| business intelligence and analytics pdf: Business Intelligence and Analytics Ramesh Sharda, Dursun Delen, Efraim Turban, Peng Liang Ting, 2014 Appropriate for all courses in Decision Support Systems (DSS), computerized decision making tools, and management support systems. Decision Support and Business Intelligence Systems 10e provides the only comprehensive, up-to-date guide to today's revolutionary management support system technologies, and showcases how they can be used for better decision-making. The 10th edition focuses on Business Intelligence (BI) and analytics for enterprise decision support in a more streamlined book. In addition to traditional decision support applications, this edition expands the reader's understanding of the various types of analytics by providing examples, products, services, and exercises by discussing Web-related issues throughout the text. |
| business intelligence and analytics pdf: The Support of Decision Processes with Business Intelligence and Analytics Martin Kowalczyk, 2017-08-22 In his research, Martin Kowalczyk empirically investigates the challenges of designing and establishing successful decision support with Business Intelligence and Analytics (BI&A). The results from his work elucidate organizational and individual perspectives of BI&A support in decision processes. The organizational perspective considers the processual aspects of decision making and addresses process phases, roles and their interactions. The individual perspective reflects upon decision making of human individuals including their cognition and behaviors involved in decision making. The support of managerial decision making with BI&A gains increasing priority for many businesses in their desire to achieve better decision outcomes and improved organizational performance. |
| business intelligence and analytics pdf: Business Intelligence Rimvydas Skyrius, 2022-03-09 This book examines the managerial dimensions of business intelligence (BI) systems. It develops a set of guidelines for value creation by implementing business intelligence systems and technologies. In particular the book looks at BI as a process – driven by a mix of human and technological capabilities – to serve complex information needs in building insights and providing aid in decision making. After an introduction to the key concepts of BI and neighboring areas of information processing, the book looks at the complexity and multidimensionality of BI. It tackles both data integration and information integration issues. Bodies of knowledge and other widely accepted collections of experience are presented and turned into lessons learned. Following a straightforward introduction to the processes and technologies of BI the book embarks on BI maturity and agility, the components, drivers and inhibitors of BI culture and soft BI factors like attention, sense and trust. Eventually the book attempts to provide a holistic view on business intelligence, possible structures and tradeoffs and embarks to provide an outlook on possible developments in BI and analytics. |
| business intelligence and analytics pdf: Decision Support, Analytics, and Business Intelligence, Third Edition Daniel J. Power, Ciara Heavin, 2017-06-08 Rapid technology change is impacting organizations large and small. Mobile and Cloud computing, the Internet of Things (IoT), and “Big Data” are driving forces in organizational digital transformation. Decision support and analytics are available to many people in a business or organization. Business professionals need to learn about and understand computerized decision support for organizations to succeed. This text is targeted to busy managers and students who need to grasp the basics of computerized decision support, including: What is analytics? What is a decision support system? What is “Big Data”? What are “Big Data” business use cases? Overall, it addresses 61 fundamental questions. In a short period of time, readers can “get up to speed” on decision support, analytics, and business intelligence. The book then provides a quick reference to important recurring questions. |
| business intelligence and analytics pdf: Video Analytics for Business Intelligence Caifeng Shan, Fatih Porikli, Tao Xiang, Shaogang Gong, 2012-04-07 Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the shop; and what are the frequent paths), and to measure operational efficiency for improving customer experience. Video analytics has the enormous potential for non-security oriented commercial applications. This book presents the latest developments on video analytics for business intelligence applications. It provides both academic and commercial practitioners an understanding of the state-of-the-art and a resource for potential applications and successful practice. |
| business intelligence and analytics pdf: 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. |
| business intelligence and analytics pdf: 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 and analytics pdf: TRAC: Trends in Analytical Chemistry U A Th Brinkman, A. E. Bruno, A. L. Burlingame, 2013-09-17 TRAC: Trends in Analytical Chemistry, Volume 10 presents relevant topics in global analytical chemistry research. This book discusses the potential of flow injection analysis for water quality monitoring. Organized into 27 parts encompassing 67 chapters, this book begins with an overview of the amount of published information on analytical chemistry research. This text then examines the analytical technique in the electrophoretic separations in narrow bore tubes, which is capable of rapid, high-resolution separations of water-soluble components in small sample volumes. Other chapters consider the application of polynomial and B-spline interpolation to the description of cyclic voltammetric features. This book discusses as well the methods used to investigate the properties of ceramic high-transition-temperature superconductors. The final chapter deals with the importance of monitoring and protecting the environment based on measurement campaigns. This book is a valuable resource for analytical chemists, environmental chemists, and biochemists. Pharmacologists, scientists, students, researcher workers, and other practitioners will also find this book useful. |
