| business process and data analysis: Business Process Analysis Geoffrey Darnton, Moksha Darnton, 1997 This is a ground-breaking book, primarily in its successful attempt to operationalise and provide empirical foundations for procedures for radical change previously developed only intuitively. The book is supported by prominent academics and practitioners in the field, including Jim Short (LBS), Raul Espejo, Dan Teichroew (Michigan), and others. It should become the standard reference for managers and consultants in BPR. |
| business process and data analysis: Process Analytics Seyed-Mehdi-Reza Beheshti, Boualem Benatallah, Sherif Sakr, Daniela Grigori, Hamid Reza Motahari-Nezhad, Moshe Chai Barukh, Ahmed Gater, Seung Hwan Ryu, 2016-03-28 This book starts with an introduction to process modeling and process paradigms, then explains how to query and analyze process models, and how to analyze the process execution data. In this way, readers receive a comprehensive overview of what is needed to identify, understand and improve business processes. The book chiefly focuses on concepts, techniques and methods. It covers a large body of knowledge on process analytics – including process data querying, analysis, matching and correlating process data and models – to help practitioners and researchers understand the underlying concepts, problems, methods, tools and techniques involved in modern process analytics. Following an introduction to basic business process and process analytics concepts, it describes the state of the art in this area before examining different analytics techniques in detail. In this regard, the book covers analytics over different levels of process abstractions, from process execution data and methods for linking and correlating process execution data, to inferring process models, querying process execution data and process models, and scalable process data analytics methods. In addition, it provides a review of commercial process analytics tools and their practical applications. The book is intended for a broad readership interested in business process management and process analytics. It provides researchers with an introduction to these fields by comprehensively classifying the current state of research, by describing in-depth techniques and methods, and by highlighting future research directions. Lecturers will find a wealth of material to choose from for a variety of courses, ranging from undergraduate courses in business process management to graduate courses in business process analytics. Lastly, it offers professionals a reference guide to the state of the art in commercial tools and techniques, complemented by many real-world use case scenarios. |
| business process and data analysis: Business Analytics Jay Liebowitz, 2013-12-19 Together, Big Data, high-performance computing, and complex environments create unprecedented opportunities for organizations to generate game-changing insights that are based on hard data. Business Analytics: An Introduction explains how to use business analytics to sort through an ever-increasing amount of data and improve the decision-making cap |
| business process and data analysis: Business analyst: a profession and a mindset Yulia Kosarenko, 2019-05-12 What does it mean to be a business analyst? What would you do every day? How will you bring value to your clients? And most importantly, what makes a business analyst exceptional? This book will answer your questions about this challenging career choice through the prism of the business analyst mindset — a concept developed by the author, and its twelve principles demonstrated through many case study examples. Business analyst: a profession and a mindset is a structurally rich read with over 90 figures, tables and models. It offers you more than just techniques and methodologies. It encourages you to understand people and their behaviour as the key to solving business problems. |
| business process and data analysis: Business Process Modeling, Simulation and Design: Manuel Laguna, Johan Marklund, 2011 Business Process Modeling, Simulation and Design covers the design of business processes from a broad quantitative modeling perspective. The text presents a multitude of analytical tools that can be used to model, analyze, understand and ultimately, to design business processes. The range of topics in this text include graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, analytical queuing methods, as well as the use of Data Envelopment Analysis (DEA) for benchmarking purposes. And a major portion of the book is devoted to simulation modeling using a state of the art discrete-event simulation package. |
| business process and data analysis: Business Process Management: Current Applications and the Challenges of Adoption Renata Gabryelczyk, Tomislav Hernaus, 2020-01-01 Business Process Management (BPM) has been evolving for over 25 years in information systems research, management science, and organizational practice (Vom Brocke & Mendling, 2018). The earliest characteristics of BPM concentrated around process analysis, improvement and control, in a less strict manner that required reengineering (Elzinga, Horak, Lee, & Bruner, 1995). More mature approaches, observed since the year 2000, have been promoting the so-called process thinking, i.e. managing an organization from a process-based point of view. These approaches emphasize that process and team work oriented organizational structures should be aligned with other management systems. Process management should be holistic by its nature so as to cover an entire organization. Although BPM researchers stressed the need for system thinking at that time, published literature distinguished two perspectives of looking at BPM: the organizational perspective and the technological perspective of BPM. From the organizational perspective, authors focused on a number of key factors, i.e., process governance, a process-based organizational structure concept, customer orientation of internal and external processes, managing an organization based on process outputs, building process relations, and improving process maturity throughout the customer value chain, as well as through strategically aligning process initiatives to organizational objectives. From the technological perspective, the key factors of interest to authors, referred to as BPMS (Business Process Management System), include IT methods, techniques and tools that support