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Author: C. Keith Harrison
Genre: Computers
Publisher: CRC Press
ISBN: 9781315350622
Book Pages: 236
Format: PDF, ePub & Mobi

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.


Author: Dinabandhu Bag
Genre: Business & Economics
Publisher: Routledge
ISBN: 9781315464671
Book Pages: 230
Format: PDF, ePub & Mobi

This book provides a first-hand account of business analytics and its implementation, and an account of the brief theoretical framework underpinning each component of business analytics. The themes of the book include (1) learning the contours and boundaries of business analytics which are in scope; (2) understanding the organization design aspects of an analytical organization; (3) providing knowledge on the domain focus of developing business activities for financial impact in functional analysis; and (4) deriving a whole gamut of business use cases in a variety of situations to apply the techniques. The book gives a complete, insightful understanding of developing and implementing analytical solution.


Author: Subrata Das
Genre: Business & Economics
Publisher: CRC Press
ISBN: 9781439890707
Book Pages: 516
Format: PDF, ePub & Mobi

Learn How to Properly Use the Latest Analytics Approaches in Your Organization Computational Business Analytics presents tools and techniques for descriptive, predictive, and prescriptive analytics applicable across multiple domains. Through many examples and challenging case studies from a variety of fields, practitioners easily see the connections to their own problems and can then formulate their own solution strategies. The book first covers core descriptive and inferential statistics for analytics. The author then enhances numerical statistical techniques with symbolic artificial intelligence (AI) and machine learning (ML) techniques for richer predictive and prescriptive analytics. With a special emphasis on methods that handle time and textual data, the text: Enriches principal component and factor analyses with subspace methods, such as latent semantic analyses Combines regression analyses with probabilistic graphical modeling, such as Bayesian networks Extends autoregression and survival analysis techniques with the Kalman filter, hidden Markov models, and dynamic Bayesian networks Embeds decision trees within influence diagrams Augments nearest-neighbor and k-means clustering techniques with support vector machines and neural networks These approaches are not replacements of traditional statistics-based analytics; rather, in most cases, a generalized technique can be reduced to the underlying traditional base technique under very restrictive conditions. The book shows how these enriched techniques offer efficient solutions in areas, including customer segmentation, churn prediction, credit risk assessment, fraud detection, and advertising campaigns.


Author: A CONTEMPORARY APPROACH
Genre:
Publisher: Macmillan International Higher Education
ISBN: 9781137610614
Book Pages:
Format: PDF, ePub & Mobi

This innovative new textbook, co-authored by an established academic and a leading practitioner, is the first to bring together issues of cloud computing, business intelligence and big data analytics in order to explore how organisations use cloud technology to analyse data and make decisions. In addition to offering an up-to-date exploration of key issues relating to data privacy and ethics, information governance, and the future of analytics, the text describes the options available in deploying analytic solutions to the cloud and draws on real-world, international examples from companies such as Rolls Royce, Lego, Volkswagen and Samsung. Combining academic and practitioner perspectives that are crucial to the understanding of this growing field, Business Analytics acts an ideal core text for undergraduate, postgraduate and MBA modules on Big Data, Business and Data Analytics, and Business Intelligence, as well as functioning as a supplementary text for modules in Marketing Analytics. The book is also an invaluable resource for practitioners and will quickly enable the next generation of 'Information Builders' within organisations to understand innovative cloud based-analytic solutions.


Author: Jay Liebowitz
Genre: Business & Economics
Publisher: CRC Press
ISBN: 9781482218510
Book Pages: 304
Format: PDF, ePub & Mobi

"The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions to ‘do this, avoid that.’" —From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee Company With the growing barrage of "big data," it becomes vitally important for organizations to make sense of this data and information in a timely and effective way. That’s where analytics come into play. Research shows that organizations that use business analytics to guide their decision making are more productive and experience higher returns on equity. Big Data and Business Analytics helps you quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive. Packed with case studies, this book assembles insights from some of the leading experts and organizations worldwide. Spanning industry, government, not-for-profit organizations, and academia, they share valuable perspectives on big data domains such as cybersecurity, marketing, emergency management, healthcare, finance, and transportation. Understand the trends, potential, and challenges associated with big data and business analytics Get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues Learn from VPs of Big Data/Insights & Analytics via case studies of Fortune 100 companies, government agencies, universities, and not-for-profits Big data problems are complex. This book shows you how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage. Author Jay Liebowitz recently had an article published in The World Financial Review. www.worldfinancialreview.com/?p=1904


Author: Ayanendranath Basu
Genre: Business & Economics
Publisher: CRC Press
ISBN: 9781315356495
Book Pages: 384
Format: PDF, ePub & Mobi

A User's Guide to Business Analytics provides a comprehensive discussion of statistical methods useful to the business analyst. Methods are developed from a fairly basic level to accommodate readers who have limited training in the theory of statistics. A substantial number of case studies and numerical illustrations using the R-software package are provided for the benefit of motivated beginners who want to get a head start in analytics as well as for experts on the job who will benefit by using this text as a reference book. The book is comprised of 12 chapters. The first chapter focuses on business analytics, along with its emergence and application, and sets up a context for the whole book. The next three chapters introduce R and provide a comprehensive discussion on descriptive analytics, including numerical data summarization and visual analytics. Chapters five through seven discuss set theory, definitions and counting rules, probability, random variables, and probability distributions, with a number of business scenario examples. These chapters lay down the foundation for predictive analytics and model building. Chapter eight deals with statistical inference and discusses the most common testing procedures. Chapters nine through twelve deal entirely with predictive analytics. The chapter on regression is quite extensive, dealing with model development and model complexity from a user’s perspective. A short chapter on tree-based methods puts forth the main application areas succinctly. The chapter on data mining is a good introduction to the most common machine learning algorithms. The last chapter highlights the role of different time series models in analytics. In all the chapters, the authors showcase a number of examples and case studies and provide guidelines to users in the analytics field.


