Publisher Fact Sheet How to leverage corporate information for reduced costs & increased profits.

Business intelligence--the acquisition, management, and utilization of information--is crucial in the global marketplace of the 21st century. This savvy handbook explains how even the smallest firm can use inexpensive Web resources to create an Internet Business Intelligence System (IBIS) that rivals the multimillion-dollar systems of Fortune 500 companies. IBIS tracks competitors, explore markets, and evaluates opportunities and risks. It can also be used to launch a business, find customers, test new products, and increase sales.

Annotation Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks describes business intelligence (BI), how it is being conducted and managed and its major opportunities, limitations, issues and risks. This book takes an in-depth look at the scope of global technological change and BI. During this transition to BI, information does not merely add efficiency to the transaction; it adds value. This book brings together high quality expository discussions from experts in this field to identify, define, and explore BI methodologies, systems, and approaches in order to understand the opportunities, limitations and risks.

The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named "Industry 5.0" or "Industrial Internet of Things." The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive.

Global Business Intelligence refers to an organization’s ability to gather, process and analyze pertinent international information in order to make optimal business decisions in a timely manner. With a challenging economic and geopolitical environment, companies and executives need to be adept at information gathering in order to manage emerging challenges and gain competitive advantages. This book Global Business Intelligence assembles a cast of international experts and thought leaders and explores the implications of business intelligence on contemporary management. Global Business Intelligence will be a key resource for researchers, academics, students and policy makers alike in the fields of International Business & Management, Business Strategy, and Geopolitics as well as related disciplines like Political Science, Economics, and Geography.

Business Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks at the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge. Organized into 21 chapters, this book begins with an overview of the kind of knowledge that can be exposed and exploited through the use of BI. It then proceeds with a discussion of information use in the context of how value is created within an organization, how BI can improve the ways of doing business, and organizational preparedness for exploiting the results of a BI program. It also looks at some of the critical factors to be taken into account in the planning and execution of a successful BI program. In addition, the reader is introduced to considerations for developing the BI roadmap, the platforms for analysis such as data warehouses, and the concepts of business metadata. Other chapters focus on data preparation and data discovery, the business rules approach, and data mining techniques and predictive analytics. Finally, emerging technologies such as text analytics and sentiment analysis are considered. This book will be valuable to data management and BI professionals, including senior and middle-level managers, Chief Information Officers and Chief Data Officers, senior business executives and business staff members, database or software engineers, and business analysts. - Guides managers through developing, administering, or simply understanding business intelligence technology - Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization's data into actionable knowledge - Contains a handy, quick-reference to technologies and terminology

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.

Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors' tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you'll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success. - Provides practical guidelines for building successful BI, DW and data integration solutions. - Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language. - Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses - Describes best practices and pragmatic approaches so readers can put them into action. - Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.

This book provides the latest viewpoints of scientific research in the field of e-business. It is organized into three sections: “Higher Education and Digital Economy Development”, “Artificial Intelligence in E-Business”, and “Business Intelligence Applications”. Chapters focus on China’s higher education in e-commerce, digital economy development, natural language processing applications in business, Information Technology Governance, Risk and Compliance (IT GRC), business intelligence, and more.

This book examines the managerial dimensions of business intelligence (BI) systems. It develops a set of guidelines for value creation by implementing business intelligence systems and technologies. In particular the book looks at BI as a process – driven by a mix of human and technological capabilities – to serve complex information needs in building insights and providing aid in decision making. After an introduction to the key concepts of BI and neighboring areas of information processing, the book looks at the complexity and multidimensionality of BI. It tackles both data integration and information integration issues. Bodies of knowledge and other widely accepted collections of experience are presented and turned into lessons learned. Following a straightforward introduction to the processes and technologies of BI the book embarks on BI maturity and agility, the components, drivers and inhibitors of BI culture and soft BI factors like attention, sense and trust. Eventually the book attempts to provide a holistic view on business intelligence, possible structures and tradeoffs and embarks to provide an outlook on possible developments in BI and analytics.