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| business intelligence in retail industry: Retail Analytics Emmett Cox, 2011-10-18 The inside scoop on boosting sales through spot-on analytics Retailers collect a huge amount of data, but don't know what to do with it. Retail Analytics not only provides a broad understanding of retail, but also shows how to put accumulated data to optimal use. Each chapter covers a different focus of the retail environment, from retail basics and organization structures to common retail database designs. Packed with case studies and examples, this book insightfully reveals how you can begin using your business data as a strategic advantage. Helps retailers and analysts to use analytics to sell more merchandise Provides fact-based analytic strategies that can be replicated with the same success the author achieved on a global level Reveals how retailers can begin using their data as a strategic advantage Includes examples from many retail departments illustrating successful use of data and analytics Analytics is the wave of the future. Put your data to strategic use with the proven guidance found in Retail Analytics. |
| business intelligence in retail industry: Retail Analytics Emmett Cox, 2011-09-13 The inside scoop on boosting sales through spot-on analytics Retailers collect a huge amount of data, but don't know what to do with it. Retail Analytics not only provides a broad understanding of retail, but also shows how to put accumulated data to optimal use. Each chapter covers a different focus of the retail environment, from retail basics and organization structures to common retail database designs. Packed with case studies and examples, this book insightfully reveals how you can begin using your business data as a strategic advantage. Helps retailers and analysts to use analytics to sell more merchandise Provides fact-based analytic strategies that can be replicated with the same success the author achieved on a global level Reveals how retailers can begin using their data as a strategic advantage Includes examples from many retail departments illustrating successful use of data and analytics Analytics is the wave of the future. Put your data to strategic use with the proven guidance found in Retail Analytics. |
| business intelligence in retail industry: Style and Statistics Brittany Bullard, 2016-11-30 A non-technical guide to leveraging retail analytics for personal and competitive advantage Style & Statistics is a real-world guide to analytics in retail. Written specifically for the non-IT crowd, this book explains analytics in an approachable, understandable way, and provides examples of direct application to retail merchandise management, marketing, and operations. The discussion covers current industry trends and emerging-standard processes, and illustrates how analytics is providing new solutions to perennial retail problems. You'll learn how to leverage the benefits of analytics to boost your personal career, and how to interpret data in a way that's useful to the average end business user or shopper. Key concepts are detailed in easy-to-understand language, and numerous examples highlight the growing importance of understanding analytics in the retail environment. The power of analytics has become apparent across industries, but it's left an especially indelible mark on retail. It's a complex topic, but you don't need to be a data scientist to take advantage of the opportunities it brings. This book shows you what you need to know, and how to put analytics to work with retail-specific applications. Learn how analytics can help you be better at your job Dig deeper into the customer's needs, wants, and dreams Streamline merchandise management, pricing, marketing, and more Find solutions for inefficiencies and inaccuracies As the retail customer evolves, so must the retail industry. The retail landscape not only includes in-store but also website, mobile site, mobile apps, and social media. With more and more competition emerging on all sides, retailers need to use every tool at their disposal to create value and gain a competitive advantage. Analytics offers a number of ways to make your company stand out, whether it's through improved operations, customer experience, or any of the other myriad factors that build a great place to shop. Style & Statistics provides an analytics primer with a practical bent, specifically for the retail industry. |
| business intelligence in retail industry: Business Intelligence and Analytics in Small and Medium Enterprises Pedro Novo Melo, Carolina Machado, 2019-11-26 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 in retail industry: E-Business Intelligence Bernard Liautaud, 2001 Publisher Fact Sheet How to leverage corporate information for reduced costs & increased profits. |
| business intelligence in retail industry: Business Intelligence Guidebook Rick Sherman, 2014-11-04 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. |
