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| financial data quality management: A Primer in Financial Data Management Martijn Groot, 2017-05-10 A Primer in Financial Data Management describes concepts and methods, considering financial data management, not as a technological challenge, but as a key asset that underpins effective business management. This broad survey of data management in financial services discusses the data and process needs from the business user, client and regulatory perspectives. Its non-technical descriptions and insights can be used by readers with diverse interests across the financial services industry. The need has never been greater for skills, systems, and methodologies to manage information in financial markets. The volume of data, the diversity of sources, and the power of the tools to process it massively increased. Demands from business, customers, and regulators on transparency, safety, and above all, timely availability of high quality information for decision-making and reporting have grown in tandem, making this book a must read for those working in, or interested in, financial management. - Focuses on ways information management can fuel financial institutions' processes, including regulatory reporting, trade lifecycle management, and customer interaction - Covers recent regulatory and technological developments and their implications for optimal financial information management - Views data management from a supply chain perspective and discusses challenges and opportunities, including big data technologies and regulatory scrutiny |
| financial data quality management: Oracle Hyperion Financial Management Tips And Techniques Peter Fugere, 2011-10-22 Master Oracle Hyperion Financial Management Consolidate financial data and maintain a scalable compliance framework with expert instruction from an Oracle ACE. Oracle Hyperion Financial Management Tips & Techniques provides advanced, time-saving procedures not documented in user manuals or help files. Find out how to configure Oracle Hyperion Financial Management, import and reconcile data, deliver dynamic business reports, and automate administrative tasks. Stragegies for supporting, testing, and tuning your application are also covered in this comprehensive Oracle Press guide. Establish objectives and develop an effective rollout plan Set up and customize Oracle Hyperion Financial Management Create rules using VBScript and the Calculation Manager feature of Oracle Hyperion Foundation Services Load, test, and reconcile your data with Oracle Data Integrator and Oracle Hyperion Financial Data Quality Management Design, update, and distribute Web-based business reports Integrate content from Microsoft Excel, Word, and PowerPoint using SmartView Work with the Lifecycle Management feature of Oracle Hyperion Foundation Services Identify and resolve performance, design, and capacity problems |
| financial data quality management: Managing Data Integrity for Finance Jane Sarah Lat, 2024-01-31 Level up your career by learning best practices for managing the data quality and integrity of your financial data Key Features Accelerate data integrity management using artificial intelligence-powered solutions Learn how business intelligence tools, ledger databases, and database locks solve data integrity issues Find out how to detect fraudulent transactions affecting financial report integrity Book DescriptionData integrity management plays a critical role in the success and effectiveness of organizations trying to use financial and operational data to make business decisions. Unfortunately, there is a big gap between the analysis and management of finance data along with the proper implementation of complex data systems across various organizations. The first part of this book covers the important concepts for data quality and data integrity relevant to finance, data, and tech professionals. The second part then focuses on having you use several data tools and platforms to manage and resolve data integrity issues on financial data. The last part of this the book covers intermediate and advanced solutions, including managed cloud-based ledger databases, database locks, and artificial intelligence, to manage the integrity of financial data in systems and databases. After finishing this hands-on book, you will be able to solve various data integrity issues experienced by organizations globally.What you will learn Develop a customized financial data quality scorecard Utilize business intelligence tools to detect, manage, and resolve data integrity issues Find out how to use managed cloud-based ledger databases for financial data integrity Apply database locking techniques to prevent transaction integrity issues involving finance data Discover the methods to detect fraudulent transactions affecting financial report integrity Use artificial intelligence-powered solutions to resolve various data integrity issues and challenges Who this book is for This book is for financial analysts, technical leaders, and data professionals interested in learning practical strategies for managing data integrity and data quality using relevant frameworks and tools. A basic understanding of finance concepts, accounting, and data analysis is expected. Knowledge of finance management is not a prerequisite, but it’ll help you grasp the more advanced topics covered in this book. |
