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| business analytics and information management: Savvy Manager Jane Flagello, Sandra Dugas, 2009 The Savvy Manager challenges readers to develop the five core strengths all great managers possess. Savvy managers; self-manage (recognize their own core values; reflect (quietly contemplate and think without judgment; act consciously (wisely choose their actions); collaborate (extend respect to all employees); and evolve (constantly grow and learn). Put learning into action with a companion website and dozens of included worksheets and exercises. |
| business analytics and information management: Encyclopedia of Business Analytics and Optimization Wang, John, 2014-02-28 As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal. |
| business analytics and information management: Information Management William McKnight, 2013-11-30 Information Management: Gaining a Competitive Advantage with Data is about making smart decisions to make the most of company information. Expert author William McKnight develops the value proposition for information in the enterprise and succinctly outlines the numerous forms of data storage. Information Management will enlighten you, challenge your preconceived notions, and help activate information in the enterprise. Get the big picture on managing data so that your team can make smart decisions by understanding how everything from workload allocation to data stores fits together. The practical, hands-on guidance in this book includes: - Part 1: The importance of information management and analytics to business, and how data warehouses are used - Part 2: The technologies and data that advance an organization, and extend data warehouses and related functionality - Part 3: Big Data and NoSQL, and how technologies like Hadoop enable management of new forms of data - Part 4: Pulls it all together, while addressing topics of agile development, modern business intelligence, and organizational change management Read the book cover-to-cover, or keep it within reach for a quick and useful resource. Either way, this book will enable you to master all of the possibilities for data or the broadest view across the enterprise. - Balances business and technology, with non-product-specific technical detail - Shows how to leverage data to deliver ROI for a business - Engaging and approachable, with practical advice on the pros and cons of each domain, so that you learn how information fits together into a complete architecture - Provides a path for the data warehouse professional into the new normal of heterogeneity, including NoSQL solutions |
| business analytics and information management: International Journal of Business Analytics (IJBAN). John Wang, 2015 |
| business analytics and information management: 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 analytics and information management: Encyclopedia of Organizational Knowledge, Administration, and Technology Khosrow-Pour D.B.A., Mehdi, 2020-09-29 For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication. |
| business analytics and information management: Business Analytics with Management Science Models and Methods Arben Asllani, 2015 This book is about prescriptive analytics. It provides business practitioners and students with a selected set of management science and optimization techniques and discusses the fundamental concepts, methods, and models needed to understand and implement these techniques in the era of Big Data. A large number of management science models exist in the body of literature today. These models include optimization techniques or heuristics, static or dynamic programming, and deterministic or stochastic modeling. The topics selected in this book, mathematical programming and simulation modeling, are believed to be among the most popular management science tools, as they can be used to solve a majority of business optimization problems. Over the years, these techniques have become the weapon of choice for decision makers and practitioners when dealing with complex business systems. |
| business analytics and information management: 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 analytics and information management: 5 Keys to Business Analytics Program Success John Boyer, Bill Frank, Brian Green, Tracy Harris, Kay Van De Vanter, 2012-11-15 A roadmap to understanding and achieving excellence in business analytics initiatives With business analytics is becoming increasingly strategic to all types of organizations and with many companies struggling to create a meaningful impact with this emerging technology, this book based on the combined experience of 10 organizations that display excellence and expertise on the subject shares the best practices, discusses the management aspects and sociology that drives success, and uncovers the five key aspects behind the success of some of the top business analytics programs in the industry. Readers will learn about numerous topics, including how to create and manage a changing business analytics strategy; align business priorities to technological innovation; quantify and demonstrate tangible business value; implement program processes that balance agility, empowerment, and control; and architecting a business analytics technology solution with future innovation in mind.This is the ideal resource for any organization that wants to learn how a business analytics program can help manage value, employees, and technology to translate strategies into actionable insight and achievement. |
| business analytics and information management: Machine Learning Techniques for Improved Business Analytics G., Dileep Kumar, 2018-07-06 Analytical tools and algorithms are essential in business data and information systems. Efficient economic and financial forecasting in machine learning techniques increases gains while reducing risks. Providing research on predictive models with high accuracy, stability, and ease of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning Techniques for Improved Business Analytics is a collection of innovative research on the methods and applications of artificial intelligence in strategic business decisions and management. Featuring coverage on a broad range of topics such as data mining, portfolio optimization, and social network analysis, this book is ideally designed for business managers and practitioners, upper-level business students, and researchers seeking current research on large-scale information control and evaluation technologies that exceed the functionality of conventional data processing techniques. |
