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Complete Guide to Federal and State Garnishment provides much-needed clarity when the federal and state laws appear to conflict. You'll find plain-English explanations of the laws and how they interact, as well as the specific steps you and your staff need to take to respond to the order properly. Numerous detailed examples and mathematical calculations make it easy to apply the law under different scenarios. Written by Amorette Nelson Bryant, who was recently appointed by the Uniform Law Commission as an observer for the Drafting Committee on a Wage Garnishment Act and was a past chair of both the APA GATF Child Support Subcommittee and Garnishment Subcommittee, Complete Guide to Federal and State Garnishment brings the payroll professional up-to-date on the latest federal and state laws and regulations affecting this ever-changing area. It is your one-stop source for answers to critical questions, such as: Does the amount exempt from garnishment change when the minimum wage goes up? How do I determine the wages to which the garnishment applies? If an employee is subject to more than one garnishment, which has priority? Which state's rules do I use when I receive a child support order sent from another state? State or federal law - which applies for creditor garnishment and support? Are there alternatives to remitting withheld child support via EFT/EDI? How do I handle garnishments when employees are paid a draw against salary? Previous Edition: Complete Guide to Federal and State Garnishment, 2019 Edition, ISBN 9781454899921
The Complete Guide to Human Resources and the Law will help you navigate complex and potentially costly Human Resources issues. You'll know what to do (and what not to do) to avoid costly mistakes or oversights, confront HR problems - legally and effectively - and understand the rules. The Complete Guide to Human Resources and the Law offers fast, dependable, plain English legal guidance for HR-related situations from ADA accommodation, diversity training, and privacy issues to hiring and termination, employee benefit plans, compensation, and recordkeeping. It brings you the most up-to-date information as well as practical tips and checklists in a well-organized, easy-to-use resource. Previous Edition: Complete Guide to Human Resources and the Law, 2018 Edition ISBN 9781454899945
A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin
Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today's data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization's standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. - Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach - Contains real examples from around the world, gleaned from the author's consulting practice and from those who implemented based on her training courses and the earlier edition of the book - Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices - A companion Web site includes links to numerous data quality resources, including many of the templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online
A Complete Data Analytics Guide for Learners and Professionals. KEY FEATURES ● Learn Big Data, Hadoop Architecture, HBase, Hive and NoSQL Database. ● Dive into Machine Learning, its tools, and applications. ● Coverage of applications of Big Data, Data Analysis, and Business Intelligence. DESCRIPTION These days critical problem solving related to data and data sciences is in demand. Professionals who can solve real data science problems using data science tools are in demand. The book “Data Analytics: Principles, Tools, and Practices” can be considered a handbook or a guide for professionals who want to start their journey in the field of data science. The journey starts with the introduction of DBMS, RDBMS, NoSQL, and DocumentDB. The book introduces the essentials of data science and the modern ecosystem, including the important steps such as data ingestion, data munging, and visualization. The book covers the different types of analysis, different Hadoop ecosystem tools like Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. It also includes the different machine learning techniques that are useful for data analytics and how to visualize data with different graphs and charts. The book discusses useful tools and approaches for data analytics, supported by concrete code examples. After reading this book, you will be motivated to explore real data analytics and make use of the acquired knowledge on databases, BI/DW, data visualization, Big Data tools, and statistical science. WHAT YOU WILL LEARN ● Familiarize yourself with Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. ● Learn to manage data warehousing with real time transaction processing. ● Explore various machine learning techniques that apply to data analytics. ● Learn how to visualize data using a variety of graphs and charts using real-world examples from the industry. ● Acquaint yourself with Big Data tools and statistical techniques for machine learning. WHO THIS BOOK IS FOR IT graduates, data engineers and entry-level professionals who have a basic understanding of the tools and techniques but want to learn more about how they fit into a broader context are encouraged to read this book. TABLE OF CONTENTS 1. Database Management System 2. Online Transaction Processing and Data Warehouse 3. Business Intelligence and its deeper dynamics 4. Introduction to Data Visualization 5. Advanced Data Visualization 6. Introduction to Big Data and Hadoop 7. Application of Big Data Real Use Cases 8. Application of Big Data 9. Introduction to Machine Learning 10. Advanced Concepts to Machine Learning 11. Application of Machine Learning
As your company moves data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure you meet compliance. Data governance incorporates the ways that people, processes, and technology work together to support business efficiency. With this practical guide, chief information, data, and security officers will learn how to effectively implement and scale data governance throughout their organizations. You'll explore how to create a strategy and tooling to support the democratization of data and governance principles. Through good data governance, you can inspire customer trust, enable your organization to extract more value from data, and generate more-competitive offerings and improvements in customer experience. This book shows you how. Enable auditable legal and regulatory compliance with defined and agreed-upon data policies Employ better risk management Establish control and maintain visibility into your company's data assets, providing a competitive advantage Drive top-line revenue and cost savings when developing new products and services Implement your organization's people, processes, and tools to operationalize data trustworthiness.