| financial data quality management: Look Smarter Than You Are with Essbase 11. 1. 2 Edward Roske, Tracy McMullen, Robert Gideon, 2015-04-03 Essbase is everywhere these days. To survive and be productive in the business world, you need to take control of Essbase. If you don't have time (and money in the budget) to go to a class, if you just want to learn at your own pace, or if you want the information not covered in classes, this book will show you the way. Whether you're a new admin building new applications or existing admin looking to learn about ASO, hybrid aggregation databases, or design and optimization best practices, this book will help you become a master of Essbase (fellow workers will look at you in sheer, dumbstruck awe). You will learn to: Use the basics of the Smart View Add-in to retrieve and analyze data Build aggregate storage option, block storage option, and hybrid aggregation databases Tune and optimize aggregate storage option, block storage option, and hybrid aggregation databases Administer Essbase databases Take advantage of all the new Essbase features including version 11.1.2. |
| financial data quality management: Strategic Financial Management Muhammad Ali, Leong Choi-Meng, Chin-Hong Puah, Syed Ali Raza, Premagowrie Sivanandan, 2024-10-25 Investigating theoretical frameworks, identifying problems, and discussing implications for managers, entrepreneurs, and policymakers, regulatory changes and compliance challenges are dissected in this book, providing a timely guide for managers to navigate the evolving regulatory landscape. |
| financial data quality management: Financial Management Challenges at the Department of Justice United States. Congress. House. Committee on Government Reform. Subcommittee on Government Management, Finance, and Accountability, 2005 |
| financial data quality management: Information Quality and Governance for Business Intelligence Yeoh, William, 2013-12-31 Business intelligence initiatives have been dominating the technology priority list of many organizations. However, the lack of effective information quality and governance strategies and policies has been meeting these initiatives with some challenges. Information Quality and Governance for Business Intelligence presents the latest exchange of academic research on all aspects of practicing and managing information using a multidisciplinary approach that examines its quality for organizational growth. This book is an essential reference tool for researchers, practitioners, and university students specializing in business intelligence, information quality, and information systems. |
| financial data quality management: Big Data, Cloud and Applications Youness Tabii, Mohamed Lazaar, Mohammed Al Achhab, Nourddine Enneya, 2018-08-13 This book constitutes the thoroughly refereed proceedings of the Third International Conference on Big Data, Cloud and Applications, BDCA 2018, held in Kenitra, Morocco, in April 2018.The 45 revised full papers presented in this book were carefully selected from 99 submissions with a thorough double-blind review process. They focus on the following topics: big data, cloud computing, machine learning, deep learning, data analysis, neural networks, information system and social media, image processing and applications, and natural language processing. |
| financial data quality management: Look Smarter Than You Are with Hyperion Planning 11.1.2: An End User's Guide Edward Roske, Tracy McMullen, 2013-04-25 How Can I Use Oracle Hyperion Planning to plan, budget and forecast? Oracle Hyperion Planning is the market leading budgeting and forecasting solution that provides powerful planning capabilities over the web and in Microsoft Excel. You want to plan faster and more accurately and you are sure Oracle Hyperion Planning is the answer. This book is your key to unlocking the world of Planning from an end user perspective, guiding you through the ins and outs of Planning on your quest to a better budgeting and forecasting process which in turn leads to better enterprise performance. You will learn: - What is Oracle Hyperion Planning and how to connect - All of the Planning end user features like supporting detail, comments, document attachments, adjusting, grid spreader and more - How to plan and build models in Microsoft Excel with Smart View - How to perform adhoc analysis over the web and in Excel - Steps to review and approve budgets through the approval process - What's new in 11.1.2.2 and 11.1.2.3 |
| financial data quality management: 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. |