| business intelligence in retail industry: Business Intelligence, Reprint Edition Stacia Misner, Michael Luckevich, Elizabeth Vitt, 2008-12-10 “This readable, practical book helps business people quickly understand what business intelligence is, how it works, where it's used, and why and when to use it—all illustrated by real case studies, not just theory.” Nigel Pendse Author of The OLAP Report www.olapreport.com So much information, so little time. All too often, business data is hard to get at and use—thus slowing decision-making to a crawl. This insightful book illustrates how organizations can make better, faster decisions about their customers, partners, and operations by turning mountains of data into valuable business information that’s always at the fingertips of decision makers. You’ll learn what’s involved in using business intelligence to bring together information, people, and technology to create successful business strategies—and how to execute those strategies with confidence. Topics covered include: THE BUSINESS INTELLIGENCE MINDSET: Discover the basics behind business intelligence, such as how it’s defined, why and how to use it in your organization, and what characteristics, components, and general architecture most business intelligence solutions share. THE CASE FOR BUSINESS INTELLIGENCE: Read how world leaders in finance, manufacturing, and retail have successfully implemented business intelligence solutions and see what benefits they have reaped. THE PRACTICE OF BUSINESS INTELLIGENCE: Find out what’s involved in implementing a business intelligence solution in your organization, including how to identify your business intelligence opportunities, what decisions you must make to get a business intelligence project going, and what to do to sustain the momentum so that you can continue to make sense of all the data you gather. |
| business intelligence in retail industry: The Profit Impact of Business Intelligence Steve Williams, Nancy Williams, 2010-07-27 The Profit Impact of Business Intelligence presents an A-to-Z approach for getting the most business intelligence (BI) from a company's data assets or data warehouse. BI is not just a technology or methodology, it is a powerful new management approach that – when done right – can deliver knowledge, efficiency, better decisions, and profit to almost any organization that uses it. When BI first came on the scene, it promised a lot but often failed to deliver. The missing element was the business-centric focus explained in this book. It shows how you can achieve the promise of BI by connecting it to your organization's strategic goals, culture, and strengths while correcting your BI weaknesses. It provides a practical, process-oriented guide to achieve the full promise of BI; shows how world-class companies used BI to become leaders in their industries; helps senior business and IT executives understand the strategic impact of BI and how they can ensure a strong payoff from their BI investments; and identifies the most common mistakes organizations make in implementing BI. The book also includes a helpful glossary of BI terms; a BI readiness assessment for your organization; and Web links and extensive references for more information. - A practical, process-oriented book that will help organizations realize the promise of BI - Written by Nancy and Steve Williams, veteran consultants and instructors with hands-on, in the trenches experience in government and corporate business intelligence applications - Will help senior business and IT executives understand the strategic impact of BI and how they can help ensure a strong payoff on BI investments |
| business intelligence in retail industry: Adaptive Business Intelligence Zbigniew Michalewicz, Martin Schmidt, Matthew Michalewicz, Constantin Chiriac, 2006-12-02 Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address fundamental questions: What is likely to happen in the future? What is the best course of action? Adaptive Business Intelligence explores elements of data mining, predictive modeling, forecasting, optimization, and adaptability. The book explains the application of numerous prediction and optimization techniques, and shows how these concepts can be used to develop adaptive systems. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy systems, genetic algorithms, simulated annealing, tabu search, ant systems, and agent-based modeling. |
| business intelligence in retail industry: Retail Geography and Intelligent Network Planning Mark Birkin, Graham Clarke, Martin P. Clarke, 2002-06-14 Retail Intelligence & Network Planning baut auf dem Erfolg des Vorgängerbandes Intelligent GIS auf, in dem Grundlagen und Anwendungen von GIS und Raummodellen für die strategische Planung ausführlich dargelegt wurden. Retail Intelligence & Network Planning konzentriert sich in erster Linie auf den breiten Einzelhandelssektor; die hier behandelten Beispiele stammen aus einer Vielzahl von Branchen. Die Autoren erläutern, wie wichtig Fallstudien für die moderne Standortforschung sind und behandeln eine breite Palette von Fragen zu Standort, Distribution und Management der Vertriebskanalproblematik, die für Einzelhandels- und Dienstleistungsunternehmen von großem Interesse sind. |
| business intelligence in retail industry: Business Intelligence: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2015-12-29 Data analysis is an important part of modern business administration, as efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Business Intelligence: Concepts, Methodologies, Tools, and Applications presents a comprehensive examination of business data analytics along with case studies and practical applications for businesses in a variety of fields and corporate arenas. Focusing on topics and issues such as critical success factors, technology adaptation, agile development approaches, fuzzy logic tools, and best practices in business process management, this multivolume reference is of particular use to business analysts, investors, corporate managers, and entrepreneurs in a variety of prominent industries. |