Equip yourself to manage, motivate, compensate, and reward everyone in this workplace revolution The future of work is here. From the shift to Millennials and Gen Z in the workforce to the advent of the Fourth Industrial Revolution and the Gig Economy, the world of work and rewards has significantly changed since the initial WorldatWork Handbook was published. Human resources and total rewards professionals need tools to equip them to manage a changing workforce. This completely revised second edition addresses the challenging and disruptive issues facing employers today and tomorrow. The WorldatWork Handbook of Total Rewards is the definitive authority on compensation and rewards from the leading global nonprofit organizations for professionals who are engaged in the critically important practice of total rewards. This book is a go-to resource for all business professionals and leaders who reward and create productive, committed and inspired workforces worldwide. Readers will learn the basics of rewards, along with a deep dive and high-level view of how rewards programs enable organizations to deliver on their brand promises and perform at their optimal level. Gain a thorough understanding of compensation and benefits, along with employee well-being, development, and recognition, all updated to address the realities of today’s workplace. Understand why the Millennial and Gen Z workforce requires a different value proposition, and how to meet their needs. Discover the tools and techniques you need to help you reskill and become a highly valued workforce contributor and leader in the digital era. Learn how to attract, retain, and engage talent by building a healthy workplace culture and employing unique incentives that drive high performance and loyalty. Technical enough for specialists but broad in scope for managers and HR generalists, this well-rounded resource belongs on the desk of anyone interested in organizational effectiveness. An indispensable tool for understanding and implementing the total rewards concept, The WorldatWork Handbook of Total Rewards, Second Edition is the key to designing programs and practices that ensure employee engagement and organizational success.
SAFETY AND HEALTH FOR ENGINEERS A comprehensive resource for making products, facilities, processes, and operations safe for workers, users, and the public Ensuring the health and safety of individuals in the workplace is vital on an interpersonal level but is also crucial to limiting the liability of companies in the event of an onsite injury. The Bureau of Labor Statistics reported over 4,700 fatal work injuries in the United States in 2020, most frequently in transportation-related incidents. The same year, approximately 2.7 million workplace injuries and illnesses were reported by private industry employers. According to the National Safety Council, the cost in lost wages, productivity, medical and administrative costs is close to 1.2 trillion dollars in the US alone. It is imperative—by law and ethics—for engineers and safety and health professionals to drive down these statistics by creating a safe workplace and safe products, as well as maintaining a safe environment. Safety and Health for Engineers is considered the gold standard for engineers in all specialties, teaching an understanding of many components necessary to achieve safe workplaces, products, facilities, and methods to secure safety for workers, users, and the public. Each chapter offers information relevant to help safety professionals and engineers in the achievement of the first canon of professional ethics: to protect the health, safety, and welfare of the public. The textbook examines the fundamentals of safety, legal aspects, hazard recognition and control, the human element, and techniques to manage safety decisions. In doing so, it covers the primary safety essentials necessary for certification examinations for practitioners. Readers of the fourth edition of Safety and Health for Engineers readers will also find: Updates to all chapters, informed by research and references gathered since the last publication The most up-to-date information on current policy, certifications, regulations, agency standards, and the impact of new technologies, such as wearable technology, automation in transportation, and artificial intelligence New international information, including U.S. and foreign standards agencies, professional societies, and other organizations worldwide Expanded sections with real-world applications, exercises, and 164 case studies An extensive list of references to help readers find more detail on chapter contents A solution manual available to qualified instructors Safety and Health for Engineers is an ideal textbook for courses in safety engineering around the world in undergraduate or graduate studies, or in professional development learning. It also is a useful reference for professionals in engineering, safety, health, and associated fields who are preparing for credentialing examinations in safety and health.
Does the identification number 60 indicate a toxic substance or a flammable solid, in the molten state at an elevated temperature? Does the identification number 1035 indicate ethane or butane? What is the difference between natural gas transmission pipelines and natural gas distribution pipelines? If you came upon an overturned truck on the highway that was leaking, would you be able to identify if it was hazardous and know what steps to take? Questions like these and more are answered in the Emergency Response Guidebook. Learn how to identify symbols for and vehicles carrying toxic, flammable, explosive, radioactive, or otherwise harmful substances and how to respond once an incident involving those substances has been identified. Always be prepared in situations that are unfamiliar and dangerous and know how to rectify them. Keeping this guide around at all times will ensure that, if you were to come upon a transportation situation involving hazardous substances or dangerous goods, you will be able to help keep others and yourself out of danger. With color-coded pages for quick and easy reference, this is the official manual used by first responders in the United States and Canada for transportation incidents involving dangerous goods or hazardous materials.
This book offers a comprehensive collection of research articles that utilize data—in particular large data sets—in modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid.