Business analytics

About: Business analytics is a research topic. Over the lifetime, 3593 publications have been published within this topic receiving 84601 citations. The topic is also known as: Business Analytics & business analytics.

Business Intelligence: The Savvy Manager's Guide

Abstract: Following the footsteps of the first edition, the second edition of Business Intelligence is a full overview of what comprises business intelligence. It is intended to provide an introduction to the concepts to uncomplicate the learning process when implementing a business intelligence program. Over a relatively long lifetime (7 years), the current edition of book has received numerous accolades from across the industry for its straightforward introduction to both business and technical aspects of business intelligence. As an author, David Loshin has a distinct ability to translate challenging topics into a framework that is easily digestible by managers, business analysts, and technologists alike. In addition, his material has developed a following (such as the recent Master Data Management book) among practitioners and key figures in the industry (both analysts and vendors) and that magnifies our ability to convey the value of this book. Guides managers through developing, administering, or simply understanding business intelligence technology Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization's data into actionable knowledge Contains a handy, quick-reference to technologies and terminology. Table of Contents 1. Business Intelligence - An Introduction 2. Value Drivers 3. Planning for Success 4. Developing a Business Intelligence Roadmap 5. The Business Intelligence Environment 6. Business Models and Information Flow 7. Data Requirements Analysis 8. Data Warehouses and the Technical BI Architecture 9. Business Metadata 10. Data Profiling 11. Business Rules 12. Data Quality 13. Data Integration 14. High Performance BI 15. Alternate Information Contexts 16. Location Intelligence and Spatial analysis? 17. Knowledge Discovery, Data Mining, and Analytics 18. Using Publicly Available Data 19. Knowledge Delivery 20. New and Emerging Techniques 21. Quick Reference

Business Intelligence Success Factors: Tools for Aligning Your Business in the Global Economy

Abstract: About the Contributors. Preface. Acknowledgments. PART ONE The Landscape. Chapter 1 The Evolving Business Landscape. Navigating Uncharted Waters. Shifting from Reactive to Proactive. Strategies for Capturing Value. Motivation for Change. The Evolving Organization. Chapter 2 Models from Science and Nature. Quantum Physics. Evolutionary Biology and Living Systems. Complexity Science and Chaos. Systems Theory and Systems Thinking. PART TWO The Success Factors. Chapter 3 Effective Communication. Benefits of Effective Communication. Principles of Communication. Communication in a High-Tech Economy. Nonverbal Communication. Theory of Relational Coordination. Principles of Dialogue. Art of Listening. Storytelling. Chapter 4 Collaboration. Collaborating for the Future. Creating a Collaborative Culture. Building Collaborative Teams. Value of Trust. Collaborative Technologies. Collaboration in Action: A Case Study. Chapter 5 Innovation. Creativity. Innovation in the Marketplace. Tips from the Field. Chapter 6 Adaptability. The Shifting Paradigm. Traditional Methods. The New Paradigm. Models for Adaptive Organizations. Leveraging Chaos in Organizations. Conflict Resolution: A Living Systems Approach. The Learning Organization. A New Global Organization. Chapter 7 Leadership. The Conscious Leader. Social Intelligence. Paradox of Empowerment. 10 Principles for Leading a Dynamic Organization. Tapping Organizational Wisdom. PART THREE Models and Practices. Chapter 8 Systems Thinking. Basics of Systems Thinking. Systems View of Business Analytics. Chapter 9 Holacracy. Evolving the Organization. Introducing Holacracy. Organizational Structure. Organizational Control. Core Practices. Shared Language and Meaning. PART FOUR Beyond Our Corporate Borders. Chapter 10 Possibilities. Holacracy in the World. Edgewalkers. Organizations on Purpose. Bottom Line. Appendix A: Resources. Appendix B: Suggested Reading. About the Author. Index.

Big Data and Transformational Government

Abstract: The big data phenomenon is growing throughout private and public sector domains. Profit motives make it urgent for companies in the private sector to learn how to leverage big data. However, in the public sector, government services could also be greatly improved through the use of big data. Here, the authors describe some drivers, barriers, and best practices affecting the use of big data and associated analytics in the government domain. They present a model that illustrates how big data can result in transformational government through increased efficiency and effectiveness in the delivery of services. Their empirical basis for this model uses a case vignette from the US Department of Veterans Affairs, while the theoretical basis is a balanced view of big data that takes into account the continuous growth and use of such data. This article is part of a special issue on big data and business analytics.

A framework for business analytics in performance management

Abstract: Purpose – Increased business competition requires even more rapid and sophisticated information and data analysis. These requirements challenge performance management to effectively support the decision making process. Business analytics is an emerging field that can potentially extend the domain of performance management to provide an improved understanding of business dynamics and lead to a better decision making. The purpose of this positional paper is to introduce performance management analytics as a potential extension of performance management research and practice. The paper clarifies the possible application areas of business analytics and their advantages within the context of performance management.Design/methodology/approach – The paper employs a literature based analysis and from this a conceptual argument is established. Finally, a business analytical model is presented to be used to undertake future research.Findings – The paper clarifies the possible application areas of business analytics...

Solving problems with visual analytics

Abstract: Visual analytics is an emerging research discipline aiming at making the best possible use of huge information loads in a wide variety of applications by appropriately combining the strengths of intelligent automatic data analysis with the visual perception and analysis capabilities of the human user. The major goal of visual analytics is the integration of these disciplines into visual analytics to acquire well-established and agreed upon concepts and theories, combining scientific breakthroughs in a single discipline to have a potential impact on visual analytics and vice versa. In a session at FET’11, the leaders of the thematic working groups of the recently finalised FET Open coordination action VisMaster CA presented the scientific challenges that were identified in the visual analytics research roadmap, and the connection between the various disciplines and the broader vision of visual analytics. This article contains excerpts from this research roadmap to motivate further research in this direction within FET.