| business intelligence applications examples: Developing Business Intelligence Apps for SharePoint David Feldman, Jason Himmelstein, 2013-07-02 Create dynamic business intelligence (BI) solutions for SharePoint faster and with more capabilities than previously possible. With this book, you’ll learn the entire process—from high-level concepts to development and deployment—for building data-rich BI applications with Visual Studio LightSwitch, SQL Server 2012, and a host of related Microsoft technologies. You’ll learn practical techniques and patterns necessary to use all of these technologies together as you build an example application through the course of the book, step by step. Discover how to solve real problems, using BI solutions that will evolve to meet future needs. Learn the fundamentals of SharePoint, LightSwitch, and SQL Server 2012 Get a solid grounding in BI application basics and database design principles Use LightSwitch to build a help desk app, including data model design and SharePoint data integration Build a tabular cube with Microsoft’s Business Intelligence Semantic Model (BISM) Dive into the data visualization stack, including Excel and SQL Server Reporting Services Create reports with Excel Services, Report Builder, and PowerView Use tips and tricks for setting up your BI application development environment |
| business intelligence applications examples: Data Mining for Business Analytics Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel, 2019-10-14 Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R |
| business intelligence applications examples: Research Anthology on Artificial Intelligence Applications in Security Management Association, Information Resources, 2020-11-27 As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research. |
| business intelligence applications examples: 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 applications examples: 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 applications examples: 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 applications examples: 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 applications examples: Next-Generation Business Intelligence Software with Silverlight 3 Bart Czernicki, 2011-02-02 Business intelligence (BI) software is the code and tools that allow you to view different components of a business using a single visual platform, making comprehending mountains of data easier. Applications that include reports, analytics, statistics, and historical and predictive modeling are all examples of BI applications. Currently, we are in the second generation of BI software, called BI 2.0. This generation is focused on writing BI software that is predictive, adaptive, simple, and interactive. As computers and software have evolved, more data can be presented to end users with increasingly visually rich techniques. Rich Internet application (RIA) technologies such as Microsoft Silverlight can be used to transform traditional user interfaces filled with boring data into fully interactive analytical applications to deliver insight from large data sets quickly. Furthermore, RIAs include 3D spatial design capabilities that allow for interesting layouts of aggregated data beyond a simple list or grid. BI 2.0 implemented via RIA technology can truly bring out the power of BI and deliver it to an average user via the Web. Next-Generation Business Intelligence Software with Rich Internet Applications provides developers, designers, and architects a solid foundation of BI design and architecture concepts with Microsoft Silverlight. This book covers key BI design concepts and how they can be applied without requiring an existing BI infrastructure. The author, Bart Czernicki, will show you how to build small BI applications by example that are interactive, highly visual, statistical, predictive, and most importantly, intuitive to the user. BI isn't just for the executive branch of a Fortune 500 company; it is for the masses. Let Next-Generation Business Intelligence Software with Rich Internet Applications show you how to unlock the rich intelligence you already have. |
| business intelligence applications examples: Handbook of Research on Applied AI for International Business and Marketing Applications Christiansen, Bryan, Škrinjari?, Tihana, 2020-09-25 Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students. |
| business intelligence applications examples: Building Business Intelligence Applications with .Net Robert Ericsson, 2009 |
| business intelligence applications examples: 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 applications examples: 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 applications examples: Data Science and Its Applications Aakanksha Sharaff, G R Sinha, 2021-08-18 The term data being mostly used, experimented, analyzed, and researched, Data Science and its Applications finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications. |
| business intelligence applications examples: 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 applications examples: E-Business Intelligence Bernard Liautaud, 2001 Publisher Fact Sheet How to leverage corporate information for reduced costs & increased profits. |
| business intelligence applications examples: Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications Rahman El Sheikh, Asim Abdel, 2011-09-30 Business intelligence applications are of vital importance as they help organizations manage, develop, and communicate intangible assets such as information and knowledge. Organizations that have undertaken business intelligence initiatives have benefited from increases in revenue, as well as significant cost savings.Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications highlights the marriage between business intelligence and knowledge management through the use of agile methodologies. Through its fifteen chapters, this book offers perspectives on the integration between process modeling, agile methodologies, business intelligence, knowledge management, and strategic management. |