| financial data quality management: Look Smarter Than You Are with Hyperion Planning: an Administrator's Guide Edward Roske, Tracy McMullen, 2010-07-12 Oracle Hyperion Planning is the market leading budgeting and forecasting solution that provides powerful planning capabilities over the web and in Microsoft Excel. You want to plan faster and more accurately and you are sure Oracle Hyperion Planning is the answer. This book is your key to unlocking the world of Planning from an administrator perspective, guiding you through the ins and outs of Planning on your quest for improved budgeting and forecasting.You will learn:'¢What is Oracle Hyperion Planning and how to connect'¢How to plan over the web'¢How to build a Planning application from start to finish'¢The steps to manage and administer Planning applications'¢Tips, tricks, and design best practices for Planning and its underlying Essbase databases |
| financial data quality management: The CIO's Guide to Oracle Products and Solutions Jessica Keyes, 2014-09-02 From operating systems to the cloud, Oracle's products and services are everywhere, and it has the market share to prove it. Given the share diversity of the Oracle product line, and the level of complexity of integration, management can be quite a daunting task.The CIO's Guide to Oracle Products and Solutions is the go-to guide for all things Orac |
| financial data quality management: Enterprise Data at Huawei Yun Ma, Hao Du, 2021-11-22 This book systematically introduces the data governance and digital transformation at Huawei, from the perspectives of technology, process, management, and so on. Huawei is a large global enterprise engaging in multiple types of business in over 170 countries and regions. Its differentiated operation is supported by an enterprise data foundation and corresponding data governance methods. With valuable experience, methodology, standards, solutions, and case studies on data governance and digital transformation, enterprise data at Huawei is ideal for readers to learn and apply, as well as to get an idea of the digital transformation journey at Huawei. This book is organized into four parts and ten chapters. Based on the understanding of “the cognitive world of machines,” the book proposes the prospects for the future of data governance, as well as the imaginations about AI-based governance, data sovereignty, and building a data ecosystem. |
| financial data quality management: Developing Essbase Applications Cameron Lackpour, 2012-06-13 If you love Essbase and hate seeing it misused, then this is the book for you. Written by 12 Essbase professionals that are either acknowledged Essbase gurus or certified Oracle ACEs, Developing Essbase Applications: Advanced Techniques for Finance and IT Professionals provides an unparalleled investigation and explanation of Essbase theory and bes |
| financial data quality management: Big Data Governance: Managing and Protecting Data Assets Michael Roberts, Big Data Governance: Managing and Protecting Data Assets offers a comprehensive exploration of the principles, practices, and strategies essential for governing vast volumes of data in the digital age. As organizations increasingly rely on big data to drive decision-making and innovation, effective governance becomes paramount to ensure data quality, security, and compliance. This book delves into key topics such as data governance frameworks, privacy regulations, risk management, and ethical considerations. Whether you're a data steward, IT manager, compliance officer, or business leader, this handbook equips you with the insights and tools to establish robust data governance frameworks and safeguard your organization's most valuable asset—its data. |
| financial data quality management: 200 Tips for Mastering Generative AI Rick Spair, In the rapidly evolving landscape of artificial intelligence, Generative AI stands out as a transformative force with the potential to revolutionize industries and reshape our understanding of creativity and automation. From its inception, Generative AI has captured the imagination of researchers, developers, and entrepreneurs, offering unprecedented capabilities in generating new data, simulating complex systems, and solving intricate problems that were once considered beyond the reach of machines. This book, 200 Tips for Mastering Generative AI, is a comprehensive guide designed to empower you with the knowledge and practical insights needed to harness the full potential of Generative AI. Whether you are a seasoned AI practitioner, a curious researcher, a forward-thinking entrepreneur, or a passionate enthusiast, this book provides valuable tips and strategies to navigate the vast and intricate world of Generative AI. We invite you to explore, experiment, and innovate with the knowledge you gain from this book. Together, we can unlock the full potential of Generative AI and shape a future where intelligent machines and human creativity coexist and collaborate in unprecedented ways. Welcome to 200 Tips for Mastering Generative AI. Your journey into the fascinating world of Generative AI begins here. |
