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| examples of business intelligence: 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. |
| examples of business intelligence: E-Business Intelligence Bernard Liautaud, 2001 Publisher Fact Sheet How to leverage corporate information for reduced costs & increased profits. |
| examples of business intelligence: 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. |
| examples of business intelligence: Business Intelligence Jerzy Surma, 2011-03-06 This book is about using business intelligence as a management information system for supporting managerial decision making. It concentrates primarily on practical business issues and demonstrates how to apply data warehousing and data analytics to support business decision making. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. All examples are based on the most recent achievements in business intelligence. Finally this book outlines an overview of a methodology that takes into account the complexity of developing applications in an integrated business intelligence environment. This book is written for managers, business consultants, and undergraduate and postgraduates students in business administration. |
| examples of business intelligence: Financial Business Intelligence Nils H. Rasmussen, Paul S. Goldy, Per O. Solli, 2002-10-15 Turn storehouses of data into a strategic tool Business intelligence has recently become a word used by almostevery CFO, controller, and analyst. After having spent the lastdecade implementing Enterprise Resource Planning software and othermission critical solutions, companies now have large databases withtransactional data sitting in their computer rooms. Now, finally,the technology has reached a point where it is possible- in almostreal time-to quickly and easily analyze the financial data in thecorporate databases, to be able to make more intelligent businessdecisions. This book will help financial managers understand thetrends, technology, software selection, and implementation offinancial business intelligence (financial BI) software. With adictionary of business intelligence terms, a comprehensive list ofRequest for Proposal questions, and examples of popular financialbusiness intelligence reroutes and user interfaces, this bookenables managers to measure their companies' business intelligenceand maximize its value. |
| examples of business intelligence: 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. |
| examples of business intelligence: Successful Business Intelligence: Secrets to Making BI a Killer App Cindi Howson, 2007-12-17 Praise for Successful Business Intelligence If you want to be an analytical competitor, you've got to go well beyond business intelligence technology. Cindi Howson has wrapped up the needed advice on technology, organization, strategy, and even culture in a neat package. It's required reading for quantitatively oriented strategists and the technologists who support them. --Thomas H. Davenport, President's Distinguished Professor, Babson College and co-author, Competing on Analytics When used strategically, business intelligence can help companies transform their organization to be more agile, more competitive, and more profitable. Successful Business Intelligence offers valuable guidance for companies looking to embark upon their first BI project as well as those hoping to maximize their current deployments. --John Schwarz, CEO, Business Objects A thoughtful, clearly written, and carefully researched examination of all facets of business intelligence that your organization needs to know to run its business more intelligently and exploit information to its fullest extent. --Wayne Eckerson, Director, TDWI Research Using real-world examples, Cindi Howson shows you how to use business intelligence to improve the performance, and the quality, of your company. --Bill Baker, Distinguished Engineer & GM, Business Intelligence Applications, Microsoft Corporation This book outlines the key steps to make BI an integral part of your company's culture and demonstrates how your company can use BI as a competitive differentiator. --Robert VanHees, CFO, Corporate Express Given the trend to expand the business analytics user base, organizations are faced with a number of challenges that affect the success rate of these projects. This insightful book provides practical advice on improving that success rate. --Dan Vesset, Vice President, Business Analytics Solution Research, IDC |