| business intelligence in retail industry: Data Warehouses and OLAP Robert Wrembel, Christian Koncilia, 2007-01-01 Data warehouses and online analytical processing (OLAP) are emerging key technologies for enterprise decision support systems. They provide sophisticated technologies from data integration, data collection and retrieval, query optimization, and data analysis to advanced user interfaces. New research and technological achievements in the area of data warehousing are implemented in commercial database management systems, and organizations are developing data warehouse systems into their information system infrastructures. Data Warehouses and OLAP: Concepts, Architectures and Solutions covers a wide range of technical, technological, and research issues. It provides theoretical frameworks, presents challenges and their possible solutions, and examines the latest empirical research findings in the area. It is a resource of possible solutions and technologies that can be applied when designing, implementing, and deploying a data warehouse, and assists in the dissemination of knowledge in this field. |
| business intelligence in retail industry: Business Intelligence Carlo Vercellis, 2011-08-10 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 in retail industry: Intersection of AI and Business Intelligence in Data-Driven Decision-Making Natarajan, Arul Kumar, Galety, Mohammad Gouse, Iwendi, Celestine, Das, Deepthi, Shankar, Achyut, 2024-08-28 In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success. |
| business intelligence in retail industry: Modelling for Added Value Robert Macredie, Ray Paul, Dervarajan Anketell, Brian Lehaney, Shamim Warwick, 1998-07-31 This book gathers together research from three key application themes of modelling in operational research - modelling to support evaluation and change in organisations; modelling within the development and use of organisational information systems; and the use of modelling approaches to support, enable and enhance decision support in organisational contexts. The issues raised provide valuable insight into the range of ways in which operational research techniques and practices are being successfully applied in today's information-centred business world. Modelling for Added Value provides a window onto current research and practise in modelling techniques and highlights their rising importance across the business, industrial and commercial sectors. The book contains contributions from a mix of academics and practitioners and covers a range of complex and diverse modelling issues, highlighting the broad appeal of this increasingly important subject area. |
| business intelligence in retail industry: Marketing and Smart Technologies Álvaro Rocha, José Luís Reis, Marc K. Peter, Zorica Bogdanović, 2020 This book includes selected papers presented at the International Conference on Marketing and Technologies (ICMarkTech 2019), held at Maieutica Academic Campus (University Institute of Maia & Polytechnic Institute of Maia) in Maia, Portugal, from 27 to 29 November 2019. It covers up-to-date cutting-edge research on artificial intelligence applied in marketing, virtual and augmented reality in marketing, business intelligence databases and marketing, data mining and big data, marketing data science, web marketing, e-commerce and v-commerce, social media and networking, geomarketing and IoT, marketing automation and inbound marketing, machine learning applied to marketing, customer data management and CRM, and neuromarketing technologies. |
| business intelligence in retail industry: Introduction to Data Mining and Its Applications S. Sumathi, S.N. Sivanandam, 2006-09-26 This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining. |
| business intelligence in retail industry: Data Science and Business Intelligence for Corporate Decision-Making Dr. P. S. Aithal, 2024-02-09 About the Book: A comprehensive book plan on Data Science and Business Intelligence for Corporate Decision-Making with 15 chapters, each with several sections: Chapter 1: Introduction to Data Science and Business Intelligence Chapter 2: Foundations of Data Science Chapter 3: Business Intelligence Tools and Technologies Chapter 4: Data Visualization for Decision-Making Chapter 5: Machine Learning for Business Intelligence Chapter 6: Big Data Analytics Chapter 7: Data Ethics and Governance Chapter 8: Data-Driven Decision-Making Process Chapter 9: Business Intelligence in Marketing Chapter 10: Financial Analytics and Business Intelligence Chapter 11: Operational Excellence through Data Analytics Chapter 12: Human Resources and People Analytics Chapter 13: Case Studies in Data-Driven Decision-Making Chapter 14: Future Trends in Data Science and Business Intelligence Chapter 15: Implementing Data Science Strategies in Corporations Each chapter dives deep into the concepts, methods, and applications of data science and business intelligence, providing practical insights, real-world examples, and case studies for corporate decision-making processes. |
| business intelligence in retail industry: Business Intelligence Strategy and Big Data Analytics Steve Williams, 2016-04-08 Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like big data and big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. - Provides ideas for improving the business performance of one's company or business functions - Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies - Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans |
| business intelligence in retail industry: Retail Management Prabhu TL, 2019-04-21 Step into the dynamic world of retail management—a realm where innovation, customer experience, and strategic thinking converge to shape the future of retail. Retail Management is a comprehensive guide that unravels the intricacies of this vibrant industry, offering a roadmap to excel in a fast-paced and ever-evolving market. Embracing Retail Excellence: Unleash your potential as Retail Management equips you with the essential knowledge and skills to thrive in the competitive retail landscape. From store operations to omnichannel marketing, this book presents a holistic approach to mastering the art of retail management. Key Themes Explored: Retail Strategy: Discover the strategies that differentiate successful retailers, including market positioning and competitive advantage. Customer-Centric Retail: Embrace the significance of customer experience and personalized interactions in building brand loyalty. Inventory and Supply Chain Management: Learn to optimize inventory levels and streamline supply chain processes for efficiency. Visual Merchandising: Explore the art of visual storytelling and creating immersive retail spaces that captivate customers. E-commerce and Digital Retail: Stay ahead of the digital revolution with insights into online retail and e-commerce strategies. Target Audience: Retail Management caters to retail managers, business owners, students, and anyone passionate about excelling in the retail industry. Whether you manage a physical store or an online shop, this book empowers you to navigate the complexities of retail management. Unique Selling Points: Real-World Case Studies: Engage with practical examples from successful retailers, offering lessons for your own business. Data-Driven Decisions: Embrace the power of retail analytics and consumer data to inform business strategies. Retail Trends and Innovations: Stay up-to-date with the latest retail trends, technology, and innovative business models. Sustainable Retail Practices: Champion eco-friendly initiatives and responsible retailing. Elevate Your Retail Journey: Retail Management goes beyond textbook knowledge—it's a transformative guide that equips you to excel as a retail leader. Whether you seek to optimize store operations, enhance customer loyalty, or navigate the e-commerce landscape, this book is your compass to retail success. Set your course for retail excellence! Secure your copy of Retail Management and unlock the potential to thrive in the exciting world of modern retail. |
| business intelligence in retail industry: AI-Powered Business Intelligence for Modern Organizations Natarajan, Arul Kumar, Galety, Mohammad Gouse, Iwendi, Celestine, Das, Deepthi, Shankar, Achyut, 2024-10-01 Technology’s rapid advancement has revolutionized how organizations gather, analyze, and utilize data. In this dynamic landscape, integrating artificial intelligence (AI) into business intelligence (BI) systems has emerged as a critical factor for driving informed decision-making and maintaining competitive advantage. This integration allows business to respond quickly to market changes, personalize customer experiences, and optimize operations with greater precision. As AI-driven BI tools continue to evolve, they empower organizations to harness vast amounts of data more effectively, making strategic decisions that are both timely and data-driven, thereby securing their position in an increasingly competitive marketplace. AI-Powered Business Intelligence for Modern Organizations provides a comprehensive overview of this transformative intersection, addressing the diverse challenges, opportunities, and future trends in this field. By exploring the integration of AI into BI systems, the text delves into how advanced analytics, machine learning, and automation are reshaping the way businesses operate. Covering topics such as augmented analytics, decision-making, and sustainability metrics, this book is an excellent resource for business leaders and executives, data scientists and analysts, IT and technology managers, academicians, researchers, graduate and postgraduate students, consultants, industry experts, and more. |
| business intelligence in retail industry: Applying Business Intelligence Initiatives in Healthcare and Organizational Settings Miah, Shah J., Yeoh, William, 2018-07-13 Data analysis is an important part of modern business administration, as efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Applying Business Intelligence Initiatives in Healthcare and Organizational Settings incorporates emerging concepts, methods, models, and relevant applications of business intelligence systems within problem contexts of healthcare and other organizational boundaries. Featuring coverage on a broad range of topics such as rise of embedded analytics, competitive advantage, and strategic capability, this book is ideally designed for business analysts, investors, corporate managers, and entrepreneurs seeking to advance their understanding and practice of business intelligence. |
| business intelligence in retail industry: AI Meets BI Lakshman Bulusu, Rosendo Abellera, 2020-11-03 With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI. |