| business intelligence and analytics pdf: Theory and Practice of Business Intelligence in Healthcare Khuntia, Jiban, Ning, Xue, Tanniru, Mohan, 2019-12-27 Business intelligence supports managers in enterprises to make informed business decisions in various levels and domains such as in healthcare. These technologies can handle large structured and unstructured data (big data) in the healthcare industry. Because of the complex nature of healthcare data and the significant impact of healthcare data analysis, it is important to understand both the theories and practices of business intelligence in healthcare. Theory and Practice of Business Intelligence in Healthcare is a collection of innovative research that introduces data mining, modeling, and analytic techniques to health and healthcare data; articulates the value of big volumes of data to health and healthcare; evaluates business intelligence tools; and explores business intelligence use and applications in healthcare. While highlighting topics including digital health, operations intelligence, and patient empowerment, this book is ideally designed for healthcare professionals, IT consultants, hospital directors, data management staff, data analysts, hospital administrators, executives, managers, academicians, students, and researchers seeking current research on the digitization of health records and health systems integration. |
| business intelligence and analytics pdf: Business Intelligence and Analytics Drew Bentley, 2017-05-11 Data is raw facts and figures and information is meaningful data that would be helpful for a person or company. Business intelligence extracts information from raw data through tools like data mining, perspective analysis, online analytical processing etc. The textbook will provide comprehensive information to readers about business intelligence and analytics. This book explores all the important aspects of business intelligence and analytics in the present day scenario. The topics covered in this extensive book deal with the core subjects of business intelligence. It aims to serve as a resource guide for students and facilitate the study of the discipline. |
| business intelligence and analytics pdf: 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 and analytics pdf: 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 and analytics pdf: 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. |
| business intelligence and analytics pdf: Analytics, Data Science, and Artificial Intelligence Ramesh Sharda, Dursun Delen, Efraim Turban, 2020-03-06 For courses in decision support systems, computerized decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisionsAnalytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus -- analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT. |
| business intelligence and analytics pdf: 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. |
| business intelligence and analytics pdf: 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 and analytics pdf: Business Intelligence Ramesh Sharda, Dursun Delen, Efraim Turban, 2014 Includes bibliographical references and index |
| business intelligence and analytics pdf: Business Intelligence Ramesh Sharda, Dursun Delen, Efraim Turban, 2017-01-13 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. |
| business intelligence and analytics pdf: Principles and Applications of Business Intelligence Research Herschel, Richard T., 2012-12-31 This book provides the latest ideas and research on advancing the understanding and implementation of business intelligence within organizations--Provided by publisher. |
| business intelligence and analytics pdf: 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 and analytics pdf: Beyond the Balanced Scorecard Mark Graham Brown, 2007-01-12 Improve the Health of Your Organization by Using the Right Metrics! The vast majority of companies use some form of balanced scorecard to measure performance measu, yet recent research suggests that most scorecards are based on singular, unsophisticated measurements, providing flawed data on the state of the organization. Beyond the Balanced Scorecard: Improving Business Intelligence with Analytics, by Mark Graham Brown, provides managers with the right metrics for evaluating important aspects of performance that are not accurately tracked by most companies and government organizations. Leaders will learn how to objectively measure: Relationships with Customers Employee Satisfaction External Business Environment Supplier/Vendor performance Strategy and Financials This book will show you how to construct a performance index, as well as provide you with example metrics of various aspects of performance that are difficult to measure. |
| business intelligence and analytics pdf: 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 and analytics pdf: 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. |
| business intelligence and analytics pdf: 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 |
| business intelligence and analytics pdf: 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 and analytics pdf: Handbook on Decision Support Systems 2 Frada Burstein, Clyde W. Holsapple, 2008-01-22 As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, it contains more than 70 chapters that approach decision support systems from a wide variety of perspectives. These range from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into ten major sections that novices and experts alike will refer to for years to come. |
| business intelligence and analytics pdf: Internet of Things in Business Transformation Parul Gandhi, Surbhi Bhatia, Abhishek Kumar, Mohammad Ali Alojail, Pramod Singh Rathore, 2021-02-03 The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named Industry 5.0 or Industrial Internet of Things. The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive. |
