AbouEisha
Publisher: Springer
ISBN: 3319918397
Category : Technology & Engineering
Languages : en
Pages : 277

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Book Description
Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers. This book can be used as the basis for graduate courses.

Research Advances in Data Mining Techniques and Applications

Research Advances in Data Mining Techniques and Applications PDF Author:
Publisher: BoD – Books on Demand
ISBN: 1837690782
Category : Computers
Languages : en
Pages : 162

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Book Description
For contemporary societies, data mining has emerged as a serious challenge. Thanks to more advanced analytical tools, the Big Data explosion has enabled businesses to assess their performance more thoroughly and accurately. For example, transitioning from using a basic spreadsheet to using data lake modeling offers more flexibility in terms of consulting and summarizing vast amounts of data from many business angles. Data mining, which is the foundation for this optimization of data analysis, has been strengthened by artificial intelligence and machine learning to find patterns in this deluge of data and build future prediction models, turning it into a critical tool for decision-making. This book provides an understanding of the most modern techniques and uses for data mining. It examines data mining in order to classify datasets, predict outcomes, and optimize analyses. Furthermore, the book demonstrates these technological developments by highlighting relevant applications of data mining in industry, biology, education, medicine, and health.

Data-Driven Decision Making

Data-Driven Decision Making PDF Author: Dr. Avinash S. Jagtap
Publisher: Lulu.com
ISBN: 0359354629
Category : Education
Languages : en
Pages : 314

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Book Description
Making decisions is an inevitable activity in life, whether at a personal level or at an institutional level. Everyone is faced with situations where a decision has to be made. There are two ways of treating such situations. One way is to consider the situation to be posing a challenge, where one is more worried about consequences of making a wrong decision. The other, obviously, is to consider the situation to be offering an opportunity, where one is interested in maximizing the benefits by making the right decision.

Optimization Theory, Decision Making, and Operations Research Applications

Optimization Theory, Decision Making, and Operations Research Applications PDF Author: Athanasios Migdalas
Publisher: Springer Science & Business Media
ISBN: 1461451345
Category : Mathematics
Languages : en
Pages : 364

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Book Description
These proceedings consist of 30 selected research papers based on results presented at the 10th Balkan Conference & 1st International Symposium on Operational Research (BALCOR 2011) held in Thessaloniki, Greece, September 22-24, 2011. BALCOR is an established biennial conference attended by a large number of faculty, researchers and students from the Balkan countries but also from other European and Mediterranean countries as well. Over the past decade, the BALCOR conference has facilitated the exchange of scientific and technical information on the subject of Operations Research and related fields such as Mathematical Programming, Game Theory, Multiple Criteria Decision Analysis, Information Systems, Data Mining and more, in order to promote international scientific cooperation. The carefully selected and refereed papers present important recent developments and modern applications and will serve as excellent reference for students, researchers and practitioners in these disciplines. ​

Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions

Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309450810
Category : Mathematics
Languages : en
Pages : 165

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Book Description
The Office of the Under Secretary of Defense (Personnel & Readiness), referred to throughout this report as P&R, is responsible for the total force management of all Department of Defense (DoD) components including the recruitment, readiness, and retention of personnel. Its work and policies are supported by a number of organizations both within DoD, including the Defense Manpower Data Center (DMDC), and externally, including the federally funded research and development centers (FFRDCs) that work for DoD. P&R must be able to answer questions for the Secretary of Defense such as how to recruit people with an aptitude for and interest in various specialties and along particular career tracks and how to assess on an ongoing basis service members' career satisfaction and their ability to meet new challenges. P&R must also address larger-scale questions, such as how the current realignment of forces to the Asia-Pacific area and other regions will affect recruitment, readiness, and retention. While DoD makes use of large-scale data and mathematical analysis in intelligence, surveillance, reconnaissance, and elsewhereâ€"exploiting techniques such as complex network analysis, machine learning, streaming social media analysis, and anomaly detectionâ€"these skills and capabilities have not been applied as well to the personnel and readiness enterprise. Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions offers and roadmap and implementation plan for the integration of data analysis in support of decisions within the purview of P&R.