This book discusses and conceptualizes practices on real-time strategy, focusing on the interplay between strategy and business intelligence. Combining strategic practices and business intelligence systems, the authors demonstrate how managerial practices can be developed in the age of digitization. Also developing the concept of strategic agility, the book provides perspectives from a range of disciplines including strategic practices and decision making, customer relationship management, human resource management, competitive intelligence, supplier network management and business intelligence systems. Presenting managerial frameworks and guidelines, Real-time Strategy and Business Intelligence explores how to improve utilization of business intelligence systems in real-time decision making. Providing practical and future-oriented insights backed by examples and best practices, the authors present a clearly conceptualized theoretical framework.

This book constitutes the thoroughly refereed conference proceedings of the BIRTE workshops listed below, which were held in in conjunction with VLDB, the International Conference on Very Large Data Bases: 9th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2015, held in Kohala Coast, Hawaii, in August 2015, 10th International Workshop on Enabling Real-Time Business Intelligence, BIRTE 2016, held in New Delhi, India, in September 2016, 11th International Workshop on Real-Time Business Intelligence and Analytics, BIRTE 2017, held in Munich, Germany, in August 2017. The BIRTE workshop series provides a forum for the discussion and advancement of the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques. The book includes five selected papers from BIRTE 2015; five selected papers from BIRTE 2016; and three selected papers from BIRTE 2017.

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

This book constitutes the thoroughly refereed conference proceedings of the 6th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2012, held in Istanbul, Turkey, in August 2012, in conjunction with VLDB 2012, the International Conference on Very Large Data Bases. The BIRTE workshop series provides a forum to discuss and advance the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques. This volume contains ten research papers, which were carefully reviewed and selected from 13 submissions.

Big Data Analytics Using Splunk is a hands-on book showing how to process and derive business value from big data in real time. Examples in the book draw from social media sources such as Twitter (tweets) and Foursquare (check-ins). You also learn to draw from machine data, enabling you to analyze, say, web server log files and patterns of user access in real time, as the access is occurring. Gone are the days when you need be caught out by shifting public opinion or sudden changes in customer behavior. Splunk’s easy to use engine helps you recognize and react in real time, as events are occurring. Splunk is a powerful, yet simple analytical tool fast gaining traction in the fields of big data and operational intelligence. Using Splunk, you can monitor data in real time, or mine your data after the fact. Splunk’s stunning visualizations aid in locating the needle of value in a haystack of a data. Geolocation support spreads your data across a map, allowing you to drill down to geographic areas of interest. Alerts can run in the background and trigger to warn you of shifts or events as they are taking place. With Splunk you can immediately recognize and react to changing trends and shifting public opinion as expressed through social media, and to new patterns of eCommerce and customer behavior. The ability to immediately recognize and react to changing trends provides a tremendous advantage in today’s fast-paced world of Internet business. Big Data Analytics Using Splunk opens the door to an exciting world of real-time operational intelligence. Built around hands-on projects Shows how to mine social media Opens the door to real-time operational intelligence

As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, it contains more than 70 chapters that approach decision support systems from a wide variety of perspectives. These range from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into ten major sections that novices and experts alike will refer to for years to come.

Aligning business intelligence (BI) infrastructure with strategy processes not only improves your organization's ability to respond to change, but also adds significant value to your BI infrastructure and development investments. Until now, there has been a need for a comprehensive book on business analysis for BI that starts with a macro view and

"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.

In todayís competitive and highly dynamic environment, analyzing data to understand how the business is performing, to predict outcomes and trends, and to improve the effectiveness of business processes underlying business operations has become cri- cal. The traditional approach to reporting is no longer adequate, users now demand easy-to-use intelligent platforms and applications capable of analyzing real-time bu- ness data to provide insight and actionable information at the right time. The end goal is to improve the enterprise performance by better and timelier decision making, - abled by the availability of up-to-date, high-quality information. As a response, the notion of "real-time enterprise" has emerged and is beginning to be recognized in the industry. Gartner defines it as “using up-to-date information, getting rid of delays, and using speed for competitive advantage is what the real-time enterprise is all about. . . Indeed, the goal of the real-time enterprise is to act on events as they happen. ” Although there has been progress in this direction and many com- nies are introducing products toward making this vision a reality, there is still a long way to go. In particular, the whole lifecycle of business intelligence requires new techniques and methodologies capable of dealing with the new requirements imposed by the real-time enterprise.

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.