"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.
With their rapidly changing architecture and API-driven automation, cloud platforms come with unique security challenges and opportunities. This hands-on book guides you through security best practices for multivendor cloud environments, whether your company plans to move legacy on-premises projects to the cloud or build a new infrastructure from the ground up. Developers, IT architects, and security professionals will learn cloud-specific techniques for securing popular cloud platforms such as Amazon Web Services, Microsoft Azure, and IBM Cloud. Chris Dotson—an IBM senior technical staff member—shows you how to establish data asset management, identity and access management, vulnerability management, network security, and incident response in your cloud environment.
Data-governance programs focus on authority and accountability for the management of data as a valued organizational asset. Data Governance should not be about command-and-control, yet at times could become invasive or threatening to the work, people and culture of an organization. Non-Invasive Data Governance™ focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources. Non-Invasive Data Governance will provide you with a complete set of tools to help you deliver a successful data governance program. Learn how: • Steward responsibilities can be identified and recognized, formalized, and engaged according to their existing responsibility rather than being assigned or handed to people as more work. • Governance of information can be applied to existing policies, standard operating procedures, practices, and methodologies, rather than being introduced or emphasized as new processes or methods. • Governance of information can support all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives. • A practical and non-threatening approach can be applied to governing information and promoting stewardship of data as a cross-organization asset. • Best practices and key concepts of this non-threatening approach can be communicated effectively to leverage strengths and address opportunities to improve.
As organizations deploy business intelligence and analytic systems to harness business value from their data assets, data governance programs are quickly gaining prominence. And, although data management issues have traditionally been addressed by IT departments, organizational issues critical to successful data management require the implementation of enterprise-wide accountabilities and responsibilities. Data Governance: Creating Value from Information Assets examines the processes of using data governance to manage data effectively. Addressing the complete life cycle of effective data governance—from metadata management to privacy and compliance—it provides business managers, IT professionals, and students with an integrated approach to designing, developing, and sustaining an effective data governance strategy. Explains how to align data governance with business goals Describes how to build successful data stewardship with a governance framework Outlines strategies for integrating IT and data governance frameworks Supplies business-driven and technical perspectives on data quality management, metadata management, data access and security, and data lifecycle The book summarizes the experiences of global experts in the field and addresses critical areas of interest to the information systems and management community. Case studies from healthcare and financial sectors, two industries that have successfully leveraged the potential of data-driven strategies, provide further insights into real-time practice. Facilitating a comprehensive understanding of data governance, the book addresses the burning issue of aligning data assets to both IT assets and organizational strategic goals. With a focus on the organizational, operational, and strategic aspects of data governance, the text provides you with the understanding required to leverage, derive, and sustain maximum value from the informational assets housed in your IT infrastructure.
This book delves into the concept of data as a critical enterprise asset needed for informed decision making, compliance, regulatory reporting and insights into trends, behaviors, performance and patterns. With good data being key to staying ahead in a competitive market, enterprises capture and store exponential volumes of data. Considering the business impact of data, there needs to be adequate management around it to derive the best value. Data governance is one of the core data management related functions. However, it is often overlooked, misunderstood or confused with other terminologies and data management functions. Given the pervasiveness of data and the importance of data, this book provides comprehensive understanding of the business drivers for data governance and benefits of data governance, the interactions of data governance function with other data management functions and various components and aspects of data governance that can be facilitated by technology and tools, the distinction between data management tools and data governance tools, the readiness checks to perform before exploring the market to purchase a data governance tool, the different aspects that must be considered when comparing and selecting the appropriate data governance technologies and tools from large number of options available in the marketplace and the different market players that provide tools for supporting data governance. This book combines the data and data governance knowledge that the author has gained over years of working in different industrial and research programs and projects associated with data, processes and technologies with unique perspectives gained through interviews with thought leaders and data experts. This book is highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge and get guidance on implementing data governance in their own data initiatives.
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.
Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
This book aims to provide the necessary background to work with big data blockchain by introducing some novel applications in service operations for both academics and interested practitioners, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book intends to cover theory, research, development, and applications of big data and blockchain, as embedded in the fields of mathematics, engineering, computer science, physics, economics, business, management, and life sciences, to help service operations management.
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.
In an era where data is the lifeblood of organizations, ensuring its proper management, protection, and ethical use is more critical than ever. The Data Stewardship Handbook is your essential guide to navigating the complex world of data governance, offering a clear, actionable roadmap for anyone tasked with managing data within an organization. Whether you're a seasoned data professional or new to the field, this book equips you with the knowledge and tools needed to implement effective data stewardship practices. You'll explore key concepts such as data quality, privacy, compliance, and security, while learning how to build a robust data governance framework that aligns with your organization's goals and regulatory requirements. This comprehensive guide delves into: Understanding Data Stewardship: Gain a deep understanding of the roles and responsibilities of a data steward and how they contribute to the success of an organization's data strategy. Building a Data Governance Framework: Learn how to design and implement a data governance structure that ensures data accuracy, integrity, and accessibility across your organization. Data Quality Management: Discover best practices for maintaining high data quality, including strategies for data profiling, cleansing, and validation. Privacy and Compliance: Navigate the complex landscape of data privacy laws and regulations, such as GDPR and CCPA, and learn how to ensure your organization remains compliant. Data Security: Protect your organization's data assets by understanding the principles of data security, including encryption, access controls, and incident response. Case Studies and Real-World Examples: Gain insights from real-world scenarios and case studies that illustrate the challenges and successes of data stewardship in various industries. Written by a seasoned data stewardship professional, this handbook combines practical advice, industry insights, and a wealth of resources to help you become a more effective data steward. Whether you're responsible for managing data in a small business or a large enterprise, the Data Stewardship Handbook is your go-to resource for ensuring that your organization's data is managed, protected, and leveraged to its fullest potential. Take control of your data strategy today and set your organization up for success with the Data Stewardship Handbook.