| financial data quality management: Look Smarter Than You Are with Hyperion Planning 11.1.2: Creating Hyperion Planning Applications Edward Roske, Tracy McMullen, 2013-01-11 How do I build a Hyperion Planning application? Oracle Hyperion Planning is the market leading budgeting and forecasting solution that provides powerful planning capabilities over the web and in Microsoft Excel. You want to plan faster and more accurately and you are sure Oracle Hyperion Planning is the answer. This book is your key to unlocking the world of Planning from an administrator perspective, guiding you through the ins and outs of Planning of creating 11.1.2 Hyperion Planning applications. You will learn: -What is Oracle Hyperion Planning and how to connect -How to plan over the web -How to build a Planning application from start to finish -How to assign security for Planning applications -How to set up and use Approvals -All of the new 11.1.2.2 and 11.1.2.3 Hyperion Planning features For additional reading on Hyperion Planning, please check out Look Smarter Than You Are with Hyperion Planning 11.1.2: Advanced Hyperion Planning. |
| financial data quality management: Financial Management Excellence: Strategies for Sustainable Growth Dr Nidhi Srivastava, 2022-10-08 Achieve sustainable growth with excellence in financial management. This book covers essential strategies and practices for managing finances effectively, making it a valuable resource for financial professionals and business leaders. |
| financial data quality management: , |
| financial data quality management: Enterprise Design, Operations, and Computing. EDOC 2023 Workshops Tiago Prince Sales, |
| financial data quality management: Management of Data Quality in Enterprise Resource Planning Systems Michael Röthlin, 2010 Originally presented as the author's thesis (doctoral)--Universiteat Bern, 2010. |
| financial data quality management: Look Smarter Than You Are with Essbase System 9 Edward Roske, Tracy McMullen, 2008 Look Smarter Than You Are with Essbase System 9: The Complete Guide How Can I Make Better Use of Essbase? Essbase is everywhere these days. To survive and be productive in the business world, you need to take control of Essbase. If you don't have time (or money in the budget) to go to a class, if you just want to learn at your own pace, or if you want the information not covered in classes, this book will show you the way. Whether you're an end user looking to better analyze information or an admin building new applications, you will become a master of Essbase and your coworkers will look at you in sheere, dumbstruck awe. |
| financial data quality management: Recent Advancements in Computational Finance and Business Analytics Rangan Gupta, |
| financial data quality management: The 2013 International Conference on Management and Information Technology Alice Peng, 2013-11-20 The aims of CMIT2013 are to provide a platform for researchers, educators, engineers, and government officials involved in the general areas of management and Information Technology to disseminate their latest research results and exchange views on the fu ture research directions of these fields, to exchange management and information technology and integrate of their practice, application of the academic ideas, improve the academic depth of information technology and its application, provide an internation al communication platform for educational technology and scientific research for the world's universities, business intelligence engineering field experts, professionals, and business executives. The CMIT 2013 tends to collect the latest research results an d applications on management and information technology . It includes a selection of 125 papers from 781 papers submitted to the conference from universities and industries all over the world. All of accepted papers were subjected to strict peerreviewing b y two to four expert referees. The papers have been selected for this volume because of quality and the relevance to the conference. The conference is designed to stimulate the young minds including Research Scholars, Academicians, and Practitioners to co ntribute their ideas, thoughts and nobility in these two disciplines. |
| financial data quality management: Information Quality Management Latif Al-Hakim, 2007-01-01 Technologies such as the Internet and mobile commerce bring with them ubiquitous connectivity, real-time access, and overwhelming volumes of data and information. The growth of data warehouses and communication and information technologies has increased the need for high information quality management in organizations. Information Quality Management: Theory and Applications provides solutions to information quality problems becoming increasingly prevalent.Information Quality Management: Theory and Applications provides insights and support for professionals and researchers working in the field of information and knowledge management, information quality, practitioners and managers of manufacturing, and service industries concerned with the management of information. |