| business analytics and information management: Applications of Big Data and Business Analytics in Management Sneha Kumari, K. K. Tripathy, Vidya Kumbhar, 2020-12-04 Applications of Big Data and Business Analytics in Management uses advanced analytic tools to explore the solutions to problems in society, environment and industry. The chapters within bring together researchers, engineers and practitioners, encompassing a wide and diverse set of topics in almost every field. |
| business analytics and information management: Business Analytics for Sales and Marketing Managers Gert H. N. Laursen, 2011-03-16 Expert guidance on information management for optimum customer intelligence processes Providing essential guidance for information management, this book helps you understand the basics of information management, how to design and launch customer intelligence campaigns, and optimize existing customer intelligence processes. How to align information management with company strategy Examines how to get, grow, and retain valuable customers Discusses how to optimize existing customer intelligence processes Showing you how to make extensive use of data, statistical, and quantitative analysis, explanatory and predictive modeling, and fact-based management to drive decision making, Business Analytics for Customer Intelligence provides you with the tools your business needs to optimize you data driven processes. |
| business analytics and information management: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| business analytics and information management: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| business analytics and information management: Business Analytics Richard Vidgen, Sam Kirshner, Felix Tan, 2019-10-09 This exciting new textbook offers an accessible, business-focused overview of the key theoretical concepts underpinning modern data analytics. It provides engaging and practical advice on using the key software tools, including SAS Visual Analytics, R and DataRobot, that are used in organisations to help make effective data-driven decisions. Combining theory with hands-on practical examples, this essential text includes cutting edge coverage of new areas of interest including social media analytics, design thinking and the ethical implications of using big data. A wealth of learning features including exercises, cases, online resources and data sets help students to develop analytic problem-solving skills. With its management perspective on analytics and its coverage of a range of popular software tools, this is an ideal essential text for upper-level undergraduate, postgraduate and MBA students. It is also ideal for practitioners wanting to understand the broader organisational context of big data analysis and to engage critically with the tools and techniques of business analytics. |
| business analytics and information management: Business Analytics for Managers Wolfgang Jank, 2011-09-08 The practice of business is changing. More and more companies are amassing larger and larger amounts of data, and storing them in bigger and bigger data bases. Consequently, successful applications of data-driven decision making are plentiful and increasing on a daily basis. This book will motivate the need for data and data-driven solutions, using real data from real business scenarios. It will allow managers to better interact with personnel specializing in analytics by exposing managers and decision makers to the key ideas and concepts of data-driven decision making. Business Analytics for Managers conveys ideas and concepts from both statistics and data mining with the goal of extracting knowledge from real business data and actionable insight for managers. Throughout, emphasis placed on conveying data-driven thinking. While the ideas discussed in this book can be implemented using many different software solutions from many different vendors, it also provides a quick-start to one of the most powerful software solutions available. The main goals of this book are as follows: to excite managers and decision makers about the potential that resides in data and the value that data analytics can add to business processes and provide managers with a basic understanding of the main concepts of data analytics and a common language to convey data-driven decision problems so they can better communicate with personnel specializing in data mining or statistics. |
| business analytics and information management: Real-world Data Mining Dursun Delen, 2015 As business becomes increasingly complex and global, decision-makers must act more rapidly and accurately, based on the best available evidence. Modern data mining and analytics is indispensable for doing this. Real-World Data Mining demystifies current best practices, showing how to use data mining and analytics to uncover hidden patterns and correlations, and leverage these to improve all business decision-making. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, Delen provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: data mining processes, methods, and techniques; the role and management of data; tools and metrics; text and web mining; sentiment analysis; and integration with cutting-edge Big Data approaches. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials. |