| examples of business intelligence: Business Intelligence Success Factors Olivia Parr Rud, 2009-06-02 Over the last few decades, the growth of Business Intelligence has enabled companies to streamline many processes and expand into new markets on an unprecedented scale. New BI technologies are also enabling mass collaboration and innovation. However, implementation of these BI solutions often gives rise to new challenges. Business Intelligence Success Factors shows you how to turn those challenges into opportunities by mastering five key skills. Olivia Parr Rud shares insights gained from her two decades of experience in Business Intelligence to offer the latest practices that are emerging in organizational development. Written to help enhance your understanding of the current business climate and to provide the tools necessary to thrive in this new global economy, Business Intelligence Success Factors examines the components of chaos theory, complex adaptive systems, quantum physics, and evolutionary biology. A scientific framework for these new corporate issues helps explain why developing these key competencies are critical, given the speed of change, globalization, as well as advancements in technology and Business Intelligence. Divided into four cohesive parts, Business Intelligence Success Factors explores: The current business landscape as well as the latest scientific research: today's business realities and how and why they can lead to chaos New scientific models for viewing the global economy The five essential competencies—Communication, Collaboration, Innovation, Adaptability, and Leadership—that improve an organization's ability to leverage the new opportunities in a volatile global economy Profiles of several amazing leaders who are working to make a difference Cutting-edge research and case studies via invited contributors offering a wealth of knowledge and experience Move beyond mere survival to realize breakaway success in the global economy with the practical guidance found in Business Intelligence Success Factors. |
| examples of business intelligence: Real-time Strategy and Business Intelligence Marko Kohtamäki, 2017-07-05 This book discusses and conceptualizes practices on real-time strategy, focusing on the interplay between strategy and business intelligence. Combining strategic practices and business intelligence systems, the authors demonstrate how managerial practices can be developed in the age of digitization. Also developing the concept of strategic agility, the book provides perspectives from a range of disciplines including strategic practices and decision making, customer relationship management, human resource management, competitive intelligence, supplier network management and business intelligence systems. Presenting managerial frameworks and guidelines, Real-time Strategy and Business Intelligence explores how to improve utilization of business intelligence systems in real-time decision making. Providing practical and future-oriented insights backed by examples and best practices, the authors present a clearly conceptualized theoretical framework. |
| examples of business intelligence: 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 |
| examples of business intelligence: Handbook of Research on Applied AI for International Business and Marketing Applications Christiansen, Bryan, Škrinjari?, Tihana, 2020-09-25 Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students. |
| examples of business intelligence: Business Intelligence Tools for Small Companies Albert Nogués, Juan Valladares, 2017-05-25 Learn how to transition from Excel-based business intelligence (BI) analysis to enterprise stacks of open-source BI tools. Select and implement the best free and freemium open-source BI tools for your company’s needs and design, implement, and integrate BI automation across the full stack using agile methodologies. Business Intelligence Tools for Small Companies provides hands-on demonstrations of open-source tools suitable for the BI requirements of small businesses. The authors draw on their deep experience as BI consultants, developers, and administrators to guide you through the extract-transform-load/data warehousing (ETL/DWH) sequence of extracting data from an enterprise resource planning (ERP) database freely available on the Internet, transforming the data, manipulating them, and loading them into a relational database. The authors demonstrate how to extract, report, and dashboard key performance indicators (KPIs) in a visually appealing format from the relational database management system (RDBMS). They model the selection and implementation of free and freemium tools such as Pentaho Data Integrator and Talend for ELT, Oracle XE and MySQL/MariaDB for RDBMS, and Qliksense, Power BI, and MicroStrategy Desktop for reporting. This richly illustrated guide models the deployment of a small company BI stack on an inexpensive cloud platform such as AWS. What You'll Learn You will learn how to manage, integrate, and automate the processes of BI by selecting and implementing tools to: Implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure Extract data from any enterprise resource planning (ERP) tool Process and integrate BI data using open-source extract-transform-load (ETL) tools Query, report, and analyze BI data using open-source visualization and dashboard tools Use a MOLAP tool to define next year's budget, integrating real data with target scenarios Deploy BI solutions and big data experiments inexpensively on cloud platforms Who This Book Is For Engineers, DBAs, analysts, consultants, and managers at small companies with limited resources but whose BI requirements have outgrown the limitations of Excel spreadsheets; personnel in mid-sized companies with established BI systems who are exploring technological updates and more cost-efficient solutions |