Author: Lawrence Maisel
Genre: Business & Economics
Publisher: John Wiley & Sons
ISBN: 9781118175569
Book Pages: 272
Format: PDF, ePub & Mobi

Discover the breakthrough tool your company can use to make winning decisions This forward-thinking book addresses the emergence of predictive business analytics, how it can help redefine the way your organization operates, and many of the misconceptions that impede the adoption of this new management capability. Filled with case examples, Predictive Business Analytics defines ways in which specific industries have applied these techniques and tools and how predictive business analytics can complement other financial applications such as budgeting, forecasting, and performance reporting. Examines how predictive business analytics can help your organization understand its various drivers of performance, their relationship to future outcomes, and improve managerial decision-making Looks at how to develop new insights and understand business performance based on extensive use of data, statistical and quantitative analysis, and explanatory and predictive modeling Written for senior financial professionals, as well as general and divisional senior management Visionary and effective, Predictive Business Analytics reveals how you can use your business's skills, technologies, tools, and processes for continuous analysis of past business performance to gain forward-looking insight and drive business decisions and actions.


Author: Jeffrey D. Camm
Genre: Business & Economics
Publisher: Cengage AU
ISBN: 9780357131787
Book Pages: 816
Format: PDF, ePub & Mobi

Present the full range of analytics -- from descriptive and predictive to prescriptive analytics -- with Camm/Cochran/Fry/Ohlmann's market-leading BUSINESS ANALYTICS, 4E. Clear, step-by-step instructions teach students how to use Excel, Tableau, R and JMP Pro to solve more advanced analytics concepts. As instructor, you have the flexibility to choose your preferred software for teaching concepts. Extensive solutions to problems and cases save grading time, while providing students with critical practice. This edition covers topics beyond the traditional quantitative concepts, such as data visualization and data mining, which are increasingly important in today's analytical problem solving. In addition, MindTap and WebAssign customizable digital course solutions offer an interactive eBook, auto-graded exercises from the printed book, algorithmic practice problems with solutions and Exploring Analytics visualizations to strengthen students' understanding of course concepts.


Author: David Roi Hardoon
Genre: Business & Economics
Publisher: CRC Press
ISBN: 9781439896532
Book Pages: 190
Format: PDF, ePub & Mobi

Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data. The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data. Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization.


Author: Hiriyappa B
Genre:
Publisher: Independently Published
ISBN: 1652287663
Book Pages: 52
Format: PDF, ePub & Mobi

Business analytics is a set of techniques and processes that can be used to analyze data to improve business performance through fact- based decision-making. Business analytics create capabilities for companies to compete in the market effectively. However, nowadays companies use analytics as competitive strategy of the business.1 Introduction to AnalyticsAnalytics2 Business Analytics.Evolution of business analyticsScope of business analyticsImportance of business analyticsData use for analytics3 Challenges of Business AnalyticsBenefits and advantages of implementingbusiness analyticsChallenges in implementing businessanalytics in an organization4 How Business Analytics Helps CompaniesHow business analytics helps a company5Business Analytics ProcessBusiness analytics processStep 1: Defining the business needs and requirementStep 2: Explore the structured and unstructured dataStep 3: Analyze the dataStep 4: Predict what is likely to happenStep 5: Optimize to find the best solutionStep 6: Make a strategic decision and measurethe outcomeStep 7: Update the system with the results of thestrategic decision6 Types of Business AnalyticsDescriptive analyticsPredictive analyticsDiagnostic analyticsPrescriptive analyticsDecision analytics7 Business Analytics Tools for BusinessOpen-source analytics toolsRPythonApache SparkApache StormPIG and HIVECommercial analytics toolsSASTableauExcelQlikViewSplunkOther business analytical tools8 Business Analytics ApplicationsBusiness analytics applicationsFinancial analyticsHuman resource analyticsMarketing analyticsHealth care analyticsSupply-chain analyticsWeb analyticsCRM analytics9 Career in Business AnalyticsNeed for business analyticsCareers in business analyticsBusiness analytics helps companies to find the most profitable customer and allows them to justify their marketing effort, especially when the competition is very high. By using the business analytical software, the corporate world has the ability to make better decisions, and it improves with analytical skills.Decision-making process is largely dependent on business analytics in organizations and businesses. When business analytics is carried out the right way, it can help companies put the right foot forward.Business analytics is based on the data and statistical methods. It focuses on using a set of metrics to investigate the past, present, and future of an organization or a business. This book helps you to know the analytics, analytics in business, challenges, process, types, tools, and applications of analytics.