| business intelligence applications examples: Artificial Intelligence in Practice Bernard Marr, 2019-04-15 Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce. |
| business intelligence applications examples: 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 applications examples: Oracle Business Intelligence Applications Simon Miller, William Hutchinson, 2013-06-28 Implement Oracle Business Intelligence Applications Provide actionable business intelligence across the enterprise to enable informed decision-making and streamlined business processes. Oracle Business Intelligence Applications: Deliver Value Through Rapid Implementations shows how to justify, configure, customize, and extend this complete package of BI solutions. You'll get a technical walkthrough of Oracle Business Intelligence Applications architecture--from the dashboard to the data source--followed by best practices for maximizing the powerful features of each application. You will also find out about stakeholders critical to project approval and success. Optimize performance using Oracle Exalytics In-Memory Machine Deliver timely financial information to managers with Oracle Financial Analytics Enable a streamlined, demand-driven supply chain via Oracle Supply Chain and Order Management Analytics Provide end-to-end visibility into manufacturing operations with Oracle Manufacturing Analytics Optimize supply-side performance through Oracle Procurement and Spend Analytics Use Oracle Human Resources Analytics to provide key workforce information to managers and HR professionals Track the costs and labor required to maintain and operate assets with Oracle Enterprise Asset Management Analytics Maintain visibility into project performance via Oracle Project Analytics Provide actionable insight into sales opportunities using Oracle Sales Analytics Enable superior customer service with Oracle Service Analytics |
| business intelligence applications examples: Business Intelligence, Reprint Edition Stacia Misner, Michael Luckevich, Elizabeth Vitt, 2008-12-10 “This readable, practical book helps business people quickly understand what business intelligence is, how it works, where it's used, and why and when to use it—all illustrated by real case studies, not just theory.” Nigel Pendse Author of The OLAP Report www.olapreport.com So much information, so little time. All too often, business data is hard to get at and use—thus slowing decision-making to a crawl. This insightful book illustrates how organizations can make better, faster decisions about their customers, partners, and operations by turning mountains of data into valuable business information that’s always at the fingertips of decision makers. You’ll learn what’s involved in using business intelligence to bring together information, people, and technology to create successful business strategies—and how to execute those strategies with confidence. Topics covered include: THE BUSINESS INTELLIGENCE MINDSET: Discover the basics behind business intelligence, such as how it’s defined, why and how to use it in your organization, and what characteristics, components, and general architecture most business intelligence solutions share. THE CASE FOR BUSINESS INTELLIGENCE: Read how world leaders in finance, manufacturing, and retail have successfully implemented business intelligence solutions and see what benefits they have reaped. THE PRACTICE OF BUSINESS INTELLIGENCE: Find out what’s involved in implementing a business intelligence solution in your organization, including how to identify your business intelligence opportunities, what decisions you must make to get a business intelligence project going, and what to do to sustain the momentum so that you can continue to make sense of all the data you gather. |
| business intelligence applications examples: Computational Intelligence Applications in Business Intelligence and Big Data Analytics Vijayan Sugumaran, Arun Kumar Sangaiah, Arunkumar Thangavelu, 2017-06-26 There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book. |
| business intelligence applications examples: Adaptive Business Intelligence Zbigniew Michalewicz, Martin Schmidt, Matthew Michalewicz, Constantin Chiriac, 2006-12-02 Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address fundamental questions: What is likely to happen in the future? What is the best course of action? Adaptive Business Intelligence explores elements of data mining, predictive modeling, forecasting, optimization, and adaptability. The book explains the application of numerous prediction and optimization techniques, and shows how these concepts can be used to develop adaptive systems. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy systems, genetic algorithms, simulated annealing, tabu search, ant systems, and agent-based modeling. |
