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This book constitutes the thoroughly refereed post-workshop proceedings of eight international workshops held in Ulm, Germany, in conjunction with the 7th International Conference on Business Process Management, BPM 2009, in September 2009. The eight workshops were on Empirical Research in Business Process Management (ER-BPM 2009), Reference Modeling (RefMod 2009), Business Process Design (BPD 2009), Business Process Intelligence (BPI 2009), Collaborative Business Processes (CBP 2009), Process-Oriented Information Systems in Healthcare (ProHealth 2009), Business Process Management and Social Software (BPMS2 2009), Event-Driven Business Process Management (edBPM 2009). The 67 revised full papers presented were carefully reviewed and selected from numerous submissions.

Business -- Data processing -- Congresses. --- Business -- Data processing -- Management -- Congresses. --- Business -- Data processing -- Management. --- Business -- Data processing. --- Management information systems -- Congresses. --- Management information systems. --- Workflow -- Management -- Congresses. --- Industrial management --- Marketing & Sales --- Commerce - General --- Commerce --- Business & Economics --- Business --- Management information systems --- Workflow --- Data processing --- Management --- Workflow systems --- Trade --- Business. --- Information technology. --- Business mathematics. --- Software engineering. --- Application software. --- Computer engineering. --- Business and Management. --- Business Mathematics. --- Software Engineering/Programming and Operating Systems. --- Computer Engineering. --- IT in Business. --- Information Systems Applications (incl. Internet). --- Computer Applications. --- Data processing. --- Computers --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Computer software engineering --- Engineering --- Arithmetic, Commercial --- Business arithmetic --- Business math --- Commercial arithmetic --- Finance --- Mathematics --- Electronic data processing --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Economics --- Design and construction --- Computer science. --- Informatics --- Science --- Business—Data processing. --- Industrial management. --- Business administration --- Business enterprises --- Business management --- Corporate management --- Corporations --- Industrial administration --- Management, Industrial --- Rationalization of industry --- Scientific management --- Industrial organization

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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.

Data mining. --- Management information systems. --- Information systems. --- Data Mining and Knowledge Discovery. --- Business Information Systems. --- Computer Appl. in Administrative Data Processing. --- Information Systems Applications (incl. Internet). --- Business Process Management. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Communication systems --- Business intelligence --- Data processing. --- Application software. --- Industrial management. --- Business administration --- Business enterprises --- Business management --- Corporate management --- Corporations --- Industrial administration --- Management, Industrial --- Rationalization of industry --- Scientific management --- Business --- Industrial organization --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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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 policy --- Computer. Automation

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This book constitutes the revised selected papers from the 6th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2016, held in Graz, Austria in December 2016. The 5 papers presented in this volume were carefully reviewed and selected from 18 submissions. In this edition, the presentations focused on the adoption of process mining algorithms for continuous monitoring of business process. They underline the most relevant challenges identified and propose novel solutions for their resolution.

Computer science. --- Management information systems. --- Industrial management. --- Data mining. --- Application software. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Business Process Management. --- Information Systems Applications (incl. Internet). --- Computer Appl. in Administrative Data Processing. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Business administration --- Business enterprises --- Business management --- Corporate management --- Corporations --- Industrial administration --- Management, Industrial --- Rationalization of industry --- Scientific management --- Management --- Business --- Industrial organization --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Informatics --- Science --- Communication systems --- Information systems. --- Data mining --- Information technology --- Computer and Information Systems Applications. --- Computer Application in Administrative Data Processing. --- Management.

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This book constitutes the revised selected papers from the 6th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2016, held in Graz, Austria in December 2016. The 5 papers presented in this volume were carefully reviewed and selected from 18 submissions. In this edition, the presentations focused on the adoption of process mining algorithms for continuous monitoring of business process. They underline the most relevant challenges identified and propose novel solutions for their resolution.

Office management --- Business management --- Programming --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- MIS (management informatie systeem) --- datamining --- informatica --- bedrijfsadministratie --- informatiesystemen --- organisatiecultuur --- data acquisition