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Author: Rick Spair Publisher: Rick Spair ISBN: Category : Computers Languages : en Pages : 149
Book Description
The world of document management is evolving rapidly, and organizations are increasingly turning to Intelligent Document Processing (IDP) to streamline their document management processes. This comprehensive guide serves as a valuable resource for individuals and organizations embarking on their IDP journey. It offers a step-by-step approach, practical tips, and best practices to help readers successfully implement IDP and achieve significant improvements in efficiency, accuracy, and cost savings. In today's digital age, the volume and complexity of documents continue to grow exponentially, posing significant challenges for organizations across industries. Traditional manual document management processes are time-consuming, error-prone, and resource-intensive, leading to inefficiencies and missed opportunities. However, the advent of Intelligent Document Processing (IDP) presents a game-changing solution. Intelligent Document Processing combines the power of artificial intelligence, machine learning, and automation technologies to extract and process data from unstructured documents swiftly and accurately. By automating manual tasks, organizations can enhance productivity, improve data accuracy, and optimize their document management workflows. This guide serves as a roadmap for readers looking to harness the potential of IDP and transform their document management practices. The chapters of this guide take readers on a comprehensive journey through the world of IDP. It begins with an introduction to document management and the concept of Intelligent Document Processing. Readers will gain a clear understanding of the benefits and importance of implementing IDP in their organizations. The guide then delves into the key aspects of implementing IDP. It covers topics such as assessing document management needs, identifying document types and formats, analyzing document volume and complexity, and evaluating existing document management processes. These chapters provide practical insights, tips, and strategies to help readers assess their current state and identify areas for improvement. As the journey progresses, the guide dives into creating an IDP strategy, including setting clear goals and objectives, selecting the right IDP solution, and defining key performance indicators (KPIs). It emphasizes the importance of customization and adaptation to align with specific organizational needs and goals. The guide further explores preparing documents for IDP, including standardizing formats and layouts, optimizing image quality and resolution, and implementing document classification and indexing. It provides detailed guidance on leveraging intelligent capture technologies, extracting data from structured and unstructured documents, and validating and verifying extracted data. The chapters also cover crucial aspects such as integrating IDP with existing systems, monitoring and measuring IDP performance, change management, and user adoption. They address data security and compliance requirements, as well as provide real-world case studies and success stories to inspire and educate readers. Throughout the guide, readers will find tips, recommendations, and best practices from industry leaders who have successfully implemented IDP. These insights serve as valuable lessons learned and provide practical guidance for readers as they embark on their IDP journey. In conclusion, this comprehensive guide equips readers with the knowledge and tools needed to implement Intelligent Document Processing successfully. By following the chapters, tips, recommendations, and strategies outlined in this guide, organizations can streamline their document management processes, achieve significant improvements in efficiency and accuracy, and drive tangible business outcomes. The IDP journey begins here, offering endless possibilities for optimizing document management in the digital era.
Author: Rick Spair Publisher: Rick Spair ISBN: Category : Computers Languages : en Pages : 149
Book Description
The world of document management is evolving rapidly, and organizations are increasingly turning to Intelligent Document Processing (IDP) to streamline their document management processes. This comprehensive guide serves as a valuable resource for individuals and organizations embarking on their IDP journey. It offers a step-by-step approach, practical tips, and best practices to help readers successfully implement IDP and achieve significant improvements in efficiency, accuracy, and cost savings. In today's digital age, the volume and complexity of documents continue to grow exponentially, posing significant challenges for organizations across industries. Traditional manual document management processes are time-consuming, error-prone, and resource-intensive, leading to inefficiencies and missed opportunities. However, the advent of Intelligent Document Processing (IDP) presents a game-changing solution. Intelligent Document Processing combines the power of artificial intelligence, machine learning, and automation technologies to extract and process data from unstructured documents swiftly and accurately. By automating manual tasks, organizations can enhance productivity, improve data accuracy, and optimize their document management workflows. This guide serves as a roadmap for readers looking to harness the potential of IDP and transform their document management practices. The chapters of this guide take readers on a comprehensive journey through the world of IDP. It begins with an introduction to document management and the concept of Intelligent Document Processing. Readers will gain a clear understanding of the benefits and importance of