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"Whether you are a subject matter expert who occasionally takes on a trainer role, a trainer who wants to build on solid presentation skills, or anywhere in between, This book will help you create supportive and effective learning and is designed to improve your facilitation proficiency so you can give face-to-face as well as online and virtual classroom learners your best. It offers practical examples, worksheets, and tools that make workplace learning easy and rewarding. You'll walk away with proven facilitation techniques and a deeper understanding of how to manage difficult participants and use media to support learning. --"

"Summary: Nonprofits are communicating more often and in more ways than ever before . . .but is anyone paying attention? In her follow-up to The Nonprofit Marketing Guide: High-Impact, Low-Cost Ways to Build Support for Your Good Cause, Kivi Leroux Miller shows you how to design and implement a content marketing strategy that will attract people to your cause, rather than begging for their attention or interrupting them with your communications. Youll learn how to plan, create, share, and manage relevant and valuable content that inspires and motivates people to support your nonprofit in many "

"[This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. , This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. ]"

"Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors’ tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, big data is belittled, projects flounder, are late and go over budget. Business intelligence guidebook : from data integration to analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers.After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget, turning the deluge of data into actionable information that fuels business knowledge. Finally, you’ll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success."

"Managing extreme financial risk addresses the need for better management strategies in light of increased market risk and volatility in financial institutions' revenue models. Top officials from the financial and regulatory industries point to real corporate issues, showing how institutions react to financial crises. From first-hand experiences, they explain how effective sustainability management does not just prevent being blindsided; it also leads to proactive solutions that enhance an institution's strength to weather a sudden financial crisis, add significant shareholder value, and reduce systemic risk. Readable, coherent, and logical, managing extreme financial risk shows how extreme risk needs to be handled when the cost of being wrong means the difference between life and death of the institution."

"Performance measurement and management for engineers introduces key concepts in finance, accounting, and management to project managers who have engineering backgrounds. It focuses these basic concepts on issues of measuring and managing enterprise value. Thus, after defining enterprise value, the book begins by explaining the ways and means of measurement. It then takes up financial measurement, describing and analyzing the typologies of financial indicators while illustrating their advantages and disadvantages. After focusing on measuring enterprise value, the second section takes up managing that value. Like the first, it pursues a double view: using indicators for internal control while employing them to analyze other companies. If engineering project managers possess a source of quantitative and qualitative information about business management."

"Social data analytics is the first practical guide for professionals who want to employ social data for analytics and business intelligence (BI). This book provides a comprehensive overview of the technologies and platforms and shows you how to access and analyze the data. You'll explore the five major types of social data and learn from cases and platform examples to help you make the most of sentiment, behavioral, social graph, location, and rich media data. A four-step approach to the social BI process will help you access, evaluate, collaborate, and share social data with ease."