| financial data quality management: Built on Value Weiwei Huang, 2019-06-14 This book is open access under a CC BY-NC-ND 4.0 license. This book presents the concept of value as the central component to success and longevity of the global ICT industry player, Huawei. It provides examples of how Huawei focuses on customers to pursue sustainable and profitable growth rather than focusing on capital market valuation which is a familiar scenario among Western companies. It is the business departments that are the creators of value for Huawei, while the finance department is tasked to provide support and services to those business departments during the value creation process. The book illustrates how Huawei Finance sets rules, allocates resources, and builds centers of expertise all over the world to address future uncertainties. More than a decade ago Huawei dedicated seven years to implement the Integrated Financial Services (IFS) Transformation Program with the help of IBM consultants. This book also draws on the leading concepts and successful experience of the IFS Transformation Program. Huawei Finance adopts three types of centralized vertical management from the top down: treasury, accounting, and auditing. It does not transfer such central authority down to lower levels, but delegates all other authority to business organizations across all levels. This management model represents the focus of this book. Built on Value provides an overview of Huawei's finance management and will help academic researchers in Business/Management, as well as practitioners in industry, an accurate and in-depth understanding of Huawei as a company. |
| financial data quality management: Essbase for Mere Mortals: An Insider's Guide , |
| financial data quality management: Frontiers in Cyber Security Guangquan Xu, Kaitai Liang, Chunhua Su, 2020-11-05 This book constitutes the proceedings of the Third International Conference on Frontiers in Cyber Security, FCS 2020, held in Tianjin, China*, in November 2020. The 39 full papers along with the 10 short papers presented were carefully reviewed and selected from 143 submissions. The papers are organized in topical sections on: IoT security; artificial intelligence; blockchain; cyber-physical systems security; cryptography; database security; depth estimation; mobile security; network security; privacy; program analysis; quantum cryptography; steganography; web security. *The conference was held virtually due to the COVID-19 pandemic. |
| financial data quality management: Information Quality Richard Wang, Elizabeth M. Pierce, Stuart Madnick, Craig Fisher, 2014-12-18 Organizations today have access to vast stores of data that come in a wide variety of forms and may be stored in places ranging from file cabinets to databases, and from library shelves to the Internet. The enormous growth in the quantity of data, however, has brought with it growing problems with the quality of information, further complicated by the struggles many organizations are experiencing as they try to improve their systems for knowledge management and organizational memory. Failure to manage information properly, or inaccurate data, costs businesses billions of dollars each year. This volume presents cutting-edge research on information quality. Part I seeks to understand how data can be measured and evaluated for quality. Part II deals with the problem of ensuring quality while processing data into information a company can use. Part III presents case studies, while Part IV explores organizational issues related to information quality. Part V addresses issues in information quality education. |
| financial data quality management: Handbook of Financial Data and Risk Information II Margarita S. Brose, Mark D. Flood, Dilip Krishna, Bill Nichols, 2014-01-09 A comprehensive resource for understanding the issues involved in collecting, measuring and managing data in the financial services industry. |
| financial data quality management: Data Quality Management in the Data Age Haiyan Yu, |
| financial data quality management: Third validation compendium report Great Britain: National Audit Office, 2006-12-19 In 2004, the Government announced 110 Public Service Agreement (PSA) targets for 17 Departments covering the period 2005-08. PSA targets express the priority outcomes that Departments are seeking to achieve nationally and internationally, and cover key aspects of the Government's social, economic and environmental policy. Large sums of public money are devoted to the programmes designed to deliver them. This NAO report summarises the results of its examination of the data systems used by six government departments to monitor and report progress against their 2005-08 PSA targets, covering a total of 65 data systems. The six Departments are: the Cabinet Office, the Department for Culture, Media and Sport, the Department for Education and Skills, the Department for the Environment, Food and Rural Affairs, the Ministry of Defence and HM Treasury. Findings include that 75 per cent of the data systems used are broadly appropriate, but less than half of these were fully fit for purpose. Most required some action to strengthen measurement or reporting arrangements. A companion volume (HCP 127-II, session 2006-07, ISBN 0102944083) is available separately which contains the NAO's detailed findings. |
