Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition

Management Information Systems provides comprehensive and integrative coverage of essential new technologies, information system applications, and their impact on business models and managerial decision-making in an exciting and interactive manner. The twelfth edition focuses on the major changes that have been made in information technology over the past two years, and includes new opening, closing, and Interactive Session cases.

Warehouses are an integral link in the modern supply chain, ensuring that the correct product is delivered in the right quantity, in good condition, at the required time, and at minimal cost: in effect, the perfect order. The effective management of warehouses is vital in minimizing costs and ensuring the efficient operation of any supply chain. Warehouse Management is a complete guide to best practice in warehouse operations. Covering everything from the latest technological advances to current environmental issues, this book provides an indispensable companion to the modern warehouse. Supported by case studies, the text considers many aspects of warehouse management, including: cost reduction productivity people management warehouse operations With helpful tools, hints and up-to-date information, Warehouse Management provides an invaluable resource for anyone looking to reduce costs and boost productivity.

This book contains the proceedings of the International Conference on Industrial Design and Environmental Engineering (IDEE 2023) held via the hybrid form in Zhengzhou, China from November 24th to 26th, 2023. The specific topics covered in this conference include innovative design, multimedia applied art design, environmental analysis and monitoring, pollution control programs, hydrology and water resources engineering, urban and regional planning, global climate change and international carbon emission reduction cooperation. The conference aims to bring together various professionals from the scientific community to foster connections between science, technology, and industry, and provide a platform for exploring fundamental issues and new applications in related fields. We hope that the scientific attitudes and skills developed through research will encourage scholars worldwide to contribute to the development of knowledge generated by research. Finally, we would like to express our gratitude to the conference chair, publication chairs, technical program committee chairs, local organizing chairs, program committee chairs, conference secretariat, and conference sponsors for their financial support, which made the successful organization of IDEE 2023 possible. We hope that this conference will continue to be held in the coming years, publishing more insightful articles with inspiring research. We would also like to thank the invited speakers for their valuable contributions and for sharing their perspectives during their speeches.

This book vividly illustrates all the promising and potential machine learning (ML) and deep learning (DL) algorithms through a host of real-world and real-time business use cases. Machines and devices can be empowered to self-learn and exhibit intelligent behavior. Also, Big Data combined with real-time and runtime data can lead to personalized, prognostic, predictive, and prescriptive insights. This book examines the following topics: Cognitive machines and devices Cyber physical systems (CPS) The Internet of Things (IoT) and industrial use cases Industry 4.0 for smarter manufacturing Predictive and prescriptive insights for smarter systems Machine vision and intelligence Natural interfaces K-means clustering algorithm Support vector machine (SVM) algorithm A priori algorithms Linear and logistic regression Applied Learning Algorithms for Intelligent IoT clearly articulates ML and DL algorithms that can be used to unearth predictive and prescriptive insights out of Big Data. Transforming raw data into information and relevant knowledge is gaining prominence with the availability of data processing and mining, analytics algorithms, platforms, frameworks, and other accelerators discussed in the book. Now, with the emergence of machine learning algorithms, the field of data analytics is bound to reach new heights. This book will serve as a comprehensive guide for AI researchers, faculty members, and IT professionals. Every chapter will discuss one ML algorithm, its origin, challenges, and benefits, as well as a sample industry use case for explaining the algorithm in detail. The book’s detailed and deeper dive into ML and DL algorithms using a practical use case can foster innovative research.

Buying and selling self-storage can be a win-win-win prospect for all parties. Self-storage has become a household name in the past few years, not only on TV and to the general American public, but to Wall Street and private investors throughout the United States and abroad. This boom in demand for self-storage ownership has erupted the transactional volume--with facilities being sold for record prices and in record time. As such, we've also seen a development boom over the past few years, with investors trying to ride the storage wave and enjoy the wonderful profits that self-storage has historically delivered time and time again. Navigating this new landscape in the industry can be challenging, to say the least. With the entrance of a plethora of new capital and new competition comes a very sophisticated market with highly educated investors and big firms going head to head with the single owner-operators throughout the United States. This competitive environment and massive demand for self-storage creates an optimal sellers' market, one that can be extremely profitable with the right help. The Sexy Side Of Self-Storage was written to help any facility owner in the self-storage industry--but particularly the single owner-operator--maximize the value of their self-storage investment at sale.