the designing, implementation, modeling and simulation of business processes and are considered to be an extension of classical workflow systems or an environment for designing management support IT systems, e.g. ERP class systems. An integrated and interdisciplinary approach was proposed in the framework of six core BPM elements required for the holistic and sustainable use of process management (Rosemann & Vom Brocke, 2010). These include strategic alignment, governance, methods, information technology, people and culture. In this sense, technology is only one of six closely interrelated elements. Currently, there are two distinct directions in the evolution of BPM: traditional BPM and digital BPM. The former encompasses methods, techniques and systems that traditionally lead to increased organizational efficiency and to improved process effectiveness and flexibility. Although studies on BPM have been continuously evolving, some research gaps still remain open. The traditional understanding of process management seems particularly vital to organizations in developing economies, which sometimes follow practices and models that were designed and tested in highly developed countries, but should also be committed to drawing on their own experience and understanding of their local business environment (Gabryelczyk & Roztocki, 2018). Research on BPM in this traditional focus is still needed to better document, implement and improve idiosyncratic business processes in the context of an organization, environment, culture, and country. This is also confirmed by research conducted under the JEMI Special Issue on Business Process Management. Besides the traditionally shaped approach to BPM, organizations increasingly treat BPM as a driver of organizational innovation and as an essential part of the digital transformation (Vom Brocke & Schmiedel, 2015). New digital technologies such as social media, digital platforms, big data and advanced data analytics, blockchains, robotics, etc., enable development and growth in a constantly changing environment. To take advantage of these opportunities in the digital world, organizations require new BPM competences and capabilities. However, digital disruption creates quite a challenge for the BPM research community. How can BPM capabilities be developed in order to achieve adaptability, growth, flexibility, and agility? How can BPM foster innovations within and throughout organizations? These are just some of the issues for future BPM-related research. Threads associated with employing BPM for digital transformation have been included in a proposed Special Issue on BPM. This Special Issue on BPM consists of six articles including contributions from invited authors from three transition economies: Croatia, Slovakia, and Poland. All of the papers focus on applications of the process approach to management or directly to the adoption of Business Process Management. The majority of articles relate to the traditional BPM thread, although the indicated BPM alliances with other concepts such as Knowledge Management, Change Management, and Project Management are worthy of note. Only one article addresses the topic of BPM in the context of digital transformation. The nature and structure of these articles may be indicative of the current motivational factors and process maturity levels of organizations adopting ordinary and/or advanced BPM practices. When analyzing the content of individual articles, we pay attention to the factors underlying BPM adoption. We understand the primary motivation to be the expected benefits from BPM. Therefore, we can assume this Special Issue to be a contribution to BPM development in the form of the indicating motivation and triggers for BPM adoption. The first paper, by Jerzy Auksztol and Magdalena Chomuszko, proposes a process-based approach to construct a Data Control Framework for Standard Audit File for Tax (SAF-T). The process approach is used to redesign the internal financial control processes and procedures of an organization to meet the new requirements of a fiscal audit. The process approach, combined with risk management and quality management, is, therefore, a tool supporting entrepreneurs adapting to new regulations imposed on them by their external environment, particularly those of tax authorities. Therefore, in this case, the main motivation for adopting elements of BPM was the impact of external environment factors. The paper by Ana-Marija Stjepić, Lucija Ivančić, and Dalia Suša Vugec focuses on the link between Business Process Management and digital transformation. The authors have developed a theoretical framework for the emerging role of BPM in digitalization and as a guide for researchers and practitioners conducting digital transformation initiatives in organizations. The results obtained in the article prove that the set goals and expected benefits of digital transformation can be achieved by a rethink and improvement of the processes, with a particular focus on end-to-end customer processes through supply chain management. Based on this article, we can conclude that one of the main motivational factors for BPM adoption is a desire to obtain the benefits of digital transformation. The article written by Miroslava Nyulásziová and Dana Paľová takes up the issues of using and linking the process approach and BPM lifecycle with the designing of decision support systems. The authors of this paper have developed an innovative system for decision support by implementing modeling, analysis, and improvement methods to the transportation process in the studied organization. The forwarding company’s case study presented in the paper also shows how BPM adoption began with a single main process that has been streamlined and automated. Therefore, the motivations for BPM adoption were not only operational, relating to the optimization of the cost of the process, but also managerial, oriented on improving the decision-making process. The use of information technology allowed the full exploitation of the potential for process improvements. The next paper by Olga Sobolewska is about incorporating the issues of BPM into the contemporary challenges of network organizations. The author claims that the organization’s orientation towards both business processes and knowledge management is a strong success factor for network cooperation. The author argues that modern organizations should focus on managing knowledge-oriented