| examples of business intelligence: Business Intelligence Elizabeth Vitt, Michael Luckevich, Stacia Misner, 2002 This 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 at the fingertips of decision makers. It describes 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. Real-life case studies show how world leaders in finance, manufacturing, and retail have successfully implemented business intelligence solutions and detail the benefits they have reaped. |
| examples of business intelligence: Artificial Intelligence in Practice Bernard Marr, 2019-04-15 Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce. |
| examples of business intelligence: 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. |
| examples of business intelligence: 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. |
| examples of business intelligence: Business Intelligence Applied Michael S. Gendron, 2012-10-19 Expert guidance for building an information communication and technology infrastructure that provides best in business intelligence Enterprise performance management (EPM) technology has been rapidly advancing, especially in the areas of predictive analysis and cloud-based solutions. Business intelligence caught on as a concept in the business world as the business strategy application of data warehousing in the early 2000s. With the recent surge in interest in data analytics and big data, it has seen a renewed level of interest as the ability of a business to find the valuable data in a timely—and competitive—fashion. Business Intelligence Applied reveals essential information for building an optimal and effective information and communication technology (ICT) infrastructure. Defines ICT infrastructure Examines best practices for documenting business change and for documenting technology recommendations Includes examples and cases from Europe and Asia Written for business intelligence staff, CIOs, CTOs, and technology managers With examples and cases from Europe and Asia, Business Intelligence Applied expertly covers business intelligence, a hot topic in business today as a key element to business and data analytics. |
| examples of business intelligence: 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. |
| examples of business intelligence: Data Science and Its Applications Aakanksha Sharaff, G R Sinha, 2021-08-18 The term data being mostly used, experimented, analyzed, and researched, Data Science and its Applications finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications. |
| examples of business intelligence: Cyclopaedia of Commercial and Business Anecdotes Richard Miller Devens, 1865 |
| examples of business intelligence: Fundamentals of Business Intelligence Wilfried Grossmann, Stefanie Rinderle-Ma, 2015-06-02 This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided. The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples. |
| examples of business intelligence: Seven Methods for Transforming Corporate Data Into Business Intelligence Vasant Dhar, Roger Stein, 1997 Information systems: past, present, and emerging; Intelligence density a metric for knowledge work; The vocabulary of intelligence density; Method one: data-driven decision support; Method two: evolving solutions: genetic algorithms; Method three: simulating the brain to solve problems: neural networks; Method four: putting expert resoning in a box: rule-based systems; Method five: dealing with linguistic ambiguity: fuzzy logic; Method six: soilving problems by analogy case-based resoning; Method seven: deriving rules from data: machine learning; Appendix saving time and money with object; Appendix case studies. |
| examples of business intelligence: Business Intelligence Techniques Murugan Anandarajan, Asokan Anandarajan, Cadambi A. Srinivasan, 2012-11-02 Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment. |
| examples of business intelligence: Business Intelligence Roadmap Larissa Terpeluk Moss, S. Atre, 2003 This software will enable the user to learn about business intelligence roadmap. |
| examples of business intelligence: Developing Business Intelligence Apps for SharePoint David Feldman, Jason Himmelstein, 2013-07-02 Create dynamic business intelligence (BI) solutions for SharePoint faster and with more capabilities than previously possible. With this book, you’ll learn the entire process—from high-level concepts to development and deployment—for building data-rich BI applications with Visual Studio LightSwitch, SQL Server 2012, and a host of related Microsoft technologies. You’ll learn practical techniques and patterns necessary to use all of these technologies together as you build an example application through the course of the book, step by step. Discover how to solve real problems, using BI solutions that will evolve to meet future needs. Learn the fundamentals of SharePoint, LightSwitch, and SQL Server 2012 Get a solid grounding in BI application basics and database design principles Use LightSwitch to build a help desk app, including data model design and SharePoint data integration Build a tabular cube with Microsoft’s Business Intelligence Semantic Model (BISM) Dive into the data visualization stack, including Excel and SQL Server Reporting Services Create reports with Excel Services, Report Builder, and PowerView Use tips and tricks for setting up your BI application development environment |
| examples of business intelligence: Big Data Viktor Mayer-Schönberger, Kenneth Cukier, 2013 A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large. |
| examples of business intelligence: Smart Intelligent Computing and Applications Suresh Chandra Satapathy, Vikrant Bhateja, Swagatam Das, 2018-11-04 The proceedings covers advanced and multi-disciplinary research on design of smart computing and informatics. The theme of the book broadly focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solution to varied problems in society, environment and industries. The volume publishes quality work pertaining to the scope of the conference which is extended towards deployment of emerging computational and knowledge transfer approaches, optimizing solutions in varied disciplines of science, technology and healthcare. |
| examples of business intelligence: Sport Business Analytics C. Keith Harrison, Scott Bukstein, 2016-11-18 Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics. |
| examples of business intelligence: Business Intelligence Strategy John Boyer, Bill Frank, Brian Green, Tracy Harris, Kay Van De Vanter, 2010 Geared toward IT management and business executives seeking to excel in business intelligence initiatives, this practical guide explores creating business alignment strategies that help prioritize business requirements, build organizational and cultural strategies, increase IT efficiency, and promote user adoption. Business intelligence, together with business analytics and performance management, eliminates information overload by organizing the massive amounts of information available in the modern enterprise. Addressing the challenges of business intelligence operations, this resource supports the goal of better business decision making and identifying unrealized opportunities. Each chapter includes a checklist of recommended approaches and a strategy overview template. |
| examples of business intelligence: Agile Analytics Ken Collier, 2012 Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. However, conventional Agile methods must be carefully adapted to address the unique characteristics of DW/BI projects. In Agile Analytics, Agile pioneer Ken Collier shows how to do just that. Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets and how to support enormous and fast-growing data volumes. Collier's techniques offer optimal value whether your projects involve back-end data management, front-end business analysis, or both. Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your Agile DW/BI project community can collaborate toward success Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, database administrator, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way. |
| examples of business intelligence: Business Intelligence Efraim Turban, 2013-07-17 For courses on Business Intelligence or Decision Support Systems. A managerial approach to understanding business intelligence systems. To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice. The second edition features updated information on data mining, text and web mining, and implementation and emerging technologies. |
| examples of business intelligence: Business Intelligence and Data Mining Anil Maheshwari, 2014-12-31 “This book is a splendid and valuable addition to this subject. The whole book is well written and I have no hesitation to recommend that this can be adapted as a textbook for graduate courses in Business Intelligence and Data Mining.” Dr. Edi Shivaji, Des Moines, Iowa “As a complete novice to this area just starting out on a MBA course I found the book incredibly useful and very easy to follow and understand. The concepts are clearly explained and make it an easy task to gain an understanding of the subject matter.” -- Mr. Craig Domoney, South Africa. Business Intelligence and Data Mining is a conversational and informative book in the exploding area of Business Analytics. Using this book, one can easily gain the intuition about the area, along with a solid toolset of major data mining techniques and platforms. This book can thus be gainfully used as a textbook for a college course. It is also short and accessible enough for a busy executive to become a quasi-expert in this area in a couple of hours. Every chapter begins with a case-let from the real world, and ends with a case study that runs across the chapters. |