| business intelligence and analytics pdf: 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 and analytics pdf: Decision Support Systems for Business Intelligence Vicki L. Sauter, 2014-08-21 Praise for the First Edition This is the most usable decision support systems text. [i]t is far better than any other text in the field —Computing Reviews Computer-based systems known as decision support systems (DSS) play a vital role in helping professionals across various fields of practice understand what information is needed, when it is needed, and in what form in order to make smart and valuable business decisions. Providing a unique combination of theory, applications, and technology, Decision Support Systems for Business Intelligence, Second Edition supplies readers with the hands-on approach that is needed to understand the implications of theory to DSS design as well as the skills needed to construct a DSS. This new edition reflects numerous advances in the field as well as the latest related technological developments. By addressing all topics on three levels—general theory, implications for DSS design, and code development—the author presents an integrated analysis of what every DSS designer needs to know. This Second Edition features: Expanded coverage of data mining with new examples Newly added discussion of business intelligence and transnational corporations Discussion of the increased capabilities of databases and the significant growth of user interfaces and models Emphasis on analytics to encourage DSS builders to utilize sufficient modeling support in their systems A thoroughly updated section on data warehousing including architecture, data adjustment, and data scrubbing Explanations and implications of DSS differences across cultures and the challenges associated with transnational systems Each chapter discusses various aspects of DSS that exist in real-world applications, and one main example of a DSS to facilitate car purchases is used throughout the entire book. Screenshots from JavaScript® and Adobe® ColdFusion are presented to demonstrate the use of popular software packages that carry out the discussed techniques, and a related Web site houses all of the book's figures along with demo versions of decision support packages, additional examples, and links to developments in the field. Decision Support Systems for Business Intelligence, Second Edition is an excellent book for courses on information systems, decision support systems, and data mining at the advanced undergraduate and graduate levels. It also serves as a practical reference for professionals working in the fields of business, statistics, engineering, and computer technology. |
| business intelligence and analytics pdf: Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks Raisinghani, Mahesh S., 2003-07-01 Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks describes business intelligence (BI), how it is being conducted and managed and its major opportunities, limitations, issues and risks. This book takes an in-depth look at the scope of global technological change and BI. During this transition to BI, information does not merely add efficiency to the transaction; it adds value. This book brings together high quality expository discussions from experts in this field to identify, define, and explore BI methodologies, systems, and approaches in order to understand the opportunities, limitations and risks. |
| business intelligence and analytics pdf: Integrated Business Information Systems Klaus-Dieter Gronwald, 2017-05-30 Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Customer Relationship Management (CRM), Business Intelligence (BI) and Big Data Analytics (BDA) are business related tasks and processes, which are supported by standardized software solutions. The book explains that this requires business oriented thinking and acting from IT specialists and data scientists. It is a good idea to let students experience this directly from the business perspective, for example as executives of a virtual company. The course simulates the stepwise integration of the linked business process chain ERP-SCM-CRM-BI-Big Data of four competing groups of companies. The course participants become board members with full P&L responsibility for business units of one of four beer brewery groups managing supply chains from production to retailer. |
| business intelligence and analytics pdf: 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 and analytics pdf: 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. |
| business intelligence and analytics pdf: 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 |
| business intelligence and analytics pdf: Enterprise Resource Planning and Business Intelligence Systems for Information Quality Carlo Caserio, Sara Trucco, 2018-04-13 This book analyses the role of Enterprise Resource Planning (ERP) and Business Intelligence (BI) systems in improving information quality through an empirical analysis carried out in Italy. The study begins with a detailed examination of ERP features that highlights the advantages and disadvantages of ERP adoption. Critical success factors for ERP implementation and post-implementation are then discussed, along with the capabilities of ERP in driving the alignment between management accounting and financial accounting information.The study goes on to illustrate the features of BI systems and to summarize companies’ needs for BI. Critical success factors for BI implementation are then presented, along with the BI maturity model and lifecycle. The focus of the research entails a detailed empirical analysis in the Italian setting designed to investigate the role played by ERP and BI systems in reducing information overload/underload and improving information quality by influencing the features of information flow. The practical and theoretical implications of the study are discussed and future avenues of research are suggested. This book will be of value for all those who have an interest in the capacities of ERP and BI systems to enhance business information quality. |
| business intelligence and analytics pdf: 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. |
| business intelligence and analytics pdf: 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. |
| business intelligence and analytics pdf: 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. |
| business intelligence and analytics pdf: 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. |
| business intelligence and analytics pdf: An Introduction to Business Analytics Ger Koole, 2019 Business Analytics (BA) is about turning data into decisions. This book covers the full range of BA topics, including statistics, machine learning and optimization, in a way that makes them accessible to a broader audience. Decision makers will gain enough insight into the subject to have meaningful discussions with machine learning specialists, and those starting out as data scientists will benefit from an overview of the field and take their first steps as business analytics specialist. Through this book and the various exercises included, you will be equipped with an understanding of BA, while learning R, a popular tool for statistics and machine learning. |
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys …
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, …
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the …
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned …
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….