| business analytics and information management: Applied Business Analytics Nathaniel Lin, 2015 Now that you've collected the data and crunched the numbers, what do you do with all this information? How do you take the fruit of your analytics labor and apply it to business decision making? How do you actually apply the information gleaned from quants and tech teams? Applied Business Analytics will help you find optimal answers to these questions, and bridge the gap between analytics and execution in your organization. Nathaniel Lin explains why analytics value chains often break due to organizational and cultural issues, and offers in the trenches guidance for overcoming these obstacles. You'll learn why a special breed of analytics deciders is indispensable for any organization that seeks to compete on analytics; how to become one of those deciders; and how to identify, foster, support, empower, and reward others who join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at every level: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ -- and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer |
| business analytics and information management: Analytics at Work Thomas H. Davenport, Jeanne G. Harris, Robert Morison, 2010 As a follow-up to the successful Competing on Analytics, authors Tom Davenport, Jeanne Harris, and Robert Morison provide practical frameworks and tools for all companies that want to use analytics as a basis for more effective and more profitable decision making. Regardless of your company's strategy, and whether or not analytics are your company's primary source of competitive differentiation, this book is designed to help you assess your organization's analytical capabilities, provide the tools to build these capabilities, and put analytics to work. The book helps you answer these pressing questions: What assets do I need in place in my organization in order to use analytics to run my business? Once I have these assets, how do I deploy them to get the most from an analytic approach? How do I get an analytic initiative off the ground in the first place, and then how do I sustain analytics in my organization over time? Packed with tools, frameworks, and all new examples, Analytics at Work makes analytics understandable and accessible and teaches you how to make your company more analytical. |
| business analytics and information management: 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 analytics and information management: Win with Advanced Business Analytics Jean-Paul Isson, Jesse Harriott, 2012-09-25 Plain English guidance for strategic business analytics and big data implementation In today's challenging economy, business analytics and big data have become more and more ubiquitous. While some businesses don't even know where to start, others are struggling to move from beyond basic reporting. In some instances management and executives do not see the value of analytics or have a clear understanding of business analytics vision mandate and benefits. Win with Advanced Analytics focuses on integrating multiple types of intelligence, such as web analytics, customer feedback, competitive intelligence, customer behavior, and industry intelligence into your business practice. Provides the essential concept and framework to implement business analytics Written clearly for a nontechnical audience Filled with case studies across a variety of industries Uniquely focuses on integrating multiple types of big data intelligence into your business Companies now operate on a global scale and are inundated with a large volume of data from multiple locations and sources: B2B data, B2C data, traffic data, transactional data, third party vendor data, macroeconomic data, etc. Packed with case studies from multiple countries across a variety of industries, Win with Advanced Analytics provides a comprehensive framework and applications of how to leverage business analytics/big data to outpace the competition. |
| business analytics and information management: Big Data and Business Analytics Jay Liebowitz, 2016-04-19 The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions todo this, avoid that.'-From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee CompanyWith the growing barrage of big data, it becomes vitally important for organizations to mak |
| business analytics and information management: Business Analytics Principles, Concepts, and Applications with SAS Marc J. Schniederjans, Dara G. Schniederjans, Christopher M. Starkey, 2014-10-07 Responding to a shortage of effective content for teaching business analytics, this text offers a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. Business Analytics Principles, Concepts, and Applications with SAS offers a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, Business Analytics Principles, Concepts, and Applications with SAS demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. |
| business analytics and information management: Delivering Business Analytics Evan Stubbs, 2013-01-30 AVOID THE MISTAKES THAT OTHERS MAKE – LEARN WHAT LEADS TO BEST PRACTICE AND KICKSTART SUCCESS This groundbreaking resource provides comprehensive coverage across all aspects of business analytics, presenting proven management guidelines to drive sustainable differentiation. Through a rich set of case studies, author Evan Stubbs reviews solutions and examples to over twenty common problems spanning managing analytics assets and information, leveraging technology, nurturing skills, and defining processes. Delivering Business Analytics also outlines the Data Scientist’s Code, fifteen principles that when followed ensure constant movement towards effective practice. Practical advice is offered for addressing various analytics issues; the advantages and disadvantages of each issue’s solution; and how these solutions can optimally create organizational value. With an emphasis on real-world examples and pragmatic advice throughout, Delivering Business Analytics provides a reference guide on: The economic principles behind how business analytics leads to competitive differentiation The elements which define best practice The Data Scientist’s Code, fifteen management principles that when followed help teams move towards best practice Practical solutions and frequent missteps to twenty-four common problems across people and process, systems and assets, and data and decision-making Drawing on the successes and failures of countless organizations, author Evan Stubbs provides a densely packed practical reference on how to increase the odds of success in designing business analytics systems and managing teams of data scientists. Uncover what constitutes best practice in business analytics and start achieving it with Delivering Business Analytics. |