| business intelligence applications examples: Successful Business Intelligence: Secrets to Making BI a Killer App Cindi Howson, 2007-12-17 Praise for Successful Business Intelligence If you want to be an analytical competitor, you've got to go well beyond business intelligence technology. Cindi Howson has wrapped up the needed advice on technology, organization, strategy, and even culture in a neat package. It's required reading for quantitatively oriented strategists and the technologists who support them. --Thomas H. Davenport, President's Distinguished Professor, Babson College and co-author, Competing on Analytics When used strategically, business intelligence can help companies transform their organization to be more agile, more competitive, and more profitable. Successful Business Intelligence offers valuable guidance for companies looking to embark upon their first BI project as well as those hoping to maximize their current deployments. --John Schwarz, CEO, Business Objects A thoughtful, clearly written, and carefully researched examination of all facets of business intelligence that your organization needs to know to run its business more intelligently and exploit information to its fullest extent. --Wayne Eckerson, Director, TDWI Research Using real-world examples, Cindi Howson shows you how to use business intelligence to improve the performance, and the quality, of your company. --Bill Baker, Distinguished Engineer & GM, Business Intelligence Applications, Microsoft Corporation This book outlines the key steps to make BI an integral part of your company's culture and demonstrates how your company can use BI as a competitive differentiator. --Robert VanHees, CFO, Corporate Express Given the trend to expand the business analytics user base, organizations are faced with a number of challenges that affect the success rate of these projects. This insightful book provides practical advice on improving that success rate. --Dan Vesset, Vice President, Business Analytics Solution Research, IDC |
| business intelligence applications examples: Organizational Applications of Business Intelligence Management: Emerging Trends Herschel, Richard T., 2012-03-31 This book offers a deep look into the latest research, tools, implementations, frameworks, architectures, and case studies within the field of Business Intelligence Management--Provided by publisher. |
| business intelligence applications examples: Implementing Information Technology Governance: Models, Practices and Cases Van Grembergen, Wim, De Haes, Steven, 2007-09-30 In many organizations, information technology (IT) has become crucial in the support, sustainability, and growth of the business. This pervasive use of technology has created a critical dependency on IT that calls for a specific focus on IT governance. Implementing Information Technology Governance: Models, Practices and Cases presents insight gained through literature reviews and case studies to provide practical guidance for organizations who want to start implementing IT governance or improving existing governance models, and provides a detailed set of IT governance structures, processes, and relational mechanisms that can be leveraged to implement IT governance in practice. |
| business intelligence applications examples: Data Virtualization for Business Intelligence Systems Rick van der Lans, 2012-07-25 Annotation In this book, Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. |
| business intelligence applications examples: 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 applications examples: Business Intelligence Techniques Murugan Anandarajan, Asokan Anandarajan, Cadambi A. Srinivasan, 2012-11-02 Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment. |
| business intelligence applications examples: Smart Intelligent Computing and Applications Suresh Chandra Satapathy, Vikrant Bhateja, Swagatam Das, 2018-11-04 The proceedings covers advanced and multi-disciplinary research on design of smart computing and informatics. The theme of the book broadly focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solution to varied problems in society, environment and industries. The volume publishes quality work pertaining to the scope of the conference which is extended towards deployment of emerging computational and knowledge transfer approaches, optimizing solutions in varied disciplines of science, technology and healthcare. |
| business intelligence applications examples: Seven Methods for Transforming Corporate Data Into Business Intelligence Vasant Dhar, Roger Stein, 1997 Information systems: past, present, and emerging; Intelligence density a metric for knowledge work; The vocabulary of intelligence density; Method one: data-driven decision support; Method two: evolving solutions: genetic algorithms; Method three: simulating the brain to solve problems: neural networks; Method four: putting expert resoning in a box: rule-based systems; Method five: dealing with linguistic ambiguity: fuzzy logic; Method six: soilving problems by analogy case-based resoning; Method seven: deriving rules from data: machine learning; Appendix saving time and money with object; Appendix case studies. |
| business intelligence applications examples: Decision Trees for Business Intelligence and Data Mining Barry De Ville, 2006 This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements other business intelligence applications. |
| business intelligence applications examples: Successful Business Intelligence, Second Edition Cindi Howson, 2013-11-05 Expanded to cover the latest in business intelligence-big data, cloud, mobile, visual data discovery, and in-memory, this fully updated bestseller by BI guru Cindi Howson provides the most modern techniques to exploit BI for the highest ROI. |
