Governance Of Through Big Data Volume Ii

These two volumes collect twenty five articles and papers published within the “Governance of/through Data” research project financed by the Italian Ministry of Universities. The research project, which was promoted by Roma Tre University, as project lead, and saw the participation of professors and reseachers from Bocconi University in Milan; LUMSA University in Rome; Salento University in Lecce and Turin Polytechnic, cover multiple issues which are here presented in five sections: Algorithms and artificial intelligence; Antitrust, artificial intelligence and data; Big Data; Data governance; Data protection and privacy.

These two volumes collect twenty five articles and papers published within the “Governance of/through Data” research project financed by the Italian Ministry of Universities. The research project, which was promoted by Roma Tre University, as project lead, and saw the participation of professors and reseachers from Bocconi University in Milan; LUMSA University in Rome; Salento University in Lecce and Turin Polytechnic, cover multiple issues which are here presented in five sections: Algorithms and artificial intelligence; Antitrust, artificial intelligence and data; Big Data; Data governance; Data protection and privacy. DOI: 10.13134/979-12-5977-173-5

Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.

Written by a leading expert in the field, this guide focuses on the convergence of two major trends in information management--big data and information governance--by taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data; this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes, procedures, and policies. It teaches readers to understand how big data fits within an overall information governance program; quantify the business value of big data; apply information governance concepts such as stewardship, metadata, and organization structures to big data; appreciate the wide-ranging business benefits for various industries and job functions; sell the value of big data governance to businesses; and establish step-by-step processes to implement big data governance.

This IBM® Redbooks® publication describes how the IBM Big Data Platform provides the integrated capabilities that are required for the adoption of Information Governance in the big data landscape. As organizations embark on new use cases, such as Big Data Exploration, an enhanced 360 view of customers, or Data Warehouse modernization, and absorb ever growing volumes and variety of data with accelerating velocity, the principles and practices of Information Governance become ever more critical to ensure trust in data and help organizations overcome the inherent risks and achieve the wanted value. The introduction of big data changes the information landscape. Data arrives faster than humans can react to it, and issues can quickly escalate into significant events. The variety of data now poses new privacy and security risks. The high volume of information in all places makes it harder to find where these issues, risks, and even useful information to drive new value and revenue are. Information Governance provides an organization with a framework that can align their wanted outcomes with their strategic management principles, the people who can implement those principles, and the architecture and platform that are needed to support the big data use cases. The IBM Big Data Platform, coupled with a framework for Information Governance, provides an approach to build, manage, and gain significant value from the big data landscape.

Data is the new Gold and Analytics is the machinery to mine, mold and mint it. Data analytics has become core to business and decision making. The rapid increase in data volume, velocity and variety, known as big data, offers both opportunities and challenges. While open source solutions to store big data, like Hadoop and NoSQL offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Organizations that are launching big data initiatives face significant challenges for managing this data effectively. In this book, the author has collected best practices from the world's leading organizations who have successfully implemented big data platforms. He offers the latest techniques and methods for managing big data effectively. The book offers numerous policies, strategies and recipes for managing big data. It addresses many issues that are prevalent with data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. Topics that cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and information technology leaders who are implementing big data platforms in their organizations.

The world is witnessing the growth of a global movement facilitated by technology and social media. Fueled by information, this movement contains enormous potential to create more accountable, efficient, responsive, and effective governments and businesses, as well as spurring economic growth. Big Data Governance and Perspectives in Knowledge Management is a collection of innovative research on the methods and applications of applying robust processes around data, and aligning organizations and skillsets around those processes. Highlighting a range of topics including data analytics, prediction analysis, and software development, this book is ideally designed for academicians, researchers, information science professionals, software developers, computer engineers, graduate-level computer science students, policymakers, and managers seeking current research on the convergence of big data and information governance as two major trends in information management.

This book is the first practical case study on the application of big data in China's government management scenarios, which is important for comprehensively presenting the achievements of China's e-government and digital construction as well as deeply understanding the implementation of big data strategy in China. The author of this book is one of the earliest practitioners engaged in the study of big data applications, and has personally experienced the development, major events, application cases, and industry changes of big data in China. Cases in this book are all actual projects carried out. The author of this book explains the development history of big data she has personally experienced, presenting in an easy-to-understand way the basic concept and characteristics of big data and practical interpretation, which provides important reference for the practical work of government and enterprise managers. The application ideas of big data in management innovation are proposed, and scenarios are described and discussed in terms of accelerating research on sharing big data in government affairs, breaking barriers, realizing data flow information sharing, creating one-stop services, improving the corresponding policy system for sharing big data in government affairs, building public information platform for e-government, and strengthening network and information infrastructure. Especially for the government personnel in departments, this book will give them a better understanding of the charm and value of big data, intuitively understand the utilization and analysis of big data, carry out effective government management and make correct decisions, so as to improve the data literacy of organizations and individuals, form scientific support for their own government's decision-making and management, thus promote the continued construction of digital government, digital China, and digital economy era based on the application of big data.