| financial data quality management: Sensor Systems and Software Michele Magno, Fabien Ferrero, Vedran Bilas, 2017-07-18 This book constitutes the thoroughly refereed post-conference proceedings of the 7th EAI International Conference on Sensor Systems and Software, S-Cube 2016, held in Sophia Antipolis, Nice, France, in December 2016. The 15 revised full papers and 5 invited papers cover technologies for wireless sensor networks, smart city and industry 4.0 applications, and smart sensing. |
| financial data quality management: Business Information Systems Workshops Witold Abramowicz, Gary Klein, 2020-11-11 This book constitutes revised papers from the five workshops which were held during June 2020 at the 23rd International Conference on Business Information Systems, BIS 2020. The conference was planned to take place in Colorado Springs, CO, USA. Due to the COVID-19 pandemic it changed to a virtual format. There was a total of 54 submissions to all workshops of which 26 papers were accepted for publication. The workshops included in this volume are: BITA 2020: 11th Workshop on Business and IT Alignment BSCT 2020: 3rd Workshop on Blockchain and Smart Contract Technologies DigEX 2020: 2nd International Workshop on transforming the Digital Customer Experience iCRM 2020: 5th International Workshop on Intelligent Data Analysis in Integrated Social CRM QOD 2020: 3rd Workshop on Quality of Open Data |
| financial data quality management: Look Smarter Than You Are with Essbase - An End User's Guide Edward Roske, Tracy McMullen, 2008-06-01 How Can I Use Essbase to Analyze Data? With millions of users world-wide, Essbase seems to be everywhere these days and now it's a part of your life. You want to slice and dice data, analyze information, and make highly formatted spreadsheet retrievals. You're sure Essbase is the answer and thank goodness your boss bought copies of this book for your entire department! This book is your key to unlocking the world of analysis through Essbase. You will learn: [ How to connect to Essbase databases and retrieve data [ What is multi-dimensionality and why should you care? [ The basics of Essbases end-user add-ins for adhoc analysis [ Steps to creating highly formatted reports and templates that you can use month after month [ Creation and saving of advanced analytic queries using the query designers |
| financial data quality management: Meeting the Challenges of Data Quality Management Laura Sebastian-Coleman, 2022-01-25 Meeting the Challenges of Data Quality Management outlines the foundational concepts of data quality management and its challenges. The book enables data management professionals to help their organizations get more value from data by addressing the five challenges of data quality management: the meaning challenge (recognizing how data represents reality), the process/quality challenge (creating high-quality data by design), the people challenge (building data literacy), the technical challenge (enabling organizational data to be accessed and used, as well as protected), and the accountability challenge (ensuring organizational leadership treats data as an asset). Organizations that fail to meet these challenges get less value from their data than organizations that address them directly. The book describes core data quality management capabilities and introduces new and experienced DQ practitioners to practical techniques for getting value from activities such as data profiling, DQ monitoring and DQ reporting. It extends these ideas to the management of data quality within big data environments. This book will appeal to data quality and data management professionals, especially those involved with data governance, across a wide range of industries, as well as academic and government organizations. Readership extends to people higher up the organizational ladder (chief data officers, data strategists, analytics leaders) and in different parts of the organization (finance professionals, operations managers, IT leaders) who want to leverage their data and their organizational capabilities (people, processes, technology) to drive value and gain competitive advantage. This will be a key reference for graduate students in computer science programs which normally have a limited focus on the data itself and where data quality management is an often-overlooked aspect of data management courses. - Describes the importance of high-quality data to organizations wanting to leverage their data and, more generally, to people living in today's digitally interconnected world - Explores the five challenges in relation to organizational data, including Big Data, and proposes approaches to meeting them - Clarifies how to apply the core capabilities required for an effective data quality management program (data standards definition, data quality assessment, monitoring and reporting, issue management, and improvement) as both stand-alone processes and as integral components of projects and operations - Provides Data Quality practitioners with ways to communicate consistently with stakeholders |