| examples of business intelligence: Business Analytics for Managers Gert Laursen, Jesper Thorlund, 2010-07-13 While business analytics sounds like a complex subject, this book provides a clear and non-intimidating overview of the topic. Following its advice will ensure that your organization knows the analytics it needs to succeed, and uses them in the service of key strategies and business processes. You too can go beyond reporting!—Thomas H. Davenport, President's Distinguished Professor of IT and Management, Babson College; coauthor, Analytics at Work: Smarter Decisions, Better Results Deliver the right decision support to the right people at the right time Filled with examples and forward-thinking guidance from renowned BA leaders Gert Laursen and Jesper Thorlund, Business Analytics for Managers offers powerful techniques for making increasingly advanced use of information in order to survive any market conditions. Take a look inside and find: Proven guidance on developing an information strategy Tips for supporting your company's ability to innovate in the future by using analytics Practical insights for planning and implementing BA How to use information as a strategic asset Why BA is the next stepping-stone for companies in the information age today Discussion on BA's ever-increasing role Improve your business's decision making. Align your business processes with your business's objectives. Drive your company into a prosperous future. Taking BA from buzzword to enormous value-maker, Business Analytics for Managers helps you do it all with workable solutions that will add tremendous value to your business. |
| examples of business intelligence: Business Intelligence David Loshin, 2012-11-27 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 |
| examples of business intelligence: Business Intelligence Demystified Anoop Kumar V K, 2021-09-25 Clear your doubts about Business Intelligence and start your new journey KEY FEATURES ● Includes successful methods and innovative ideas to achieve success with BI. ● Vendor-neutral, unbiased, and based on experience. ● Highlights practical challenges in BI journeys. ● Covers financial aspects along with technical aspects. ● Showcases multiple BI organization models and the structure of BI teams. DESCRIPTION The book demystifies misconceptions and misinformation about BI. It provides clarity to almost everything related to BI in a simplified and unbiased way. It covers topics right from the definition of BI, terms used in the BI definition, coinage of BI, details of the different main uses of BI, processes that support the main uses, side benefits, and the level of importance of BI, various types of BI based on various parameters, main phases in the BI journey and the challenges faced in each of the phases in the BI journey. It clarifies myths about self-service BI and real-time BI. The book covers the structure of a typical internal BI team, BI organizational models, and the main roles in BI. It also clarifies the doubts around roles in BI. It explores the different components that add to the cost of BI and explains how to calculate the total cost of the ownership of BI and ROI for BI. It covers several ideas, including unconventional ideas to achieve BI success and also learn about IBI. It explains the different types of BI architectures, commonly used technologies, tools, and concepts in BI and provides clarity about the boundary of BI w.r.t technologies, tools, and concepts. The book helps you lay a very strong foundation and provides the right perspective about BI. It enables you to start or restart your journey with BI. WHAT YOU WILL LEARN ● Builds a strong conceptual foundation in BI. ● Gives the right perspective and clarity on BI uses, challenges, and architectures. ● Enables you to make the right decisions on the BI structure, organization model, and budget. ● Explains which type of BI solution is required for your business. ● Applies successful BI ideas. WHO THIS BOOK IS FOR This book is a must-read for business managers, BI aspirants, CxOs, and all those who want to drive the business value with data-driven insights. TABLE OF CONTENTS 1. What is Business Intelligence? 2. Why do Businesses need BI? 3. Types of Business Intelligence 4. Challenges in Business Intelligence 5. Roles in Business Intelligence 6. Financials of Business Intelligence 7. Ideas for Success with BI 8. Introduction to IBI 9. BI Architectures 10. Demystify Tech, Tools, and Concepts in BI |
| examples of business intelligence: Business Intelligence and Performance Management Peter Rausch, Alaa F. Sheta, Aladdin Ayesh, 2013-02-15 During the 21st century business environments have become more complex and dynamic than ever before. Companies operate in a world of change influenced by globalisation, volatile markets, legal changes and technical progress. As a result, they have to handle growing volumes of data and therefore require fast storage, reliable data access, intelligent retrieval of information and automated decision-making mechanisms, all provided at the highest level of service quality. Successful enterprises are aware of these challenges and efficiently respond to the dynamic environment in which their business operates. Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges and provide techniques to enable effective business change. The important aspects of both topics are discussed within this state-of-the-art volume. It covers the strategic support, business applications, methodologies and technologies from the field, and explores the benefits, issues and challenges of each. Issues are analysed from many different perspectives, ranging from strategic management to data technologies, and the different subjects are complimented and illustrated by numerous examples of industrial applications. Contributions are authored by leading academics and practitioners representing various universities, research centres and companies worldwide. Their experience covers multiple disciplines and industries, including finance, construction, logistics, and public services, amongst others. Business Intelligence and Performance Management is a valuable source of reference for graduates approaching MSc or PhD programs and for professionals in industry researching in the fields of BI and PM for industrial application. |