processes to become attractive to cooperation partners for network organizations. In this article, BPM adoption is of a strategic nature for the purposes of undertaking new forms of cooperation. The paper by Hubert Bogumił has an interdisciplinary character and, in a unique way, shows the connections between the concepts of process management, organizational change management, and IT project management. The author undertook the challenge of examining how problems for organizations managing IT projects facilitate in different ways the use of distinctive approaches to improve business processes. The author emphasizes that the main difficulty is the fact that modern organizations most often use a hybrid approach, with elements of both traditional project management and agile. The need to create a work environment that takes into account the risk of unexpected system and business regression, as well as a diagnosis of the causes and methods of its mitigation, is the initial research result in this paper. This article contributes to the development of BPM governance and integration of IT governance. The motivational factors for BPM are multi-faceted, as is the scope of the article. However, their managerial and cultural character (related to methods of communication and rules of cooperation in teams) should be emphasized. The article by Agnieszka Bitkowska concerns the integration of the concept of Knowledge Management and BPM. The author restates in her article that the identification, acquisition, presentation and documentation of knowledge are not independent tasks, but are implemented within business processes. In this paper, the correlations between BPM and Knowledge Management have been examined and the benefits and practical implications resulting from the integrated implementation of both concepts are emphasized. In the case of this article, BPM adoption can be a success factor for the implementation of Knowledge Management and the achievement of associated benefits. Studying Business Process Management from the different angles presented in this Special Issue should enrich our understanding of current BPM practices and better realize future challenges, especially those related to BPM development in the context of digital transformation and the integration of BPM with other management-related concepts. In addition, the contribution made by the authors of this Special Issue allowed us to see various motivations and triggers for BPM adoption, from operational, to managerial, strategic, cultural and technological ones, and those driven by the external environment. We would like to thank the authors for their contribution to this Special Issue. We would also like to thank all the reviewers for their valuable comments, which helped the authors improve their articles significantly. We are firmly convinced that the BPM research results presented in this Special Issue will help strengthen the existing body of BPM knowledge. We recommend reading the related issue of the JEMI journal to the wider community of BPM researchers, practitioners, and enthusiasts. Guest Editors Renata Gabryelczyk , Tomislav Hernaus Acknowledgments The editorial work on this Special Issue was supported by the Polish National Science Centre, Poland, Grant No. 2017/27/B/HS4/01734. References Elzinga, D. J., Horak, T., Lee, C.-Y., & Bruner, C. (1995). Business process management: Survey and methodology. IEEE Transactions on Engineering Management, 42(2), 119-128. http://dx.doi.org/10.1109/17.387274 Gabryelczyk, R., & Roztocki, N. (2018). Business process management success framework for transition economies. Information Systems Management, 35(3), 234-253. http://dx.doi.org/10.1080/10580530.2018.1477299http://dx.doi.org/10.1080/10580530.2018.1477299 Rosemann, M., & Vom Brocke, J. (2010). The six core elements of business process management. In Handbook on Business Process Management 1. Cham: Springer. Vom Brocke, J., & Mendling, J. (Eds.). (2018). Business Process Management Cases. Digital Innovation and Business Transformation in Practice. Berlin: Springer. Vom Brocke, J., & Schmiedel, T. (Eds.). (2015). BPM-Driving Innovation in a Digital World. Cham: Springer. |
| business process and data analysis: Fundamentals of Business Process Management Marlon Dumas, Marcello La Rosa, Jan Mendling, Hajo A. Reijers, 2018-03-23 This textbook covers the entire Business Process Management (BPM) lifecycle, from process identification to process monitoring, covering along the way process modelling, analysis, redesign and automation. Concepts, methods and tools from business management, computer science and industrial engineering are blended into one comprehensive and inter-disciplinary approach. The presentation is illustrated using the BPMN industry standard defined by the Object Management Group and widely endorsed by practitioners and vendors worldwide. In addition to explaining the relevant conceptual background, the book provides dozens of examples, more than 230 exercises – many with solutions – and numerous suggestions for further reading. This second edition includes extended and completely revised chapters on process identification, process discovery, qualitative process analysis, process redesign, process automation and process monitoring. A new chapter on BPM as an enterprise capability has been added, which expands the scope of the book to encompass topics such as the strategic alignment and governance of BPM initiatives. The textbook is the result of many years of combined teaching experience of the authors, both at the undergraduate and graduate levels as well as in the context of professional training. Students and professionals from both business management and computer science will benefit from the step-by-step style of the textbook and its focus on fundamental concepts and proven methods. Lecturers will appreciate the class-tested format and the additional teaching material available on the accompanying website. |