| business intelligence applications examples: Silverlight 4 Business Intelligence Software Bart Czernicki, 2011-01-27 Business intelligence (BI) software allows you to view different components of a business using a single visual platform, which makes comprehending mountains of data easier. BI is everywhere. Applications that include reports, analytics, statistics, and historical and predictive modeling are all examples of business intelligence. Currently, we are in the second generation of business intelligence software—called BI 2.0—which is focused on writing business intelligence software that is predictive, adaptive, simple, and interactive. As computers and software have evolved, more data can be presented to end users with increasingly visually rich techniques. Rich Internet application (RIA) technologies such as Microsoft Silverlight can be used to transform traditional user-interfaces filled with boring data into fully interactive analytical applications that quickly deliver insight from large data sets. Furthermore, RIAs now include 3D spatial-design capabilities that move beyond a simple list or grid and allow for interesting layouts of aggregated data. BI 2.0 implemented via an RIA technology can truly bring out the power of business intelligence and deliver it to an average user on the Web. Silverlight 4 Business Intelligence Software provides developers, designers, and architects with a solid foundation in business intelligence design and architecture concepts for Microsoft Silverlight. This book covers key business intelligence design concepts and how they can be applied without an existing BI infrastructure. Author Bart Czernicki provides you with examples of how to build small BI applications that are interactive, highly visual, statistical, predictive—and most importantly—intuitive to the end-user. Business intelligence isn’t just for the executive branch of a Fortune 500 company—it is for the masses. Let Silverlight 4 Business Intelligence Software show you how to unlock the rich intelligence you already have. |
| business intelligence applications examples: Introduction to Information Systems R. Kelly Rainer, Casey G. Cegielski, Ingrid Splettstoesser-Hogeterp, Cristobal Sanchez-Rodriguez, 2013-08-30 The goal of Introduction to Information Systems, 3rd Canadian Edition remains the same: to teach all business majors, especially undergraduate ones, how to use information technology to master their current or future jobs and to help ensure the success of their organization. To accomplish this goal, this text helps students to become informed users; that is, persons knowledgeable about information systems and information technology. The focus is not on merely learning the concepts of IT but rather on applying those concepts to facilitate business processes. The authors concentrate on placing information systems in the context of business, so that students will more readily grasp the concepts presented in the text. The theme of this book is What's In IT for Me? This question is asked by all students who take this course. The book will show you that IT is the backbone of any business, whether a student is majoring in Accounting, Finance, Marketing, Human Resources, or Production/Operations Management. Information for the Management Information Systems (MIS) major is also included. |
| business intelligence applications examples: Data Virtualization for Business Intelligence Systems Rick van der Lans, 2012-07-25 Data virtualization can help you accomplish your goals with more flexibility and agility. Learn what it is and how and why it should be used with Data Virtualization for Business Intelligence Systems. In this book, expert author Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. You'll learn the difference is between this new form of data integration and older forms, such as ETL and replication, and gain a clear understanding of how data virtualization really works. Data Virtualization for Business Intelligence Systems outlines the advantages and disadvantages of data virtualization and illustrates how data virtualization should be applied in data warehouse environments. You'll come away with a comprehensive understanding of how data virtualization will make data warehouse environments more flexible and how it make developing operational BI applications easier. Van der Lans also describes the relationship between data virtualization and related topics, such as master data management, governance, and information management, so you come away with a big-picture understanding as well as all the practical know-how you need to virtualize your data. - First independent book on data virtualization that explains in a product-independent way how data virtualization technology works. - Illustrates concepts using examples developed with commercially available products. - Shows you how to solve common data integration challenges such as data quality, system interference, and overall performance by following practical guidelines on using data virtualization. - Apply data virtualization right away with three chapters full of practical implementation guidance. - Understand the big picture of data virtualization and its relationship with data governance and information management. |
| business intelligence applications examples: Information Technology - New Generations Shahram Latifi, 2018-04-12 This volume presents a collection of peer-reviewed, scientific articles from the 15th International Conference on Information Technology – New Generations, held at Las Vegas. The collection addresses critical areas of Machine Learning, Networking and Wireless Communications, Cybersecurity, Data Mining, Software Engineering, High Performance Computing Architectures, Computer Vision, Health, Bioinformatics, and Education. |