| examples of business intelligence: Integration Challenges for Analytics, Business Intelligence, and Data Mining Azevedo, Ana, Santos, Manuel Filipe, 2020-12-11 As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students. |
| examples of business intelligence: Data Virtualization for Business Intelligence Systems Rick van der Lans, 2012-07-25 Annotation In this book, Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. |
| examples of business intelligence: Mastering Business Intelligence with MicroStrategy Dmitry Anoshin, Himani Rana, Ning Ma, 2016-07-29 Build world-class enterprise Business Intelligence solutions with MicroStrategy 10 About This Book Fix the gap between BI tools and implementation/integration processes with big data and predictive analytics using this comprehensive guide to MicroStrategy 10 Highly practical, example-rich guide that lets you implement business intelligence with MicroStrategy 10 in your organization Create the best user experience with BI dashboards using MicroStrategy using this up-to-date, comprehensive guide Who This Book Is For This book is intended for BI, DWH, ETL developers, BI/DWH/Analytics managers, analysts, and business users who already have MicroStrategy in their organization and want to take it to the next level in order to increase performance and improve user experience. In addition, it helps the reader to migrate from MicroStrategy 9 to MicroStrategy 10 and to start using the new capabilities. What You Will Learn Explore various visualization techniques for presenting analyzed data Customize MicroStrategy in order to meet your business requirements Develop and design mobile dashboards Use the advanced techniques such as designing reports, documents and interactive dashboards for building dashboards Understand the concepts of data discovery and Desktop capabilities Explore the best practices for Microstrategy system administration Find and fix issues based on connections, environment or documents Integrate third party ESRI map tools with MicroStrategy to create geo based reports In Detail Business intelligence is becoming more important by the day, with cloud offerings and mobile devices gaining wider acceptance and achieving better market penetration. MicroStrategy Reporting Suite is an absolute leader in the BI market and offers rich capabilities from basic data visualizations to predictive analytics. It lets you various delivery methods such as the Web, desktops, and mobiles. Using real-world BI scenarios, this book helps you to implement Business Analytics solutions in big e-commerce companies. It kicks off with MicroStrategy 10 features and then covers schema design models and techniques. Building upon your existing knowledge, the book will teach you advanced techniques for building documents and dashboards. It further teaches various graphical techniques for presenting data for analysis using maps, graphs, and advanced charts. Although MicroStrategy has rich functionality, the book will show how to customize it in order to meet your business requirements. You will also become familiar with the native analytical functions that will help you to maximize the impact of BI solutions with powerful predictive analytics. Furthermore, the book will focus on MicroStrategy Mobile Analytics along with data discovery and desktop capabilities such as connecting various data sources and building interactive dashboards. The book will also uncover best practices, troubleshooting techniques for MicroStrategy system administration, and also security and authentication techniques. Lastly, you will learn to use Hadoop for MicroStrategy reporting. By the end of the book, you will become proficient in evaluating any BI software in order to choose the best one that meets all business requirements. Style and approach This book will be focusing on providing extensive guide to plan how to design and develop complex BI architecture for real world scenario, using Microstrategy 10, best practices and collected experience working with BI, predictive analytics, and Microstrategy and big data. |
