Technological developments in recent years have been tremendous. This evolution is visible in companies through technological equipment, computerized procedures, and management practices associated with technologies. One of the management practices that is visible is related to business intelligence and analytics (BI&A). Concepts such as data warehousing, key performance indicators (KPIs), data mining, and dashboards are changing the business arena. This book aims to promote research related to these new trends that open up a new field of research in the small and medium enterprises (SMEs) area. Features Focuses on the more recent research findings occurring in the fields of BI&A Conveys how companies in the developed world are facing today's technological challenges Shares knowledge and insights on an international scale Provides different options and strategies to manage competitive organizations Addresses several dimensions of BI&A in favor of SMEs

Business intelligence (BI) has evolved over several years as organizations have extended their online transaction processing (OLTP) capabilities and applications to support their routine operations. With online analytical processing (OLAP), organizations have also established the capability to extract internal and external data from a variety of sources to specifically obtain intelligence about non-routine and often less-structured arrangements. BI therefore refers to applications and technologies that are used to gather, provide access to, and analyze data and information about the operations of an organization. It has the capability of providing comprehensive insight into the more volatile factors affecting the business and its operations, thereby facilitating enhanced decision-making quality and contributing to the creation of business value. Larger and more sophisticated organizations have long been exploiting these capabilities. Business Intelligence for Small and Medium-Sized Enterprises (SMEs) guides SMEs in replicating this experience to provide an agile roadmap toward business sustainability. The book points out that successful BI implementations have generated significant increases in revenue and cost savings, however, the failure rates are also very high. More importantly, it emphasizes that a full range of BI capabilities is not the exclusive purview of large organizations. It shows how SMEs make extensive use of BI techniques to develop the kind of agility endowing them with the organizational capability to sense and respond to opportunities and threats in an increasingly dynamic business environment. It points to the way to a market environment in which smaller organizations could have a larger role. In particular, the book explains that by establishing the agility to leverage internal and external data and information assets, SMEs can enhance their competitiveness by having a comprehensive understanding of the key to an agile roadmap for business sustainability.

The convergence of modern technology and social dynamics have shaped the very fabric of today’s organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers.

This book analyses the role of Enterprise Resource Planning (ERP) and Business Intelligence (BI) systems in improving information quality through an empirical analysis carried out in Italy. The study begins with a detailed examination of ERP features that highlights the advantages and disadvantages of ERP adoption. Critical success factors for ERP implementation and post-implementation are then discussed, along with the capabilities of ERP in driving the alignment between management accounting and financial accounting information.The study goes on to illustrate the features of BI systems and to summarize companies’ needs for BI. Critical success factors for BI implementation are then presented, along with the BI maturity model and lifecycle. The focus of the research entails a detailed empirical analysis in the Italian setting designed to investigate the role played by ERP and BI systems in reducing information overload/underload and improving information quality by influencing the features of information flow. The practical and theoretical implications of the study are discussed and future avenues of research are suggested. This book will be of value for all those who have an interest in the capacities of ERP and BI systems to enhance business information quality.

If you are looking for the best market, industry or sector to invest in; the “best-in-class” companies to invest in or work with; and need good, current and objective insights to do so, then this is the book for you. Using ground-up fundamental analysis and two new analytical frameworks, you will be able to identify which market, sector or industry to get into and even compare companies at the ability and capability levels. Complemented by a website that will provide up-to-date information on the markets, sectors, industries and up to 1,500 key global companies, the book will be a valuable resource for any business and individual. Objective and quantitative analysis is made real and possible for SMEs, Start-Ups, corporate and individual investors

Digital Transformation in African SMES: Emerging Issues and Trends aims to shed light on the various advantages and drawbacks of the same along with the opportunities and markets that are emerging because of digital transformation. This book provides comprehensive insights into the role of electronic commerce in the success of Small and Medium Enterprises (SMEs) in developing countries, with a specific focus on Africa (Chapter 1). Chapter 2 explores the nexus between digital transformation and SME performance, offering perspectives from developing economies. The challenges faced by SMEs in Africa regarding the adoption of Big Data are examined in Chapter 3. Chapter 4 delves into the exploration of email marketing strategies among SMEs. Additionally, the book covers factors influencing the adoption of Big Data by SMEs in Africa (Chapter 5) and investigates the use of technology by SMEs and its impact on the firms (Chapter 6). Chapter 7 focuses on key factors and impacts related to the adoption of social media by Small and Medium Enterprises. The volume provides information for educators at all levels to obtain a complete understanding of the technology-based environment that impacts teaching and commerce. It also serves as a resource for policymakers, businessmen, researchers, and university and college students, interested in digital transformation in Africa.

Smart watches, autonomous vehicles, and talking robots are now an everyday part of life for many regions of the world. The digital revolution has now permeated nearly every facet of our existence. This surge in technological advancement has ushered in what economists term an "innovation economy." In this era, the synergy between technology and business intelligence propels groundbreaking innovations, fostering entrepreneurial ventures across various sectors. These ventures encompass an array of industries, including agriculture, fast-moving consumer goods, hospitality, cultural and indigenous products, to name just a few. While these entrepreneurial endeavors bring forth creativity and contribute to circular economies within communities, not all manage to navigate the challenging environment successfully. This raises a pressing concern – how can entrepreneurs harness the power of business intelligence and innovation to achieve sustainability and a competitive edge in today's complex business landscape? Applying Business Intelligence and Innovation to Entrepreneurship brings a definitive solution to academicians, researchers, and students who seek a comprehensive understanding of the dynamic interplay between entrepreneurship, business intelligence, and innovation. By dissecting various types of organizations, from small and medium-sized enterprises (SMEs) to technology-based startups like Fintech, digital marketing, and community-driven initiatives, this book paints a vivid picture of the entrepreneurial ecosystem. It delves deep into the symbiotic relationship between local wisdom and innovation, shedding light on how entrepreneurs can seize opportunities presented by disruptive and unpredictable phenomena.

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 sheds light on the recent research directions in intelligent systems and their applications. It involves two main themes, including management information systems and advances in information security and networking. The discussion of the most recent designs, advancements, and modifications of intelligent systems, as well as their applications, is a key component of the chapters contributed to the aforementioned subjects.