| business process and data analysis: Applied Business Analytics Nathaniel Lin, 2014-12-12 Bridge the gap between analytics and execution, and actually translate analytics into better business decision-making! Now that you've collected data and crunched numbers, Applied Business Analytics reveals how to fully apply the information and knowledge you've gleaned from quants and tech teams. Nathaniel Lin explains why analytics value chains often break due to organizational and cultural issues, and offers in the trenches guidance for overcoming these obstacles. You'll discover why a special breed of analytics deciders is indispensable for any organization that seeks to compete on analytics... how to become one of those deciders... and how to identify, foster, support, empower, and reward others to join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at all levels: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ — and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer Applied Business Analytics will be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics, including Chief Analytics Officers, Chief Data Officers, Chief Scientists, Chief Marketing Officers, Chief Risk Officers, Chief Strategy Officers, VPs of Analytics and/or Big Data, data scientists, business strategists, and line of business executives. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program, including candidates for INFORMS certification. |
| business process and data analysis: Agile Data Warehouse Design Lawrence Corr, Jim Stagnitto, 2011-11 Agile Data Warehouse Design is a step-by-step guide for capturing data warehousing/business intelligence (DW/BI) requirements and turning them into high performance dimensional models in the most direct way: by modelstorming (data modeling + brainstorming) with BI stakeholders. This book describes BEAM✲, an agile approach to dimensional modeling, for improving communication between data warehouse designers, BI stakeholders and the whole DW/BI development team. BEAM✲ provides tools and techniques that will encourage DW/BI designers and developers to move away from their keyboards and entity relationship based tools and model interactively with their colleagues. The result is everyone thinks dimensionally from the outset! Developers understand how to efficiently implement dimensional modeling solutions. Business stakeholders feel ownership of the data warehouse they have created, and can already imagine how they will use it to answer their business questions. Within this book, you will learn: ✲ Agile dimensional modeling using Business Event Analysis & Modeling (BEAM✲) ✲ Modelstorming: data modeling that is quicker, more inclusive, more productive, and frankly more fun! ✲ Telling dimensional data stories using the 7Ws (who, what, when, where, how many, why and how) ✲ Modeling by example not abstraction; using data story themes, not crow's feet, to describe detail ✲ Storyboarding the data warehouse to discover conformed dimensions and plan iterative development ✲ Visual modeling: sketching timelines, charts and grids to model complex process measurement - simply ✲ Agile design documentation: enhancing star schemas with BEAM✲ dimensional shorthand notation ✲ Solving difficult DW/BI performance and usability problems with proven dimensional design patterns Lawrence Corr is a data warehouse designer and educator. As Principal of DecisionOne Consulting, he helps clients to review and simplify their data warehouse designs, and advises vendors on visual data modeling techniques. He regularly teaches agile dimensional modeling courses worldwide and has taught dimensional DW/BI skills to thousands of students. Jim Stagnitto is a data warehouse and master data management architect specializing in the healthcare, financial services, and information service industries. He is the founder of the data warehousing and data mining consulting firm Llumino. |
| business process and data analysis: Data Analytics for Organisational Development Uwe H. Kaufmann, Amy B. C. Tan, 2021-07-26 A practical guide for anyone who aspires to become data analytics–savvy Data analytics has become central to the operation of most businesses, making it an increasingly necessary skill for every manager and for all functions across an organisation. Data Analytics for Organisational Development: Unleashing the Potential of Your Data introduces a methodical process for gathering, screening, transforming, and analysing the correct datasets to ensure that they are reliable tools for business decision-making. Written by a Six Sigma Master Black Belt and a Lean Six Sigma Black Belt, this accessible guide explains and illustrates the application of data analytics for organizational development and design, with particular focus on Customer and Strategy Analytics, Operations Analytics and Workforce Analytics. Designed as both a handbook and workbook, Data Analytics for Organisational Development presents the application of data analytics for organizational design and development using case studies and practical examples. It aims to help build a bridge between data scientists, who have less exposure to actual business issues, and the non-data scientists. With this guide, anyone can learn to perform data analytics tasks from translating a business question into a data science hypothesis to understanding the data science results and making the appropriate decisions. From data acquisition, cleaning, and transformation to analysis and decision making, this book covers it all. It also helps you avoid the pitfalls of unsound decision making, no matter where in the value chain you work. Follow the “Five Steps of a Data Analytics Case” to arrive at the correct business decision based on sound data analysis Become more proficient in effectively communicating and working with the data experts, even if you have no background in data science Learn from cases and practical examples that demonstrate a systematic method for gathering and processing data accurately Work through end-of-chapter exercises to review key concepts and apply methods using sample data sets Data Analytics for Organisational Development includes downloadable tools for learning enrichment, including spreadsheets, Power BI slides, datasets, R analysis steps and more. Regardless of your level in your organisation, this book will help you become savvy with data analytics, one of today’s top business tools. |