| business analytics and information management: Information Systems Efrem G. Mallach, 2015-08-18 Most information systems textbooks overwhelm business students with overly technical information they may not need in their careers. Information Systems: What Every Business Student Needs to Know takes a new approach to the required information systems course for business majors.For each topic covered, the text highlights key Take-Aways that aler |
| business analytics and information management: Applied Big Data Analytics in Operations Management Kumar, Manish, 2016-09-30 Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management. |
| business analytics and information management: A Research Agenda for Knowledge Management and Analytics Jay Liebowitz, 2021-01-29 Leveraging the knowledge gained from Knowledge Management and from the growing fields of Analytics and Artificial Intelligence (AI), this Research Agenda highlights the research gaps, issues, applications, challenges and opportunities related to Knowledge Management (KM). Exploring synergies between KM and emerging technologies, leading international scholars and practitioners examine KM from a multidisciplinary perspective, demonstrating the ways in which knowledge sharing worldwide can be enhanced in order to better society and improve organisational performance. |
| business analytics and information management: Recent Developments in Data Science and Business Analytics Madjid Tavana, Srikanta Patnaik, 2018-03-27 This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains. |
| business analytics and information management: 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 analytics and information management: Operations and Service Management: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2017-11-30 Organizations of all types are consistently working on new initiatives, product lines, and workflows as a way to remain competitive in the modern business environment. No matter the type of project at hand, employing the best methods for effective execution and timely completion of the task is essential to business success. Operations and Service Management: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source for the latest research on business operations and production processes. It examines the need for a customer focus and highlights a range of pertinent topics such as financial performance measures, human resource development, and business analytics, this multi-volume book is ideally designed for managers, professionals, students, researchers, and academics interested in operations and service management. |
| business analytics and information management: Information Systems Management in the Big Data Era Peter Lake, Robert Drake, 2015-01-12 This timely text/reference explores the business and technical issues involved in the management of information systems in the era of big data and beyond. Topics and features: presents review questions and discussion topics in each chapter for classroom group work and individual research assignments; discusses the potential use of a variety of big data tools and techniques in a business environment, explaining how these can fit within an information systems strategy; reviews existing theories and practices in information systems, and explores their continued relevance in the era of big data; describes the key technologies involved in information systems in general and big data in particular, placing these technologies in an historic context; suggests areas for further research in this fast moving domain; equips readers with an understanding of the important aspects of a data scientist’s job; provides hands-on experience to further assist in the understanding of the technologies involved. |
| business analytics and information management: Handbook of Research on Organizational Transformations through Big Data Analytics Tavana, Madjid, 2014-11-30 Big data analytics utilizes a wide range of software and analytical tools to provide immediate, relevant information for efficient decision-making. Companies are recognizing the immense potential of BDA, but ensuring the data is appropriate and error-free is the largest hurdle in implementing BDA applications. The Handbook of Research on Organizational Transformations through Big Data Analytics not only catalogues the existing platforms and technologies, it explores new trends within the field of big data analytics (BDA). Containing new and existing research materials and insights on the various approaches to BDA; this publication is intended for researchers, IT professionals, and CIOs interested in the best ways to implement BDA applications and technologies. |
| business analytics and information management: Big Data: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2016-04-20 The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics. |
| business analytics and information management: Customer and Business Analytics Daniel S. Putler, Robert E. Krider, 2012-05-07 Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the tex |
| business analytics and information management: 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 analytics and information management: A Primer on Business Analytics Yudhvir Seetharam, 2022-01-01 This book will provide a comprehensive overview of business analytics, for those who have either a technical background (quantitative methods) or a practitioner business background. Business analytics, in the context of the 4th Industrial Revolution, is the “new normal” for businesses that operate in this digital age. This book provides a comprehensive primer and overview of the field (and related fields such as Business Intelligence and Data Science). It will discuss the field as it applies to financial institutions, with some minor departures to other industries. Readers will gain understanding and insight into the field of data science, including traditional as well as emerging techniques. Further, many chapters are dedicated to the establishment of a data-driven team – from executive buy-in and corporate governance to managing and quantifying the return of data-driven projects. |
