Models and methods for operational risks assessment and mitigation are gaining importance in financial institutions, healthcare organizations, industry, businesses and organisations in general. This book introduces modern Operational Risk Management and describes how various data sources of different types, both numeric and semantic sources such as text can be integrated and analyzed. The book also demonstrates how Operational Risk Management is synergetic to other risk management activities such as Financial Risk Management and Safety Management. Operational Risk Management: a practical approach to intelligent data analysis provides practical and tested methodologies for combining structured and unstructured, semantic-based data, and numeric data, in Operational Risk Management (OpR) data analysis. Key Features: The book is presented in four parts: 1) Introduction to OpR Management, 2) Data for OpR Management, 3) OpR Analytics and 4) OpR Applications and its Integration with other Disciplines. Explores integration of semantic, unstructured textual data, in Operational Risk Management. Provides novel techniques for combining qualitative and quantitative information to assess risks and design mitigation strategies. Presents a comprehensive treatment of «near-misses» data and incidents in Operational Risk Management. Looks at case studies in the financial and industrial sector. Discusses application of ontology engineering to model knowledge used in Operational Risk Management. Many real life examples are presented, mostly based on the MUSING project co-funded by the EU FP6 Information Society Technology Programme. It provides a unique multidisciplinary perspective on the important and evolving topic of Operational Risk Management. The book will be useful to operational risk practitioners, risk managers in banks, hospitals and industry looking for modern approaches to risk management that combine an analysis of structured and unstructured data. The book will also benefit academics interested in research in this field, looking for techniques developed in response to real world problems.
In this book, authors Dalton Cervo and Mark Allen show you how to implement Master Data Management (MDM) within your business model to create a more quality controlled approach. Focusing on techniques that can improve data quality management, lower data maintenance costs, reduce corporate and compliance risks, and drive increased efficiency in customer data management practices, the book will guide you in successfully managing and maintaining your customer master data. You'll find the expert guidance you need, complete with tables, graphs, and charts, in planning, implementing, and managing MDM.
Tag-based approaches were originally designed to increase the throughput of capillary sequencing, where concatemers of short sequences were first used in expression profiling. New Next Generation Sequencing methods largely extended the use of tag-based approaches as the tag lengths perfectly match with the short read length of highly parallel sequencing reactions. Tag-based approaches will maintain their important role in life and biomedical science, because longer read lengths are often not required to obtain meaningful data for many applications. Whereas genome re-sequencing and de novo sequencing will benefit from ever more powerful sequencing methods, analytical applications can be performed by tag-based approaches, where the focus shifts from 'sequencing power' to better means of data analysis and visualization for common users. Today Next Generation Sequence data require powerful bioinformatics expertise that has to be converted into easy-to-use data analysis tools. The book's intention is to give an overview on recently developed tag-based approaches along with means of their data analysis together with introductions to Next-Generation Sequencing Methods, protocols and user guides to be an entry for scientists to tag-based approaches for Next Generation Sequencing.
This book argues persuasively that a behavioral perspective offers the best foundation for strategic management scholarship. This book presents a focused approach to strategic management theory. Outlines the basics of a behavioral approach to strategic management. Examines assumptions of rationality and equilibrium and the problems they create. Considers how a behavioral approach relates to a number of conventional approaches.
A ground shaking exposé on the failure of popular cyber risk management methods How to Measure Anything in Cybersecurity Risk exposes the shortcomings of current «risk management» practices, and offers a series of improvement techniques that help you fill the holes and ramp up security. In his bestselling book How to Measure Anything, author Douglas W. Hubbard opened the business world's eyes to the critical need for better measurement. This book expands upon that premise and draws from The Failure of Risk Management to sound the alarm in the cybersecurity realm. Some of the field's premier risk management approaches actually create more risk than they mitigate, and questionable methods have been duplicated across industries and embedded in the products accepted as gospel. This book sheds light on these blatant risks, and provides alternate techniques that can help improve your current situation. You'll also learn which approaches are too risky to save, and are actually more damaging than a total lack of any security. Dangerous risk management methods abound; there is no industry more critically in need of solutions than cybersecurity. This book provides solutions where they exist, and advises when to change tracks entirely. Discover the shortcomings of cybersecurity's «best practices» Learn which risk management approaches actually create risk Improve your current practices with practical alterations Learn which methods are beyond saving, and worse than doing nothing Insightful and enlightening, this book will inspire a closer examination of your company's own risk management practices in the context of cybersecurity. The end goal is airtight data protection, so finding cracks in the vault is a positive thing—as long as you get there before the bad guys do. How to Measure Anything in Cybersecurity Risk is your guide to more robust protection through better quantitative processes, approaches, and techniques.