| business process and data analysis: Business Process Analysis in the Digital Transformation Era Tukino, Ahmad Fauzi, Baenil Huda, 2024-05-05 Embark on a transformative journey into the heart of modern business practices with Business Process Analysis in the Digital Transformation Era. Through twelve insightful chapters, this comprehensive guide navigates the intricate landscape of digital transformation, offering practical insights and expert guidance for thriving in today's dynamic business environment. In Chapter 1, readers are introduced to the fundamental concepts of digital transformation and its profound implications for organizational processes and strategies. Delve deeper into the realm of Business Process Analysis in Chapter 2, where core principles and methodologies are explored to equip readers with the tools needed to navigate the complexities of digital transformation. Chapter 3 sheds light on the role of technology in driving Digital Transformation in Business, illuminating the ways in which organizations can leverage digital tools to stay ahead in a rapidly evolving marketplace. Discover cutting-edge Tools and Methods for Business Process Analysis in Chapter 4, as experts share practical techniques for optimizing workflows and enhancing efficiency in the digital era. Chapter 5 invites readers to explore the art of Modeling and Simulating Digital Business Processes, offering actionable strategies for designing and refining digital workflows for maximum impact. Unlock the secrets of Digital Business Process Optimization in Chapter 6, where industry pioneers reveal innovative approaches for streamlining operations and driving sustainable growth. In Chapter 7, delve into the world of Digital Business Process Automation and discover how automation technologies are revolutionizing traditional workflows to drive productivity and innovation. Chapter 8 explores the importance of Business Process Integration in the Era of Digital Transformation, highlighting the value of seamless collaboration and integration in achieving organizational success. Explore the power of Big Data Analysis in Digital Business Processes in Chapter 9, as experts demonstrate how data-driven insights can inform decision-making and drive strategic growth initiatives. Navigate the complex terrain of Security and Ethics in Digital Business Processes in Chapter 10, where critical considerations surrounding data security and ethical practices are explored in-depth. In Chapter 11, real-world Case Studies and Implementation examples offer practical insights and inspiration drawn from successful digital transformation initiatives across various industries. Finally, peer into the future in Chapter 12 as experts ponder the Challenges and Future of Business Process Analysis in the Digital Transformation Era, offering visionary perspectives on the evolving role of technology and its impact on business strategy and innovation. With its comprehensive coverage and actionable insights, Business Process Analysis in the Digital Transformation Era is an essential resource for business leaders, analysts, and practitioners seeking to thrive in the digital age. |
| business process and data analysis: The Business Analysis Handbook Helen Winter, 2019-09-03 FINALIST: Business Book Awards 2020 - Specialist Book Category FINALIST: PMI UK National Project Awards 2019 - Project Management Literature Category The business analyst role can cover a wide range of responsibilities, including the elicitation and documenting of business requirements, upfront strategic work, design and implementation phases. Typical difficulties faced by analysts include stakeholders who disagree or don't know their requirements, handling estimates and project deadlines that conflict, and what to do if all the requirements are top priority. The Business Analysis Handbook offers practical solutions to these and other common problems which arise when uncovering requirements or conducting business analysis. Getting requirements right is difficult; this book offers guidance on delivering the right project results, avoiding extra cost and work, and increasing the benefits to the organization. The Business Analysis Handbook provides an understanding of the analyst role and the soft skills required, and outlines industry standard tools and techniques with guidelines on their use to suit the most appropriate situations. Covering numerous techniques such as Business Process Model and Notation (BPMN), use cases and user stories, this essential guide also includes standard templates to save time and ensure nothing important is missed. |
| business process and data analysis: Big Data Analytics and Knowledge Discovery Matteo Golfarelli, Robert Wrembel, Gabriele Kotsis, A Min Tjoa, Ismail Khalil, 2021-09-04 This volume LNCS 12925 constitutes the papers of the 23rd International Conference on Big Data Analytics and Knowledge Discovery, held in September 2021. Due to COVID-19 pandemic it was held virtually. The 12 full papers presented together with 15 short papers in this volume were carefully reviewed and selected from a total of 71 submissions. The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields. |
| business process and data analysis: Business Process Improvement Workbook: Documentation, Analysis, Design, and Management of Business Process Improvement H. James Harrington, E. K. C. Esseling, H. van Nimwegen, 1997-04 Enables you to improve quality, productivity, and competitiveness the business process improvement way. This workbook shows you how to: understand and set process improvement goals; eliminate bureaucracies, duplication, and obsolescence; evaluate information management; research cycle time; analyze functions and tasks in administration; and more. |
| business process and data analysis: Data-Driven Process Discovery and Analysis Paolo Ceravolo, Stefanie Rinderle-Ma, 2017-01-20 This book constitutes the revised selected papers from the 5th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2015, held in Vienna, Austria in December 2015. The 8 papers presented in this volume were carefully reviewed and selected from 22 submissions. They cover theoretical issues related to process representation, discovery and analysis, or provide practical and operational experiences in process discovery and analysis. They focus mainly on the adoption of process mining algorithms in conjunction and coordination with other techniques and methodologies. |
| business process and data analysis: Head First Data Analysis Michael Milton, 2009-07-24 A guide for data managers and analyzers. It shares guidelines for identifying patterns, predicting future outcomes, and presenting findings to others. |