implementing IDP in their organizations. The guide then delves into the key aspects of implementing IDP. It covers topics such as assessing document management needs, identifying document types and formats, analyzing document volume and complexity, and evaluating existing document management processes. These chapters provide practical insights, tips, and strategies to help readers assess their current state and identify areas for improvement. As the journey progresses, the guide dives into creating an IDP strategy, including setting clear goals and objectives, selecting the right IDP solution, and defining key performance indicators (KPIs). It emphasizes the importance of customization and adaptation to align with specific organizational needs and goals. The guide further explores preparing documents for IDP, including standardizing formats and layouts, optimizing image quality and resolution, and implementing document classification and indexing. It provides detailed guidance on leveraging intelligent capture technologies, extracting data from structured and unstructured documents, and validating and verifying extracted data. The chapters also cover crucial aspects such as integrating IDP with existing systems, monitoring and measuring IDP performance, change management, and user adoption. They address data security and compliance requirements, as well as provide real-world case studies and success stories to inspire and educate readers. Throughout the guide, readers will find tips, recommendations, and best practices from industry leaders who have successfully implemented IDP. These insights serve as valuable lessons learned and provide practical guidance for readers as they embark on their IDP journey. In conclusion, this comprehensive guide equips readers with the knowledge and tools needed to implement Intelligent Document Processing successfully. By following the chapters, tips, recommendations, and strategies outlined in this guide, organizations can streamline their document management processes, achieve significant improvements in efficiency and accuracy, and drive tangible business outcomes. The IDP journey begins here, offering endless possibilities for optimizing document management in the digital era.
Author: Rick Spair Publisher: Rick Spair ISBN: Category : Technology & Engineering Languages : en Pages : 245
Book Description
Welcome to the Comprehensive Guide to Robotic Process Automation (RPA). In today's rapidly evolving digital landscape, organizations are increasingly turning to automation technologies to streamline processes, improve efficiency, and drive digital transformation. Among these technologies, Robotic Process Automation (RPA) stands out as a powerful tool for automating repetitive, rule-based tasks, freeing up human resources to focus on more strategic and value-added activities. This comprehensive guide aims to provide you with a deep understanding of RPA and equip you with the knowledge and strategies needed for successful RPA implementation. Whether you are a business leader, an IT professional, or an individual looking to explore the world of automation, this guide will serve as a valuable resource to navigate the complexities of RPA. In this guide, we will start by laying the foundation with an introduction to RPA, its benefits, and common misconceptions. We will then guide you through the process of assessing process suitability, selecting the right RPA tool, and building a strong foundation for RPA implementation. You will learn about establishing a dedicated RPA team, developing a roadmap, and setting realistic goals and expectations. As we delve into the core chapters, we will explore RPA design principles, process flow, decision points, and efficient automation workflows. We will address important considerations such as error handling and exception management, data and system integration, and managing security and access controls. Furthermore, this guide will provide insights into RPA implementation best practices, including creating reusable automation components, ensuring version control and documentation, and implementing proper testing and debugging processes. We will also explore the crucial aspects of governance, control, change management, and the role of RPA in business process reengineering. To enhance your understanding of RPA, we will delve into advanced topics such as cognitive automation, artificial intelligence (AI) integration, and leveraging machine learning and natural language processing capabilities. We will discuss scaling RPA implementations, managing multiple automation projects, and overcoming challenges in large-scale deployments. Throughout this guide, we will share real-world case studies, highlighting successful RPA implementations and extracting key learnings from each. These case studies will provide practical insights into how organizations have leveraged RPA to transform their operations, achieve cost savings, and enhance customer experiences. Lastly, we will explore the future of RPA and the emerging trends that will shape the landscape of automation. We will discuss evolving capabilities, the impact of AI and machine learning on RPA, and predictions for the future of automation. With each chapter, you will find tips, recommendations, and strategies to address common challenges, mitigate risks, and drive successful RPA adoption within your organization. We understand that every organization is unique, and the journey to RPA implementation will vary. However, by following the guidance provided in this guide, you will be equipped with the necessary knowledge and tools to embark on a successful RPA journey. We hope that this comprehensive guide serves as a valuable resource and reference throughout your RPA implementation. So let's dive in and unlock the transformative power of Robotic Process Automation!