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.
Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.
Today's most successful companies are Intelligent Companies that use the best available data to inform their decision making. This is called Evidence-Based Management and is one of the fastest growing business trends of our times. Intelligent Companies bring together tools such as Business Intelligence, Analytics, Key Performance Indicators, Balanced Scorecards, Management Reporting and Strategic Decision Making to generate real competitive advantages. As information and data volumes grow at explosive rates, the challenges of managing this information is turning into a losing battle for most companies and they end up drowning in data while thirsting for insights. This is made worse by the severe skills shortage in analytics, data presentation and communication. This latest book by best-selling management expert Bernard Marr, will equip you with a set of powerful skills that are vital for successful managers now and in the future. Increase your market value by gaining essential skills that are in high demand but in short supply. Loaded with practical step-by-step guidance, simple tools and real life examples of how leading organizations such as Google, CocaCola, Capital One, Saatchi & Saatchi, Tesco, Yahoo, as well as Government Departments and Agencies have put the principles into practice. The five steps to more intelligent decision making are: Step 1: More intelligent strategies – by identifying strategic priorities and agreeing your real information needs Step 2: More intelligent data – by creating relevant and meaningful performance indicators and qualitative management information liked back to your strategic information needs Step 3: More intelligent insights – by using good evidence to test and prove ideas and by analysing the data to gain robust and reliable insights Step 4: More intelligent communication – by creating informative and engaging management information packs and dashboards that provide the essential information, packaged in an easy-to-read way Step 5: More intelligent decision making – by fostering an evidence-based culture of turning information into actionable knowledge and real decisions «Bernard Marr did it again! This outstanding and practical book will help your company become more intelligent and more successful. Marr takes the fields of business-intelligence, analytics and scorecarding to bring them together into a powerful and easy-to-follow 5-step framework. The Intelligent Company is THE must-read book of our times.» —Bruno Aziza, Co-author of best-selling book Drive Business Performance and Worldwide Strategy Lead, Microsoft Business Intelligence «Book after book Bernard Marr is redefining the fundamentals of good business management. 'The Intelligent Company' is a must read in these changing times and a reference you will want on your desk every day!» —Gabriel Bellenger, Accenture Strategy
The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.
Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.
Create and modify databases and keep them secure Get up to speed on using T-SQL to store and manipulate data SQL Server 2005 improves an already great database management system. This book shows you how to put it to work in a hurry. You'll find out how to use the SQL Server Management Studio and the SQLCMD utility to write T-SQL code, retrieve data from single or multiple SQL Server tables, add data using the INSERT statement, and much more. * Create queries to retrieve data * Ensure SQL Server security * Use Visual Studio(r) 2005 with SQL Server * Create tables, views, and indexes * Work with Common Language Runtime * Query XML data
In an increasingly digital economy, mastering the quality of data is an increasingly vital yet still, in most organizations, a considerable task. The necessity of better governance and reinforcement of international rules and regulatory or oversight structures (Sarbanes Oxley, Basel II, Solvency II, IAS-IFRS, etc.) imposes on enterprises the need for greater transparency and better traceability of their data. All the stakeholders in a company have a role to play and great benefit to derive from the overall goals here, but will invariably turn towards their IT department in search of the answers. However, the majority of IT systems that have been developed within businesses are overly complex, badly adapted, and in many cases obsolete; these systems have often become a source of data or process fragility for the business. It is in this context that the management of ‘reference and master data’ or Master Data Management (MDM) and semantic modeling can intervene in order to straighten out the management of data in a forward-looking and sustainable manner. This book shows how company executives and IT managers can take these new challenges, as well as the advantages of using reference and master data management, into account in answering questions such as: Which data governance functions are available? How can IT be better aligned with business regulations? What is the return on investment? How can we assess intangible IT assets and data? What are the principles of semantic modeling? What is the MDM technical architecture? In these ways they will be better able to deliver on their responsibilities to their organizations, and position them for growth and robust data management and integrity in the future.