| business process and data analysis: Multilevel Business Processes Christoph Schütz, 2015-08-31 Christoph G. Schuetz examines the conceptual modeling aspects of multilevel business processes without neglecting the implementation aspects. Furthermore, he investigates the advantages of hetero-homogeneous models for quantitative business process analysis. Multilevel models reflect the reality of many information systems. In this respect process-aware information systems are no exception. Multilevel models capture interdependencies between business processes at different organizational levels and allow for a convenient representation of business process variability which, in turn, facilitates the analysis of business processes across different organizational units. |
| business process and data analysis: , |
| business process and data analysis: The Complete Guide to Business Process Management Jean-Noël Gillot, 2008 |
| business process and data analysis: The Practitioner's Guide to Data Quality Improvement David Loshin, 2010-11-22 The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. - Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. - Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. - Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. |
| business process and data analysis: Business Process Modeling, Simulation and Design Manuel Laguna, Johan Marklund, 2018-12-07 Business Process Modeling, Simulation and Design, Third Edition provides students with a comprehensive coverage of a range of analytical tools used to model, analyze, understand, and ultimately design business processes. The new edition of this very successful textbook includes a wide range of approaches such as graphical flowcharting tools, cycle time and capacity analyses, queuing models, discrete-event simulation, simulation-optimization, and data mining for process analytics. While most textbooks on business process management either focus on the intricacies of computer simulation or managerial aspects of business processes, this textbook does both. It presents the tools to design business processes and management techniques on operating them efficiently. The book focuses on the use of discrete event simulation as the main tool for analyzing, modeling, and designing effective business processes. The integration of graphic user-friendly simulation software enables a systematic approach to create optimal designs. |
| business process and data analysis: , |
| business process and data analysis: Multilevel Business Processes Christoph G. Schuetz, 2015-08-25 Christoph G. Schuetz examines the conceptual modeling aspects of multilevel business processes without neglecting the implementation aspects. Furthermore, he investigates the advantages of hetero-homogeneous models for quantitative business process analysis. Multilevel models reflect the reality of many information systems. In this respect process-aware information systems are no exception. Multilevel models capture interdependencies between business processes at different organizational levels and allow for a convenient representation of business process variability which, in turn, facilitates the analysis of business processes across different organizational units. |
| business process and data analysis: Handbook on Business Process Management and Digital Transformation Paul Grefen, Irene Vanderfeesten, 2024-08-06 Many organizations are currently undertaking digital transformation to improve their business processes and better achieve their goals. This Handbook provides a comprehensive overview of contemporary trends and research at the point where business process management and digital transformation meet. Presenting a multidisciplinary approach, it demonstrates the close link between these two fields through engagement with theory and practice. |
| business process and data analysis: Business Analysis For Dummies Kupe Kupersmith, Paul Mulvey, Kate McGoey, 2013-07-01 Your go-to guide on business analysis Business analysis refers to the set of tasks and activities that help companies determine their objectives for meeting certain opportunities or addressing challenges and then help them define solutions to meet those objectives. Those engaged in business analysis are charged with identifying the activities that enable the company to define the business problem or opportunity, define what the solutions looks like, and define how it should behave in the end. As a BA, you lay out the plans for the process ahead. Business Analysis For Dummies is the go to reference on how to make the complex topic of business analysis easy to understand. Whether you are new or have experience with business analysis, this book gives you the tools, techniques, tips and tricks to set your project’s expectations and on the path to success. Offers guidance on how to make an impact in your organization by performing business analysis Shows you the tools and techniques to be an effective business analysis professional Provides a number of examples on how to perform business analysis regardless of your role If you're interested in learning about the tools and techniques used by successful business analysis professionals, Business Analysis For Dummies has you covered. |
| business process and data analysis: Process Mining Wil van der Aalst, 2014-10-07 More and more information about business processes is recorded by information systems in the form of so-called “event logs”. Despite the omnipresence of such data, most organizations diagnose problems based on fiction rather than facts. Process mining is an emerging discipline based on process model-driven approaches and data mining. It not only allows organizations to fully benefit from the information stored in their systems, but it can also be used to check the conformance of processes, detect bottlenecks, and predict execution problems. Wil van der Aalst delivers the first book on process mining. It aims to be self-contained while covering the entire process mining spectrum from process discovery to operational support. In Part I, the author provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Part II focuses on process discovery as the most important process mining task. Part III moves beyond discovering the control flow of processes and highlights conformance checking, and organizational and time perspectives. Part IV guides the reader in successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM. Finally, Part V takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers. |
| business process and data analysis: Analytics in a Big Data World Bart Baesens, 2014-04-15 The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities. |