| business analytics and information management: A Business Analyst's Introduction to Business Analytics Adam Fleischhacker, 2020-07-20 This up-to-date business analytics textbook (published in July 2020) will get you harnessing the power of the R programming language to: manipulate and model data, discover and communicate insight, to visually communicate that insight, and successfully advocate for change within an organization. Book Description A frequent teaching-award winning professor with an analytics-industry background shares his hands-on guide to learning business analytics. It is the first textbook addressing a complete and modern business analytics workflow that includes data manipulation, data visualization, modelling business problems with graphical models, translating graphical models into code, and presenting insights back to stakeholders. Book Highlights Content that is accessible to anyone, even most analytics beginners. If you have taken a stats course, you are good to go. Assumes no knowledge of the R programming language. Provides introduction to R, RStudio, and the Tidyverse. Provides a solid foundation and an implementable workflow for anyone wading into the Bayesian inference waters. Provides a complete workflow within the R-ecosystem; there is no need to learn several programming languages or work through clunky interfaces between software tools. First book introducing two powerful R-packages - `causact` for visual modelling of business problems and `greta` which is an R interface to `TensorFlow` used for Bayesian inference. Uses the intuitive coding practices of the `tidyverse` including using `dplyr` for data manipulation and `ggplot2` for data visualization. Datasets that are freely and easily accessible. Code for generating all results and almost every visualization used in the textbook. Do not learn statistical computation or fancy math in a vacuum, learn it through this guide within the context of solving business problems. |
| business analytics and information management: A Guide to the Business Analysis Body of Knowledger International Institute of Business Analysis, IIBA, 2009 The BABOK Guide contains a description of generally accepted practices in the field of business analysis. Recognised around the world as a key tool for the practice of business analysis and has become a widely-accepted standard for the profession. |
| business analytics and information management: Enterprise Information Management in Practice Saumya Chaki, 2015-12-19 Learn how to form and execute an enterprise information strategy: topics include data governance strategy, data architecture strategy, information security strategy, big data strategy, and cloud strategy. Manage information like a pro, to achieve much better financial results for the enterprise, more efficient processes, and multiple advantages over competitors. As you’ll discover in Enterprise Information Management in Practice, EIM deals with both structured data (e.g. sales data and customer data) as well as unstructured data (like customer satisfaction forms, emails, documents, social network sentiments, and so forth). With the deluge of information that enterprises face given their global operations and complex business models, as well as the advent of big data technology, it is not surprising that making sense of the large piles of data is of paramount importance. Enterprises must therefore put much greater emphasis on managing and monetizing both structured and unstructured data. As Saumya Chaki—an information management expert and consultant with IBM—explains in Enterprise Information Management in Practice, it is now more important than ever before to have an enterprise information strategy that covers the entire life cycle of information and its consumption while providing security controls. With Fortune 100 consultant Saumya Chaki as your guide, Enterprise Information Management in Practice covers each of these and the other pillars of EIM in depth, which provide readers with a comprehensive view of the building blocks for EIM. Enterprises today deal with complex business environments where information demands take place in real time, are complex, and often serve as the differentiator among competitors. The effective management of information is thus crucial in managing enterprises. EIM has evolved as a specialized discipline in the business intelligence and enterprise data warehousing space to address the complex needs of information processing and delivery—and to ensure the enterprise is making the most of its information assets. |
| business analytics and information management: Introduction to Information Systems R. Kelly Rainer, Efraim Turban, 2008-01-09 WHATS IN IT FOR ME? Information technology lives all around us-in how we communicate, how we do business, how we shop, and how we learn. Smart phones, iPods, PDAs, and wireless devices dominate our lives, and yet it's all too easy for students to take information technology for granted. Rainer and Turban's Introduction to Information Systems, 2nd edition helps make Information Technology come alive in the classroom. This text takes students where IT lives-in today's businesses and in our daily lives while helping students understand how valuable information technology is to their future careers. The new edition provides concise and accessible coverage of core IT topics while connecting these topics to Accounting, Finance, Marketing, Management, Human resources, and Operations, so students can discover how critical IT is to each functional area and every business. Also available with this edition is WileyPLUS - a powerful online tool that provides instructors and students with an integrated suite of teaching and learning resources in one easy-to-use website. The WileyPLUS course for Introduction to Information Systems, 2nd edition includes animated tutorials in Microsoft Office 2007, with iPod content and podcasts of chapter summaries provided by author Kelly Rainer. |
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