| examples of business intelligence: Hands-On Business Intelligence with DAX Ian Horne, 2020-01-31 Implement business intelligence (BI), data modeling, and data analytics within Microsoft products such as Power BI, SQL Server, and Excel Key FeaturesUnderstand the ins and outs of DAX expressions and querying functions with the help of easy-to-follow examplesManipulate data of varying complexity and optimize BI workflows to extract key insightsCreate, monitor, and improve the performance of models by writing clean and robust DAX queriesBook Description Data Analysis Expressions (DAX) is known for its ability to increase efficiency by extracting new information from data that is already present in your model. With this book, you’ll learn to use DAX’s functionality and flexibility in the BI and data analytics domains. You’ll start by learning the basics of DAX, along with understanding the importance of good data models, and how to write efficient DAX formulas by using variables and formatting styles. You’ll then explore how DAX queries work with the help of examples. The book will guide you through optimizing the BI workflow by writing powerful DAX queries. Next, you’ll learn to manipulate and load data of varying complexity within Microsoft products such as Power BI, SQL Server, and Excel Power Pivot. You’ll then discover how to build and extend your data models to gain additional insights, before covering progressive DAX syntax and functions to understand complex relationships in DAX. Later, you’ll focus on important DAX functions, specifically those related to tables, date and time, filtering, and statistics. Finally, you’ll delve into advanced topics such as how the formula and storage engines work to optimize queries. By the end of this book, you’ll have gained hands-on experience in employing DAX to enhance your data models by extracting new information and gaining deeper insights. What you will learnUnderstand DAX, from the basics through to advanced topics, and learn to build effective data modelsWrite and use DAX functions and expressions with the help of hands-on examplesDiscover how to handle errors in your DAX code, and avoid unwanted resultsLoad data into a data model using Power BI, Excel Power Pivot, and SSAS TabularCover DAX functions such as date, time, and time intelligence using code examplesGain insights into data by using DAX to create new informationUnderstand the DAX VertiPaq engine and how it can help you optimize data modelsWho this book is for This book is for data analysts, business analysts, BI developers, or SQL users who want to make the best use of DAX in the BI and data analytics domain with the help of examples. Some understanding of BI concepts is mandatory to fully understand the concepts covered in the book. |
23 Real-World Examples of Business Intelligence - NetSuite
Apr 16, 2021 · Business intelligence refers to the technology that enables businesses to organize, analyze and contextualize business data from around the company. BI includes multiple tools …
21 Business Intelligence Applications and Examples in 2024
Aug 6, 2024 · Finding ways to boost sales, understand user-product interactions and personalize recommendations have led to the widespread adoption of business intelligence tools. As a …
25 Real-World Examples of Business Intelligence in 2025
Explore 25 real-world examples of how businesses use Business Intelligence (BI) to improve decision-making, optimize operations, and drive growth.
7 Real-World Examples of Business Intelligence - Atlassian
Let’s dive into seven examples of business intelligence used by these types of companies. 1. Koodos proves their concept. Koodos is a new startup from Harvard Business School’s Rock …
13 business intelligence examples across different industries
Jan 28, 2025 · Business intelligence (BI) is the use of specialized software and tools to analyze and transform data into actionable insights. Using BI, you can present complex information in …
17 Real-World Examples Where Business Intelligence Makes a …
Apr 25, 2025 · In this article, we’ll explore 17 real-world business intelligence examples across an array of industries, from retail and healthcare to e-commerce and agriculture. These stories …
The 7 Top Business Intelligence Examples of 2025 - SelectHub
May 24, 2025 · Let’s look at some business intelligence examples from global market champions that use these tools: 1. Starbucks. Have you ever wondered how your favorite coffee shops use …
8 real-world business intelligence examples by industry - Celonis
Apr 24, 2024 · Real-world business intelligence examples from across a range of different industries, including banking, CPG, energy, healthcare, manufacturing and more.
6 Real-World Examples of Business Intelligence in Action - G2
Oct 24, 2024 · To offer deeper insights into real-world applications of BI, we spoke with six business leaders across various industries. They shared how they use BI platforms and …
20 Real-world Examples of Business Intelligence (BI) in 2025
Nov 21, 2022 · There are countless real-world examples of business intelligence used by renowned brands and setting a new benchmark in the market. I’ve mentioned some of the case …
23 Real-World Examples of Business Intelligence - NetSuite
Apr 16, 2021 · Business intelligence refers to the technology that enables businesses to organize, analyze and contextualize business data from around the company. BI includes multiple tools …
21 Business Intelligence Applications and Examples in 2024
Aug 6, 2024 · Finding ways to boost sales, understand user-product interactions and personalize recommendations have led to the widespread adoption of business intelligence tools. As a …
25 Real-World Examples of Business Intelligence in 2025
Explore 25 real-world examples of how businesses use Business Intelligence (BI) to improve decision-making, optimize operations, and drive growth.