| business process and data analysis: Analytics at Work Thomas H. Davenport, Jeanne G. Harris, Robert Morison, 2010 As a follow-up to the successful Competing on Analytics, authors Tom Davenport, Jeanne Harris, and Robert Morison provide practical frameworks and tools for all companies that want to use analytics as a basis for more effective and more profitable decision making. Regardless of your company's strategy, and whether or not analytics are your company's primary source of competitive differentiation, this book is designed to help you assess your organization's analytical capabilities, provide the tools to build these capabilities, and put analytics to work. The book helps you answer these pressing questions: What assets do I need in place in my organization in order to use analytics to run my business? Once I have these assets, how do I deploy them to get the most from an analytic approach? How do I get an analytic initiative off the ground in the first place, and then how do I sustain analytics in my organization over time? Packed with tools, frameworks, and all new examples, Analytics at Work makes analytics understandable and accessible and teaches you how to make your company more analytical. |
| business process and data analysis: Business Process Standardization Björn Münstermann, 2014-11-30 Abstract: This book focuses on business process standards and standardization, offering an indepth multi-methodological analysis of the benefits organizations may obtain from BPS and how the benefits can best be achieved --Provided by publisher |
| business process and data analysis: Big Data Analysis for Green Computing Rohit Sharma, Dilip Kumar Sharma, Dhowmya Bhatt, Binh Thai Pham, 2021-10-28 This book focuses on big data in business intelligence, data management, machine learning, cloud computing, and smart cities. It also provides an interdisciplinary platform to present and discuss recent innovations, trends, and concerns in the fields of big data and analytics. Big Data Analysis for Green Computing: Concepts and Applications presents the latest technologies and covers the major challenges, issues, and advances of big data and data analytics in green computing. It explores basic as well as high-level concepts. It also includes the use of machine learning using big data and discusses advanced system implementation for smart cities. The book is intended for business and management educators, management researchers, doctoral scholars, university professors, policymakers, and higher academic research organizations. |
| business process and data analysis: Business Information Systems Workshops Witold Abramowicz, 2015-12-01 This book constitutes the refereed proceedings of the five workshops that were organized in conjunction with the International Conference on Business Information Systems, BIS 2015, which took place in Poznan, Poland, in June 2015. The 26 papers in this volume were carefully reviewed and selected from 56 submissions and were revised and extended after the event. The workshop topics covered knowledge-based business information systems (AKTB), business and IT alignment (BITA), transparency-enhancing technologies and privacy dashboards (PTDCS), semantics usage in enterprises (FSFE), and issues related to DBpedia. In addition two keynote papers are included in this book. |
| business process and data analysis: Business Modeling and Software Design Boris Shishkov, 2022-07-30 This book constitutes the refereed proceedings of the 12h International Symposium on Business Modeling and Software Design, BMSD 2022, which took place in Fribourg, Switzerland, in June 2022. The 12 full and 9 short papers included in this book were carefully reviewed and selected from a total of 56 submissions. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling and Software Development; Blockchain-Based Business Models and Information Systems; IoT and Implications for Enterprise Information Systems. Each year, a special theme is chosen, for making presentations and discussions more focused. The BMSD 2022 theme is: Information Systems Engineering and Trust. |
| business process and data analysis: Business Process Management Workshops Marcello La Rosa, Pnina Soffer, 2013-01-26 This book constitutes the refereed proceedings of 12 international workshops held in Tallinn, Estonia, in conjunction with the 10th International Conference on Business Process Management, BPM 2012, in September 2012. The 12 workshops comprised Adaptive Case Management and Other Non-Workflow Approaches to BPM (ACM 2012), Business Process Design (BPD 2012), Business Process Intelligence (BPI 2012), Business Process Management and Social Software (BPMS2 2012), Data- and Artifact-Centric BPM (DAB 2012), Event-Driven Business Process Management (edBPM 2012), Empirical Research in Business Process Management (ER-BPM 2012), Process Model Collections (PMC 2012), Process-Aware Logistics Systems (PALS 2012), Reuse in Business Process Management (rBPM 2012), Security in Business Processes (SBP 2012), and Theory and Applications of Process Visualization (TAProViz 2012). The 56 revised full papers presented were carefully reviewed and selected from 141 submissions. |
| business process and data analysis: Quality in Business Process Modeling John Krogstie, 2016-10-27 This book covers the whole spectrum of modeling goals to achieve optimal quality in the process model developed. It focuses on how to balance quality considerations across all semiotic levels when models are used for different purposes, and is based on SEQUAL, a framework for understanding the quality of models and modeling languages, which can take into account all main aspects relating to the quality of models. Chapter 1 focuses on the theoretical foundations, introducing readers to the topics of business processes and business process modeling, as well as the most important concept underlying the modeling of business processes. In turn, Chapter 2 addresses the quality of models in general and business process models in particular. Chapter 3 contains a specialization of SEQUAL for quality of business process models. In Chapter 4, examples of the practical uses of business process models are provided, together with the results of detailed case studies on how to achieve and maintain quality in business process models. Chapter 5 presents a process modeling value framework that demonstrates how to achieve more long-term and higher return on investment with regard to (business) process and enterprise models. Lastly, Chapter 6 reviews the main points of the book and discusses the potential for business process modeling in the future through its combination with other types of modeling. The book has two intended audiences. It is primarily intended for computer science, software engineering and information system students at the postgraduate level who want to know more about business process modeling and the quality of models in preparation for professional practice. The second audience consists of professionals with extensive experience in and responsibilities related to the development and evolution of process-oriented information systems and information systems methodologies in general, who need to formalize and structure their practical experience or update their knowledge as a way to improve their professional activity. The book also includes a number of real-world case studies that make it easier to grasp the main theoretical concepts, helping readers apply the approaches described. |