| financial data quality management: PROCEEDINGS OF THE 2024 INTERNATIONAL CONFERENCE ON APPLIED ECONOMICS, MANAGEMENT SCIENCE AND SOCIAL DEVELOPMENT (AEMSS 2024) T. RAMAYAH; PUI MUN LEE; EDWARD H. K. NG., 2024 |
| financial data quality management: Manufacturing In The Era Of 4th Industrial Revolution: A World Scientific Reference (In 3 Volumes) , 2021-01-13 The era of the fourth industrial revolution has fundamentally transformed the manufacturing landscape. Products are getting increasingly complex and customers expect a higher level of customization and quality. Manufacturing in the Era of 4th Industrial Revolution explores three technologies that are the building blocks of the next-generation advanced manufacturing.The first technology covered in Volume 1 is Additive Manufacturing (AM). AM has emerged as a very popular manufacturing process. The most common form of AM is referred to as 'three-dimensional (3D) printing'. Overall, the revolution of additive manufacturing has led to many opportunities in fabricating complex, customized, and novel products. As the number of printable materials increases and AM processes evolve, manufacturing capabilities for future engineering systems will expand rapidly, resulting in a completely new paradigm for solving a myriad of global problems.The second technology is industrial robots, which is covered in Volume 2 on Robotics. Traditionally, industrial robots have been used on mass production lines, where the same manufacturing operation is repeated many times. Recent advances in human-safe industrial robots present an opportunity for creating hybrid work cells, where humans and robots can collaborate in close physical proximities. This Cobots, or collaborative robots, has opened up to opportunity for humans and robots to work more closely together. Recent advances in artificial intelligence are striving to make industrial robots more agile, with the ability to adapt to changing environments and tasks. Additionally, recent advances in force and tactile sensing enable robots to be used in complex manufacturing tasks. These new capabilities are expanding the role of robotics in manufacturing operations and leading to significant growth in the industrial robotics area.The third technology covered in Volume 3 is augmented and virtual reality. Augmented and virtual reality (AR/VR) technologies are being leveraged by the manufacturing community to improve operations in a wide variety of ways. Traditional applications have included operator training and design visualization, with more recent applications including interactive design and manufacturing planning, human and robot interactions, ergonomic analysis, information and knowledge capture, and manufacturing simulation. The advent of low-cost solutions in these areas is accepted to accelerate the rate of adoption of these technologies in the manufacturing and related sectors.Consisting of chapters by leading experts in the world, Manufacturing in the Era of 4th Industrial Revolution provides a reference set for supporting graduate programs in the advanced manufacturing area. |
| financial data quality management: Multi-Domain Master Data Management Mark Allen, Dalton Cervo, 2015-03-21 Multi-Domain Master Data Management delivers practical guidance and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to you in the only reference you need to help your organization take master data management to the next level by incorporating it across multiple domains. Written in a business friendly style with sufficient program planning guidance, this book covers a comprehensive set of topics and advanced strategies centered on the key MDM disciplines of Data Governance, Data Stewardship, Data Quality Management, Metadata Management, and Data Integration. - Provides a logical order toward planning, implementation, and ongoing management of multi-domain MDM from a program manager and data steward perspective. - Provides detailed guidance, examples and illustrations for MDM practitioners to apply these insights to their strategies, plans, and processes. - Covers advanced MDM strategy and instruction aimed at improving data quality management, lowering data maintenance costs, and reducing corporate risks by applying consistent enterprise-wide practices for the management and control of master data. |
| financial data quality management: Encyclopedia of Database Technologies and Applications Rivero, Laura C., Doorn, Jorge Horacio, Ferraggine, Viviana E., 2005-06-30 Addresses the evolution of database management, technologies and applications along with the progress and endeavors of new research areas.--P. xiii. |
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