| business intelligence in retail industry: Business Intelligence For Dummies Swain Scheps, 2011-02-04 You're intelligent, right? So you've already figured out that Business Intelligence can be pretty valuable in making the right decisions about your business. But you’ve heard at least a dozen definitions of what it is, and heard of at least that many BI tools. Where do you start? Business Intelligence For Dummies makes BI understandable! It takes you step by step through the technologies and the alphabet soup, so you can choose the right technology and implement a successful BI environment. You'll see how the applications and technologies work together to access, analyze, and present data that you can use to make better decisions about your products, customers, competitors, and more. You’ll find out how to: Understand the principles and practical elements of BI Determine what your business needs Compare different approaches to BI Build a solid BI architecture and roadmap Design, develop, and deploy your BI plan Relate BI to data warehousing, ERP, CRM, and e-commerce Analyze emerging trends and developing BI tools to see what else may be useful Whether you’re the business owner or the person charged with developing and implementing a BI strategy, checking out Business Intelligence For Dummies is a good business decision. |
| business intelligence in retail industry: Data Mining and Business Intelligence Stephan Kudyba, Richard Hoptroff, 2001-01-01 Annotation Provides an overview of data mining technology and how it is applied in a business environment. Material is not written in a technical style, but rather addresses the applied methodology behind implementing data mining techniques in the corporate environment. Explains how the technology evolved, overviews the methodologies that comprise the data mining spectrum, and looks at everyday business applications for data mining, in areas such as marketing and advertising promotions and pricing policies using econometric-based modeling, and using the Internet to help improve an organization's performance. Kudyba is an economic consultant. Hoptroff is an independent consultant with experience in data mining software. Annotation c. Book News, Inc., Portland, OR (booknews.com). |
| business intelligence in retail industry: Competing on Analytics Thomas H. Davenport, Jeanne G. Harris, 2007-03-06 You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics. |
| business intelligence in retail industry: Business Intelligence for the Enterprise Mike Biere, 2003 This text aims to help you to maximize the potential of Business Intelligence in your organization. It includes stories of companies that implemented BI - those that have succeeded and those that have failed. |
| business intelligence in retail industry: The Expert Guide to Retail Pricing Kiran Gange, 2023-07-07 Going under the hood of retail strategy, this book provides in-depth coverage of how retailers can leverage the latest in data analytics and technology to improve profitability and customer value through pricing. Retail pricing is not about dollars, pounds or euros, but the value a customer associates with a product, which can and does change over time. To maximize revenues and profits, pricing must be dynamic, strategic, and in today’s hyper-connected and -competitive world, scientific. Using technology to gather customer insights and create data-driven pricing approaches can also enhance the customer experience, improve vendor management, help monitor competitors, and ensure market efficiency – including the much-needed reduction of waste in the food sector. This book uses case studies from around the globe to illustrate the evolution of retailing and offers takeaways with each chapter to enable retailers to manage the future of pricing. Retail and pricing managers, retail sector consultants, and students of sales and marketing will welcome this book’s innovative solutions to one of bricks-and-mortar retailing’s most critical challenges. |
| business intelligence in retail industry: Big Data, Big Analytics Michael Minelli, Michele Chambers, Ambiga Dhiraj, 2013-01-22 Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more. |
| business intelligence in retail industry: Technology Innovation for Business Intelligence and Analytics (TIBIA) Haitham M. Alzoubi, |
| business intelligence in retail industry: Analytics Across the Enterprise Brenda L. Dietrich, Emily C. Plachy, Maureen F. Norton, 2014-05-15 How to Transform Your Organization with Analytics: Insider Lessons from IBM’s Pioneering Experience Analytics is not just a technology: It is a better way to do business. Using analytics, you can systematically inform human judgment with data-driven insight. This doesn’t just improve decision-making: It also enables greater innovation and creativity in support of strategy. Your transformation won’t happen overnight; however, it is absolutely achievable, and the rewards are immense. This book demystifies your analytics journey by showing you how IBM has successfully leveraged analytics across the enterprise, worldwide. Three of IBM’s pioneering analytics practitioners share invaluable real-world perspectives on what does and doesn’t work and how you can start or accelerate your own transformation. This book provides an essential framework for becoming a smarter enterprise and shows through 31 case studies how IBM has derived value from analytics throughout its business. Coverage Includes Creating a smarter workforce through big data and analytics More effectively optimizing supply chain processes Systematically improving financial forecasting Managing financial risk, increasing operational efficiency, and creating business value Reaching more B2B or B2C customers and deepening their engagement Optimizing manufacturing and product management processes Deploying your sales organization to increase revenue and effectiveness Achieving new levels of excellence in services delivery and reducing risk Transforming IT to enable wider use of analytics “Measuring the immeasurable” and filling gaps in imperfect data Whatever your industry or role, whether a current or future leader, analytics can make you smarter and more competitive. Analytics Across the Enterprise shows how IBM did it--and how you can, too. Learn more about IBM Analytics |