| business process and data analysis: On the Move to Meaningful Internet Systems: OTM 2018 Workshops Christophe Debruyne, Hervé Panetto, Wided Guédria, Peter Bollen, Ioana Ciuciu, Robert Meersman, 2019-02-06 This volume constitutes the refereed proceedings of the Confederated International International Workshop on Enterprise Integration, Interoperability and Networking (EI2N ), Fact Based Modeling ( FBM), Industry Case Studies Program ( ICSP ), and International Workshop on Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society (Meta4eS), held as part of OTM 2018 in October 2018 in Valletta, Malta. As the three main conferences and the associated workshops all share the distributed aspects of modern computing systems, they experience the application pull created by the Internet and by the so-called Semantic Web, in particular developments of Big Data, increased importance of security issues, and the globalization of mobile-based technologies. |
| business process and data analysis: Process Querying Methods Artem Polyvyanyy, 2022-05-27 This book presents a framework for developing as well as a comprehensive collection of state-of-the-art process querying methods. Process querying combines concepts from Big Data and Process Modeling and Analysis with Business Process Intelligence and Process Analytics to study techniques for retrieving and manipulating models of real-world and envisioned processes to organize and extract process-related information for subsequent systematic use. The book comprises sixteen contributed chapters distributed over four parts and two auxiliary chapters. The auxiliary chapters by the editor provide an introduction to the area of process querying and a summary of the presented methods, techniques, and applications for process querying. The introductory chapter also examines a process querying framework. The contributed chapters present various process querying methods, including discussions on how they instantiate the framework components, thus supporting the comparison of the methods. The four parts are due to the distinctive features of the methods they include. The first three are devoted to querying event logs generated by IT-systems that support business processes at organizations, querying process designs captured in process models, and methods that address querying both event logs and process models. The methods in these three parts usually define a language for specifying process queries. The fourth part discusses methods that operate over inputs other than event logs and process models, e.g., streams of process events, or do not develop dedicated languages for specifying queries, e.g., methods for assessing process model similarity. This book is mainly intended for researchers. All the chapters in this book are contributed by active researchers in the research disciplines of business process management, process mining, and process querying. They describe state-of-the-art methods for process querying, discuss use cases of process querying, and suggest directions for future work for advancing the field. Yet, also other groups like business or data scientists and other professionals, lecturers, graduate students, and tool vendors will find relevant information for their distinctive needs. Chapter Celonis PQL: A Query Language for Process Mining is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| business process and data analysis: Database Development and Management Lee Chao, 2006-01-13 Today's database professionals must understand how to apply database systems to business processes and how to develop database systems for both business intelligence and Web-based applications. Database Development and Management explains all aspects of database design, access, implementation, application development, and management, as well |
| business process and data analysis: Business Process Management Workshops Michael zur Muehlen, Jianwen Su, 2011-05-10 This book constitutes the thoroughly refereed post-workshop proceedings of nine international workshops held in Hoboken, NJ, USA, in conjunction with the 8th International Conference on Business Process Management, BPM 2010, in September 2010. The nine workshops focused on Reuse in Business Process Management (rBPM 2010), Business Process Management and Sustainability (SusBPM 2010), Business Process Design (BPD 2010), Business Process Intelligence (BPI 2010), Cross-Enterprise Collaboration, People, and Work (CEC-PAW 2010), Process in the Large (IW-PL 2010), Business Process Management and Social Software (BPMS2 2010), Event-Driven Business Process Management (edBPM 2010), and Traceability and Compliance of Semi-Structured Processes (TC4SP 2010). In addition, three papers from the special track on Advances in Business Process Education are also included in this volume. The overall 66 revised full papers presented were carefully reviewed and selected from 143 submissions. |
| business process and data analysis: Business Process Management Systems James F. Chang, 2016-04-19 With a focus on strategy and implementation, James Chang discusses business management practices and the technology that enables them. He analyzes the history of process management practices and demonstrates that BPM practices are a synthesis of radical change and continuous change practices. The book is relevant to both business and IT professi |
| business process and data analysis: 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 | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