Author: Matt Calkins Publisher: Bookbaby ISBN: 9781735732909 Category : Languages : en Pages : 166
Book Description
HYPERAUTOMATION is a collection of expert essays on low-code development and the future of business process automation. In each chapter, an academic, analyst, implementer, or end-user examines different aspects of low-code and automation in the enterprise, clarifying both value and barriers through personal experiences and insights. With contributions from: Dr. George Westerman, MIT - Neil Ward-Dutton, IDC - Lakshmi N, Tata Consultancy Services - Sidney Fernandes & Alice Wei, University of South Florida - Lisa Heneghan, KPMG - Chris Skinner, FinTech expert - John R. Rymer, Forrester (Emeritus) - Isaac Sacolick, StarCIO - Darren Blake, Bexley Neighbourhood Care - Rob Galbraith, InsureTech expert - Ron Tolido, Capgemini - Michael Beckley, Appian All proceeds from the sale of this book will be donated to Black Girls Code, an organization providing young girls of color opportunities to learn in-demand skills in technology and computer programming.
Author: Craig Le Clair Publisher: ISBN: 9781097365746 Category : Languages : en Pages : 131
Book Description
If you watched Super Bowl LIII in 2019, you saw no fewer than 10 commercials featuring robots. They were eating hot dogs at baseball games and crashing down roadways, shiny heads glinting in the sun. But these aren't the robots that will take the most jobs. Software running in obscure data centers that no one will ever see will replace or transform the jobs of cubicle workers, coordinators, and even knowledge workers. This book tells you about them, what jobs they'll take and when, and what we can do about it. Interviews with everyday workers bring the unvarnished reality of advancing automation, with all its ragged edges, to life. An actionable future-of-work model can prepare businesses, governments, and individuals for a rapidly changing workplace.
Author: Sk Md Obaidullah Publisher: CRC Press ISBN: 100073983X Category : Computers Languages : en Pages : 154
Book Description
Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: · The role of AI for document image analysis · Optical character recognition · Machine learning algorithms for document analysis · Extreme learning machines and their applications · Mathematical foundation for Web text document analysis · Social media data analysis · Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.
Author: Vadim V. Strijov Publisher: Springer Nature ISBN: 3030354008 Category : Computers Languages : en Pages : 178
Book Description
This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Processing, IDP 2016, held in Barcelona, Spain, in October 2016. The 11 revised full papers were carefully reviewed and selected from 52 submissions. The papers of this volume are organized in topical sections on machine learning theory with applications; intelligent data processing in life and social sciences; morphological and technological approaches to image analysis.
Author: Vincent Rainardi Publisher: Apress ISBN: 1430205288 Category : Computers Languages : en Pages : 526
Book Description
Here is the ideal field guide for data warehousing implementation. This book first teaches you how to build a data warehouse, including defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Coverage then explains how to populate the data warehouse and explores how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. It also details testing and how to administer data warehouse operation.
Author: Alan Rushton Publisher: Kogan Page Publishers ISBN: 9780749433659 Category : Business & Economics Languages : en Pages : 612
Book Description
Designed for students, young managers and seasoned practitioners alike, this handbook explains the nuts and bolts of the modern logistics and distribution world in plain language. Illustrated throughout, this second edition includes new chapters on areas previously not covered, such as: intermodal transport; benchmarking; environmental matters; and vehicle and depot security.
Author: National Academies of Sciences, Engineering, and Medicine Publisher: National Academies Press ISBN: 0309497299 Category : Education Languages : en Pages : 307
Book Description
Mentorship is a catalyst capable of unleashing one's potential for discovery, curiosity, and participation in STEMM and subsequently improving the training environment in which that STEMM potential is fostered. Mentoring relationships provide developmental spaces in which students' STEMM skills are honed and pathways into STEMM fields can be discovered. Because mentorship can be so influential in shaping the future STEMM workforce, its occurrence should not be left to chance or idiosyncratic implementation. There is a gap between what we know about effective mentoring and how it is practiced in higher education. The Science of Effective Mentorship in STEMM studies mentoring programs and practices at the undergraduate and graduate levels. It explores the importance of mentorship, the science of mentoring relationships, mentorship of underrepresented students in STEMM, mentorship structures and behaviors, and institutional cultures that support mentorship. This report and its complementary interactive guide present insights on effective programs and practices that can be adopted and adapted by institutions, departments, and individual faculty members.
Author: Rick Spair
Author: Rick Spair
Author: Rick Spair
Author: Matt Calkins
Author: Craig Le Clair
Author: Sk Md Obaidullah
Author: Vadim V. Strijov
Author: Keith Stouffer
Author: Vincent Rainardi
Author: Alan Rushton
Author: National Academies of Sciences, Engineering, and Medicine