| business intelligence applications examples: The Kimball Group Reader Ralph Kimball, Margy Ross, 2016-02-01 The final edition of the incomparable data warehousing and business intelligence reference, updated and expanded The Kimball Group Reader, Remastered Collection is the essential reference for data warehouse and business intelligence design, packed with best practices, design tips, and valuable insight from industry pioneer Ralph Kimball and the Kimball Group. This Remastered Collection represents decades of expert advice and mentoring in data warehousing and business intelligence, and is the final work to be published by the Kimball Group. Organized for quick navigation and easy reference, this book contains nearly 20 years of experience on more than 300 topics, all fully up-to-date and expanded with 65 new articles. The discussion covers the complete data warehouse/business intelligence lifecycle, including project planning, requirements gathering, system architecture, dimensional modeling, ETL, and business intelligence analytics, with each group of articles prefaced by original commentaries explaining their role in the overall Kimball Group methodology. Data warehousing/business intelligence industry's current multi-billion dollar value is due in no small part to the contributions of Ralph Kimball and the Kimball Group. Their publications are the standards on which the industry is built, and nearly all data warehouse hardware and software vendors have adopted their methods in one form or another. This book is a compendium of Kimball Group expertise, and an essential reference for anyone in the field. Learn data warehousing and business intelligence from the field's pioneers Get up to date on best practices and essential design tips Gain valuable knowledge on every stage of the project lifecycle Dig into the Kimball Group methodology with hands-on guidance Ralph Kimball and the Kimball Group have continued to refine their methods and techniques based on thousands of hours of consulting and training. This Remastered Collection of The Kimball Group Reader represents their final body of knowledge, and is nothing less than a vital reference for anyone involved in the field. |
| business intelligence applications examples: Building a Data Warehouse Vincent Rainardi, 2008-03-11 Here is the ideal field guide for data warehousing implementation. This book first teaches you how to build a data warehouse, including defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Coverage then explains how to populate the data warehouse and explores how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. It also details testing and how to administer data warehouse operation. |
| business intelligence applications examples: Information Communication Technologies: Concepts, Methodologies, Tools, and Applications Van Slyke, Craig, 2008-04-30 The rapid development of information communication technologies (ICTs) is having a profound impact across numerous aspects of social, economic, and cultural activity worldwide, and keeping pace with the associated effects, implications, opportunities, and pitfalls has been challenging to researchers in diverse realms ranging from education to competitive intelligence. |
| business intelligence applications examples: 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. |
Ultimate Guide to Business Intelligence in The Enterprise
Ultimate Guide to Business Intelligence in The Enterprise In this e-guide: Enterprise BI systems bring a variety of uses, business benefits and challenges to organizations, as explained in this …
Core Research Focus Area: Business Intelligence - Scope Sheet …
The Business Intelligence (BI) Focus Area provides organizations with the tools they need to deliver business insight and user perspective successfully by leveraging the organization's …
The Definitive Guide do Business Intelligence The Definitive …
Today, business intelligence is defined by Forrester as “a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information …
BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS TOOLS, …
Business intelligence (BI) is a technology-driven process for analyzing data and show actionable information to help corporate executives, business managers and other end users make more …
Business Intelligence Definition and Solutions - Ohio
Business intelligence, or BI, is an umbrella term that refers to a variety of software applications used to analyze an organization’s raw data. BI as a discipline is made up of several related …
Oracle® Business Intelligence Applications
Oracle Business Intelligence Applications is a comprehensive suite of prebuilt solutions that deliver pervasive intelligence across an organization, empowering users at all levels - from …
Business Intelligence Applications Examples [PDF]
Business Intelligence Applications Examples: Fundamentals of Business Intelligence Wilfried Grossmann,Stefanie Rinderle-Ma,2015-06-02 This book presents a comprehensive and …
Insights, Strategies, and Applications of Business Analytics
These examples illustrate how predictive analytics is applied in various industries to optimize operations, improve decision-making, enhance customer experiences, and drive business …
BUSINESS INTELLIGENCE - Xavier University
Business intelligence systems combine operational data with analytical tools to present complex and competitive information to planners and decision makers. The objective is to improve the …
Oracle® Business Intelligence Applications
Oracle Business Intelligence Applications are comprehensive prebuilt solutions that deliver pervasive intelligence across an organization, empowering users at all levels, from front line …
TYIT SEM VI BUSINESS INTELLIGENCE NOTES …
Business intelligence may be defined as a set of mathematical models and analysis methodologies that exploit the available data to generate information and knowledge useful for …
Business Analytics Principles, Concepts, and Applications: …
Business intelligence (BI) can be defined as a set of processes and technologies that convert data into meaningful and useful information for business purposes.