A corporate performance management system can transform your business – but only if it is designed and implemented in the right way. this book will provide you with the tools and approaches to help translate your strategy into action and make you aware of the pitfalls to be avoided. The Handbook of Corporate Performance Management takes a practical approach, offering guidance on what works, tools to use, and how leadership makes an essential contribution to success. THE BOOK IS BROADLY DIVIDED INTO FOUR SECTIONS: Section One Provides the essential toolkit for setting up and implementing a corporate performance management system. It covers the processes and approaches you need to make it work. Section two explains how you can use performance management to manage your business from tracking performance through the management review process to checking whether your strategy is still appropriate. Section three provides guidance for measuring specific key areas; financial performance, staff performance, customers, processes, competence and resource development, and sustainability. Section four is about bringing it all together. Case studies of individuals from widely differing organisations, who have all delivered great results, illustrate the importance of good leadership in creating a culture of high performance. The Handbook of Corporate Performance Management is the essential guide to using performance measurement and management to get the best out of your business.
Your people hold the key to your business success Make Your People Before You Make Your Products is an authoritative guide to the evolution of talent management. Written specifically for HR professionals this book describes how organizations can gain a global competitive edge through better management of talent resources. With a practice-based philosophy, readers will learn more effective talent management strategies for a complex market in which people are often the only competitive advantage. Inclusivity is emphasized, and discussion centres on innovative, dynamic, fluid approaches to talent acquisition, development, and retention. In today's market environment, talent has moved from audience to community while leadership has shifted from control to empowerment. Traditional, linear approaches to talent management are falling short, and directing resources solely to senior management and HIPOs is no longer a valid strategy. This book provides practical guidance on more modern approaches, helping organizations to: Attract and retain the best talent by expanding talent resource management Augment traditional management methods with more dynamic techniques Develop a talent strategy that recognizes the new diversity of supply and demand Consider the evolving roles of talent and leadership in a global context Contextual changes in workplace dynamics necessitate an updated approach for keeping the best people on board and using them to their utmost potential. Talent management is a driving force behind an organization's success, affecting outcomes by every major metric – if the strategy becomes stale, success is no longer sustainable. Make Your People Before You Make Your Products is guide toward developing an organization's greatest asset.
A step-by-step guide to managing critical technologies of today's converged services IP networks Effective IP Address Management (IPAM) has become crucial to maintaining high-performing IP services such as data, video, and voice over IP. This book provides a concise introduction to the three core IPAM networking technologies—IPv4 and IPv6 addressing, Dynamic Host Configuration Protocol (DHCP), and Domain Name System (DNS)—as well as IPAM practice and techniques needed to manage them cohesively. The book begins with a basic overview of IP networking, including a discussion of protocol layering, addressing, and routing. After a review of the IPAM technologies, the book introduces the major components, motivation, benefits, and basic approaches of IPAM. Emphasizing the necessity of a disciplined «network management» approach to IPAM, the subsequent chapters enable you to: Understand IPAM practices, including managing your IP address inventory and tracking of address transactions (such as allocation and splitting address space, discovering network occupancy, and managing faults and performance) Weigh the costs and justifications for properly implementing an IPAM strategy Use various approaches to automating IPAM functions through workflow Learn about IPv4-IPv6 co-existence technologies and approaches Assess security issues with DHCP network access control approaches and DNS vulnerabilities and mitigation including DNSSEC Evaluate the business case for IPAM, which includes derivation of the business case cost basis, identification of savings when using an IP address management system, associated costs, and finally net results Introduction to IP Address Management concludes with a business case example, providing a real-world financial perspective of the costs and benefits of implementing an IP address management solution. No other book covers all these subjects cohesively from a network management perspective, which makes this volume imperative for manager-level networking professionals who need a broad understanding of both the technical and business aspects of IPAM. In addition, technologists interested in IP networking and address management will find this book valuable. To obtain a free copy of the IPAM Configuration Guide please send an email to: email@example.com