| business intelligence in retail industry: Encyclopedia of Business Analytics and Optimization Wang, John, 2014-02-28 As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal. |
| business intelligence in retail industry: Artificial Intelligence and Machine Learning in Business Management Sandeep Kumar Panda, Vaibhav Mishra, R. Balamurali, Ahmed A. Elngar, 2021-11-04 Artificial Intelligence and Machine Learning in Business Management The focus of this book is to introduce artificial intelligence (AI) and machine learning (ML) technologies into the context of business management. The book gives insights into the implementation and impact of AI and ML to business leaders, managers, technology developers, and implementers. With the maturing use of AI or ML in the field of business intelligence, this book examines several projects with innovative uses of AI beyond data organization and access. It follows the Predictive Modeling Toolkit for providing new insight on how to use improved AI tools in the field of business. It explores cultural heritage values and risk assessments for mitigation and conservation and discusses on-shore and off-shore technological capabilities with spatial tools for addressing marketing and retail strategies, and insurance and healthcare systems. Taking a multidisciplinary approach for using AI, this book provides a single comprehensive reference resource for undergraduate, graduate, business professionals, and related disciplines. |
| business intelligence in retail industry: Cross-Industry AI Applications Paramasivan, P., Rajest, S. Suman, Chinnusamy, Karthikeyan, Regin, R., John Joseph, Ferdin Joe, 2024-06-17 The rise of Artificial Intelligence (AI) amidst the backdrop of a world that is changing at lightning speed presents a whole new set of challenges. One of our biggest hurdles is more transparency in AI solutions. It's a complex issue, but one that we need to address if we want to ensure that the benefits of AI are accessible to everyone. Across diverse sectors such as healthcare, surveillance, and human-computer interaction, the inability to understand and evaluate AI's decision-making processes hinders progress and raises concerns about accountability. Cross-Industry AI Applications is a groundbreaking solution to illuminate the mysteries of AI-driven human behavior analysis. This pioneering book addresses the necessity of transparency and explainability in AI systems, particularly in analyzing human behavior. Compiling insights from leading experts and academics offers a comprehensive exploration of state-of-the-art methodologies, benchmarks, and systems for understanding and predicting human behavior using AI. Each chapter delves into novel approaches and real-world applications, from facial expressions to gesture recognition, providing invaluable knowledge for scholars and professionals alike. |
| business intelligence in retail industry: Solving Operational Business Intelligence with InfoSphere Warehouse Advanced Edition Whei-Jen Chen, Pat Bates, Timothy Donovan, Garrett Fitzsimons, Jon Lind, Rogerio Silva, IBM Redbooks, 2012-10-02 IBM® InfoSphere® Warehouse is the IBM flagship data warehouse platform for departmental data marts and enterprise data warehouses. It offers leading architecture, performance, backup, and recovery tools that help improve efficiency and reduce time to market through increased understanding of current data assets, while simplifying the daily operations of managing complex warehouse deployments. InfoSphere Warehouse Advanced Enterprise Edition delivers an enhanced set of database performance, management, and design tools. These tools assist companies in maintaining and increasing value from their warehouses, while helping to reduce the total cost of maintaining these complex environments. In this IBM Redbooks® publication we explain how you can build a business intelligence system with InfoSphere Warehouse Advanced Enterprise to manage and support daily business operations for an enterprise, to generate more income with lower cost. We describe the foundation of the business analytics, the Data Warehouse features and functions, and the solutions that can deliver immediate analytics solutions and help you drive better business outcomes. We show you how to use the advanced analytics of InfoSphere Warehouse Advanced Enterprise Edition and integrated tools for data modeling, mining, text analytics, and identifying and meeting the data latency requirements. We describe how the performance and storage optimization features can make building and managing a large data warehouse more affordable, and how they can help significantly reduce the cost of ownership. We also cover data lifecycle management and the key features of IBM Cognos® Business Intelligence. This book is intended for data warehouse professionals who are interested in gaining in-depth knowledge about the operational business intelligence solution for a data warehouse that the IBM InfoSphere Warehouse Advanced Enterprise Edition offers. |
| business intelligence in retail industry: Outside Insight Jorn Lyseggen, 2017-10-12 Is your business looking out? The world today is drowning in data. There is a treasure trove of valuable and underutilized insights that can be gleaned from information companies and people leave behind on the internet - our 'digital breadcrumbs' - from job postings, to online news, social media, online ad spend, patent applications and more. As a result, we're at the cusp of a major shift in the way businesses are managed and governed - moving from a focus solely on lagging, internal data, toward analyses that also encompass industry-wide, external data to paint a more complete picture of a brand's opportunities and threats and uncover forward-looking insights, in real time. Tomorrow's most successful brands are already embracing Outside Insight, benefitting from an information advantage while their competition is left behind. Drawing on practical examples of transformative, data-led decisions made by brands like Apple, Facebook, Barack Obama and many more, in Outside Insight, Meltwater CEO Jorn Lyseggen illustrates the future of corporate decision-making and offers a detailed plan for business leaders to implement Outside Insight thinking into their company mindset and processes. |
| business intelligence in retail industry: Open Source Data Warehousing and Business Intelligence Lakshman Bulusu, 2012-08-06 Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW & |
| business intelligence in retail industry: Business Intelligence Competency Centers Gloria J. Miller, Dagmar Bräutigam, Stefanie V. Gerlach, 2006-05-11 Transform data into action for competitive advantage The knowledge assets of an organization are becoming increasingly important for competitive advantage, and therefore, the way in which knowledge is created, renewed, and communicated is critical. This book provides practical insights into how this may be achieved through the establishment of a Business Intelligence Competency Centre and is a valuable read for 'information professionals.' --Bill Sturman, Information Architecture Project Manager The Open University, United Kingdom BI is more than technology and projects. BI must live in the organization--as a BICC. This book helps to make BI tangible and understandable, bringing it to life. --Miriam Eisenmann, Project Manager (PMP) CSC Ploenzke AG, Germany This book is a must-read for planning and implementing your BICC. It is a pragmatic guide that addresses a lot, if not all, of the questions you'll be asking yourself. Don't miss out on getting a head start from the people who thought this through from start to finish . . . Pray your competitors don't get hold of this book! --Claudia Imhoff, President Intelligent Solutions, Inc., USA Creating a BICC forces the organization to focus on the importance of centralizing the gathering, interpreting, and analyzing of information to create business insight. --Anne Ulyate, Group Manager Business Intelligence Mutual & Federal, South Africa BI is a highly visible element in the 'business value' trend for IT investments. Initiatives, such as competency centers, should empower user organizations to drive even more value out of their BI investments. --Marianne Kolding, Director, European ServicesIDC, United Kingdom |
| business intelligence in retail industry: Healthcare Business Intelligence Laura Madsen, 2012 This book will be constructed as a guidebook for healthcare organizations that are attempting BI/DW. It will address the primary functions of a business intelligence capability and how BI can ease the increasing regulatory reporting pressures on all healthcare organizations. Also included will be tables, checklists and a few forms. Tenative chapter contents: Chapter 1: What is Healthcare BI? Chapter 2: The Five Disciplines of Business Intelligence Chapter 3: The Importance of ETL Chapter 4: Starting with Data Governance Chapter 5: Creating a BI team Chapter 6: Data Modeling for Healthcare Chapter 7: Gaining Support for your BI program Chapter 8: Ensuring good User Adoption Chapter 9: Marketing Your BI Program Chapter 10: Maintaining Your BI Program-- |
| business intelligence in retail industry: Cyber Security Impact on Digitalization and Business Intelligence Haitham M. Alzoubi, Muhammad Turki Alshurideh, Taher M. Ghazal, 2024-01-03 This book takes a unique approach by exploring the connection between cybersecurity, digitalization, and business intelligence. In today's digital landscape, cybersecurity is a crucial aspect of business operations. Meanwhile, organizations continue to leverage digital technologies for their day-to-day operations. They must be aware of the risks associated with cyber-attacks and implement robust cybersecurity measures to protect their assets. It provides practical insights and solutions to help businesses better understand the impact of cybersecurity on their digitalization and business intelligence strategies. It provides practical insights and solutions for implementing cybersecurity measures in organizations and covers a wide range of topics, including threat intelligence, risk management, compliance, cloud security, and IoT security. The book takes a holistic approach and explores the intersection of cybersecurity, digitalization, and business intelligence and examines the possible challenges and opportunities. |
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