Introduction to Data Mining and Business Intelligence
Business intelligence is the transformation of raw data into knowledge and insight for making better business decisions. Data mining/analytics is closely related to the fields of database, …
BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS, …
Experts describe Business intelligence as a “business management term used to describe applications and technologies which are used to gather, provide access to analyze data and …
ENTERPRISE DATA MODELING FOR BUSINESS INTELLIGENCE …
Ideally, a data architect with a focus on business intelligence will start with data models to document what data the organization has, where it resides, how it’s used, and who owns it to …
Business Intelligence Applications Examples Copy
Business Intelligence Applications Examples: Fundamentals of Business Intelligence Wilfried Grossmann,Stefanie Rinderle-Ma,2015-06-02 This book presents a comprehensive and …
UNIT 4 INTRODUCTION TO BUSINESS INTELLIGENCE
4.5 BUSINESS INTELLIGENCE APPLICATIONS from various sources to assist organizations in making better business decisions. These applications typically include features such as …
SurfBI Costing Analytics - Oracle
Oracle Business Intelligence Applications are comprehensive prebuilt solutions that deliver pervasive intelligence across an organization, empowering users at all level, from front line …
Topics in Business Intelligence - SMAA.fi
What is Business Intelligence (BI)? BI refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or …
Business Intelligence A Managerial Approach Pearson Pdf
Business Intelligence, Managerial Approach, Pearson PDF, Data Analysis, Decision Making, Strategic Planning, Data Visualization I. Start with a captivating statement about the …
Ultimate Guide to Business Intelligence in The Enterprise
Ultimate Guide to Business Intelligence in The Enterprise In this e-guide: Enterprise BI systems bring a variety of uses, business benefits and challenges to organizations, as explained in this …
Core Research Focus Area: Business Intelligence - Scope …
The Business Intelligence (BI) Focus Area provides organizations with the tools they need to deliver business insight and user perspective successfully by leveraging the organization's …
The Definitive Guide do Business Intelligence The …
Today, business intelligence is defined by Forrester as “a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information …
BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS …
Business intelligence (BI) is a technology-driven process for analyzing data and show actionable information to help corporate executives, business managers and other end users make more …
Business Intelligence Definition and Solutions - Ohio
Business intelligence, or BI, is an umbrella term that refers to a variety of software applications used to analyze an organization’s raw data. BI as a discipline is made up of several related …
Oracle® Business Intelligence Applications
Oracle Business Intelligence Applications is a comprehensive suite of prebuilt solutions that deliver pervasive intelligence across an organization, empowering users at all levels - from …
Business Intelligence Applications Examples [PDF]
Business Intelligence Applications Examples: Fundamentals of Business Intelligence Wilfried Grossmann,Stefanie Rinderle-Ma,2015-06-02 This book presents a comprehensive and …
Insights, Strategies, and Applications of Business Analytics
These examples illustrate how predictive analytics is applied in various industries to optimize operations, improve decision-making, enhance customer experiences, and drive business …
BUSINESS INTELLIGENCE - Xavier University
Business intelligence systems combine operational data with analytical tools to present complex and competitive information to planners and decision makers. The objective is to improve the …
Oracle® Business Intelligence Applications
Oracle Business Intelligence Applications are comprehensive prebuilt solutions that deliver pervasive intelligence across an organization, empowering users at all levels, from front line …
TYIT SEM VI BUSINESS INTELLIGENCE NOTES …
Business intelligence may be defined as a set of mathematical models and analysis methodologies that exploit the available data to generate information and knowledge useful for …
Business Analytics Principles, Concepts, and Applications: …
Business intelligence (BI) can be defined as a set of processes and technologies that convert data into meaningful and useful information for business purposes.
Introduction to Data Mining and Business Intelligence
Business intelligence is the transformation of raw data into knowledge and insight for making better business decisions. Data mining/analytics is closely related to the fields of database, …
BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS, …
Experts describe Business intelligence as a “business management term used to describe applications and technologies which are used to gather, provide access to analyze data and …
ENTERPRISE DATA MODELING FOR BUSINESS …
Ideally, a data architect with a focus on business intelligence will start with data models to document what data the organization has, where it resides, how it’s used, and who owns it to …
Business Intelligence Applications Examples Copy
Business Intelligence Applications Examples: Fundamentals of Business Intelligence Wilfried Grossmann,Stefanie Rinderle-Ma,2015-06-02 This book presents a comprehensive and …
UNIT 4 INTRODUCTION TO BUSINESS INTELLIGENCE
4.5 BUSINESS INTELLIGENCE APPLICATIONS from various sources to assist organizations in making better business decisions. These applications typically include features such as …
SurfBI Costing Analytics - Oracle
Oracle Business Intelligence Applications are comprehensive prebuilt solutions that deliver pervasive intelligence across an organization, empowering users at all level, from front line …
Topics in Business Intelligence - SMAA.fi
What is Business Intelligence (BI)? BI refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or …
Business Intelligence A Managerial Approach Pearson Pdf
Business Intelligence, Managerial Approach, Pearson PDF, Data Analysis, Decision Making, Strategic Planning, Data Visualization I. Start with a captivating statement about the …