7 Real-World Examples of Business Intelligence - Atlassian
Let’s dive into seven examples of business intelligence used by these types of companies. 1. Koodos proves their concept. Koodos is a new startup from Harvard Business School’s Rock …
13 business intelligence examples across different industries
Jan 28, 2025 · Business intelligence (BI) is the use of specialized software and tools to analyze and transform data into actionable insights. Using BI, you can present complex information in …
17 Real-World Examples Where Business Intelligence Makes a …
Apr 25, 2025 · In this article, we’ll explore 17 real-world business intelligence examples across an array of industries, from retail and healthcare to e-commerce and agriculture. These stories …
The 7 Top Business Intelligence Examples of 2025 - SelectHub
May 24, 2025 · Let’s look at some business intelligence examples from global market champions that use these tools: 1. Starbucks. Have you ever wondered how your favorite coffee shops …
8 real-world business intelligence examples by industry - Celonis
Apr 24, 2024 · Real-world business intelligence examples from across a range of different industries, including banking, CPG, energy, healthcare, manufacturing and more.
6 Real-World Examples of Business Intelligence in Action - G2
Oct 24, 2024 · To offer deeper insights into real-world applications of BI, we spoke with six business leaders across various industries. They shared how they use BI platforms and …
20 Real-world Examples of Business Intelligence (BI) in 2025
Nov 21, 2022 · There are countless real-world examples of business intelligence used by renowned brands and setting a new benchmark in the market. I’ve mentioned some of the …
23 Real-World Examples of Business Intelligence - NetS…
Apr 16, 2021 · Business intelligence refers to the technology that enables businesses to organize, analyze and contextualize business data from …
21 Business Intelligence Applications and Examples i…
Aug 6, 2024 · Finding ways to boost sales, understand user-product interactions and personalize recommendations have led to the …
25 Real-World Examples of Business Intelligence in 2025
Explore 25 real-world examples of how businesses use Business Intelligence (BI) to improve decision-making, optimize operations, and drive growth.
7 Real-World Examples of Business Intelligence - Atlas…
Let’s dive into seven examples of business intelligence used by these types of companies. 1. Koodos proves their concept. Koodos is a new …
13 business intelligence examples across different in…
Jan 28, 2025 · Business intelligence (BI) is the use of specialized software and tools to analyze and transform data into actionable insights. Using BI, …
23 Real-World Examples of Business Intelligence - NetSuite
Apr 16, 2021 · Business intelligence refers to the technology that enables businesses to organize, analyze and contextualize business data from around the company. BI includes multiple tools …
21 Business Intelligence Applications and Examples in 2024
Aug 6, 2024 · Finding ways to boost sales, understand user-product interactions and personalize recommendations have led to the widespread adoption of business intelligence tools. As a …
25 Real-World Examples of Business Intelligence in 2025
Explore 25 real-world examples of how businesses use Business Intelligence (BI) to improve decision-making, optimize operations, and drive growth.
7 Real-World Examples of Business Intelligence - Atlassian
Let’s dive into seven examples of business intelligence used by these types of companies. 1. Koodos proves their concept. Koodos is a new startup from Harvard Business School’s Rock …
13 business intelligence examples across different industries
Jan 28, 2025 · Business intelligence (BI) is the use of specialized software and tools to analyze and transform data into actionable insights. Using BI, you can present complex information in …
17 Real-World Examples Where Business Intelligence Makes a …
Apr 25, 2025 · In this article, we’ll explore 17 real-world business intelligence examples across an array of industries, from retail and healthcare to e-commerce and agriculture. These stories …
The 7 Top Business Intelligence Examples of 2025 - SelectHub
May 24, 2025 · Let’s look at some business intelligence examples from global market champions that use these tools: 1. Starbucks. Have you ever wondered how your favorite coffee shops …
8 real-world business intelligence examples by industry - Celonis
Apr 24, 2024 · Real-world business intelligence examples from across a range of different industries, including banking, CPG, energy, healthcare, manufacturing and more.
6 Real-World Examples of Business Intelligence in Action - G2
Oct 24, 2024 · To offer deeper insights into real-world applications of BI, we spoke with six business leaders across various industries. They shared how they use BI platforms and …
20 Real-world Examples of Business Intelligence (BI) in 2025
Nov 21, 2022 · There are countless real-world examples of business intelligence used by renowned brands and setting a new benchmark in the market. I’ve mentioned some of the …
