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data lifecycle management policy: Data Protection and Information Lifecycle Management Thomas D. Petrocelli, 2006 This book introduces Information Lifecycle Management (ILM), a powerful new strategy for managing enterprise information based on its value over time. The author explains emerging techniques for protecting storage systems and storage networks, and for integrating storage security into your overall security plan. He also presents new technical advances and opportunities to improve existing data-protection processes, including backup/restore, replication, and remote copy. |
data lifecycle management policy: Data Governance: The Definitive Guide Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy-Grant, Jessi Ashdown, 2021-03-08 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. |
data lifecycle management policy: Life Cycle Management Guido Sonnemann, Manuele Margni, 2015-07-16 This book provides insight into the Life Cycle Management (LCM) concept and the progress in its implementation. LCM is a management concept applied in industrial and service sectors to improve products and services, while enhancing the overall sustainability performance of business and its value chains. In this regard, LCM is an opportunity to differentiate through sustainability performance on the market place, working with all departments of a company such as research and development, procurement and marketing, and to enhance the collaboration with stakeholders along a company’s value chain. LCM is used beyond short-term business success and aims at long-term achievements by minimizing environmental and socio-economic burden, while maximizing economic and social value. |
data lifecycle management policy: DAMA-DMBOK Dama International, 2017 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. |
data lifecycle management policy: Data Governance: The Definitive Guide Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy-Grant, Jessi Ashdown, 2021-03-08 As you move data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure your organization meets compliance requirements. Data governance incorporates the ways people, processes, and technology work together to ensure data is trustworthy and can be used effectively. This practical guide shows you how to effectively implement and scale data governance throughout your organization. Chief information, data, and security officers and their teams will learn strategy and tooling to support democratizing data and unlocking its value while enforcing security, privacy, and other governance standards. Through good data governance, you can inspire customer trust, enable your organization to identify business efficiencies, generate more competitive offerings, and improve customer experience. This book shows you how. You'll learn: Data governance strategies addressing people, processes, and tools Benefits and challenges of a cloud-based data governance approach How data governance is conducted from ingest to preparation and use How to handle the ongoing improvement of data quality Challenges and techniques in governing streaming data Data protection for authentication, security, backup, and monitoring How to build a data culture in your organization |
data lifecycle management policy: SAP Information Lifecycle Management Iwona Luther, Nicole Fernandes, 2020-08-27 Master SAP ILM, from retention management to lifecycle management for custom code. Follow step-by-step instructions and walk through all major functionality including policy creation, legal case management, data archiving, and more. Whether you're on SAP S/4HANA, SAP S/4HANA Cloud, or SAP ERP, you'll find the details you need to configure and use SAP ILM. Control and protect your data! Highlights include: 1) Retention management 2) GDPR 3) Data security 4) Blocking data 5) Data deletion 6) Archiving data 7) Legal case management 8) Data controller rule framework 9) Custom code data lifecycle 10) SAP S/4HANA 11) SAP S/4HANA Cloud 12) SAP ERP HCM |
data lifecycle management policy: Data Lifecycles Roger Reid, Gareth Fraser-King, W. David Schwaderer, 2007-01-11 Businesses now rely almost entirely on applications and databases, causing data and storage needs to increase at astounding rates. It is therefore imperative for a company to optimize and simplify the complexity of managing its data resources. Plenty of storage products are now available, however the challenge remains for companies to proactively manage their storage assets and align the resources to the various departments, divisions, geographical locations and business processes to achieve improved efficiency and profitability. Data Lifecycles identifies ways to incorporate an intelligent service platform to manage and map the storage of data. The authors give an overview of the latest trends and technologies in storage networking and cover critical issues such as world-wide compliance. Data Lifecycles: Provides a single-source guide to data and storage methodologies, processes, technologies and compliance issues. Addresses the need of an encompassing intelligent data and storage management platform for modern businesses. Gives an overview of the latest data technologies and concepts such as utility computing and information lifecycle management. Clearly defines and describes lifecycle management and strategies to ensure growth of critical business data. Shows how to dramatically reduce the total cost of storage ownership and provide rapid return on investment. Enables customers to make decisions directed toward the purchase of storage tools and storage management solutions. This text is an ideal introduction to modern data lifecycle management for network managers, system administrators, storage/system architects, network managers, information management directors as well as CIO/CTOs and their teams, senior IT managers and decision makers, and database administrators. |
data lifecycle management policy: Data Governance John Ladley, 2019-11-08 Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition |
data lifecycle management policy: The Canadian Health Information Management Lifecycle CHIMA, 2017-05-09 This HIM lifecycle resource will be useful to a wide range of jurisdictions that manage health information. The document will provide a summary of the recommended leading practices and principles related to managing health information throughout its lifecycle, regardless of the type of jurisdiction or information media. -- Publisher's website. |
data lifecycle management policy: A Developer's Guide to .NET in Azure Anuraj Parameswaran, Tamir Al Balkhi, 2023-10-20 Develop cloud-native applications using serverless technologies, Azure services, and .NET with the help of this reference guide Key Features Create cloud-native .NET applications using cutting-edge technologies Design, develop, and deploy scalable, manageable, and resilient apps with various Azure services Explore serverless architecture and optimize application scalability through efficient design Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionA Developer’s Guide to .NET in Azure helps you embark on a transformative journey through Microsoft Azure that is tailored to .NET developers. This book is a curated compendium that’ll enable you to master the creation of resilient, scalable, and highly available applications. The book is divided into four parts, with Part 1 demystifying Azure for you and emphasizing the portal's utility and seamless integration. The chapters in this section help you configure your workspace for optimal Azure synergy. You’ll then move on to Part 2, where you’ll explore serverless computing, microservices, containerization, Dapr, and Azure Kubernetes Service for scalability, and build pragmatic, cost-effective applications using Azure Functions and Container apps. Part 3 delves into data and storage, showing you how to utilize Azure Blob Storage for unstructured data, Azure SQL Database for structured data, and Azure Cosmos DB for document-oriented data. The final part teaches you about messaging and security, utilizing Azure App Configuration, Event Hubs, Service Bus, Key Vault, and Azure AD B2C for robust, secure applications. By the end of this book, you’ll have mastered Azure's responsive infrastructure for exceptional applications.What you will learn Discover how to create serverless apps and services Design microservices with Azure Kubernetes service Get to grips with different Azure databases and storage services Find out how to use secret and configuration management Familiarize yourself with event-driven architecture Understand how to leverage Azure Service Bus and Azure Event Hubs Find out how to protect APIs and apps using Azure B2C Who this book is forThis book is for .NET developers and architects who are eager to master the art of creating and deploying robust applications using .NET and Azure. A foundational understanding of .NET and Azure will enable you to enhance your skills with this resourceful guide. Developers aspiring to explore the realms of microservices and serverless applications within the .NET and Azure landscapes will find this book invaluable. |
data lifecycle management policy: Quality in the Era of Industry 4.0 Kai Yang, 2024-01-24 Enables readers to use real-world data from connected devices to improve product performance, detect design vulnerabilities, and design better solutions Quality in the Era of Industry 4.0 provides an insightful guide in harnessing user performance and behavior data through AI and other Industry 4.0 technologies. This transformative approach enables companies not only to optimize products and services in real-time, but also to anticipate and mitigate likely failures proactively. In a succinct and lucid style, the book presents a pioneering framework for a new paradigm of quality management in the Industry 4.0 landscape. It introduces groundbreaking techniques such as utilizing real-world data to tailor products for superior fit and performance, leveraging connectivity to adapt products to evolving needs and use-cases, and employing cutting-edge manufacturing methods to create bespoke, cost-effective solutions with greater efficiency. Case examples featuring applications from the automotive, mobile device, home appliance, and healthcare industries are used to illustrate how these new quality approaches can be used to benchmark the product’s performance and durability, maintain smart manufacturing, and detect design vulnerabilities. Written by a seasoned expert with experience teaching quality management in both corporate and academic settings, Quality in the Era of Industry 4.0 covers sample topics such as: Evolution of quality through industrial revolutions, from ancient times to the first and second industrial revolutions Quality by customer value creation, explaining differences in producers, stakeholders, and customers in the new digital age, along with new realities brought by Industry 4.0 Data quality dimensions and strategy, data governance, and new talents and skill sets for quality professionals in Industry 4.0 Automated product lifecycle management, predictive quality control, and defect prevention using technologies like smart factories, IoT, and sensors Quality in the Era of Industry 4.0 is a highly valuable resource for product engineers, quality managers, quality engineers and quality consultants, industrial engineers, and systems engineers who wish to make a participatory approach towards data-driven design, economical mass-customization, and late differentiation. |
data lifecycle management policy: Product Lifecycle Management John Stark, 2011-08-12 Product Lifecycle Management (2nd edition) explains what Product Lifecycle Management (PLM) is, and why it's needed. It describes the environment in which products are developed, realised and supported, before looking at the basic components of PLM, such as the product, processes, applications, and people. The final part addresses the implementation of PLM, showing the steps of a project or initiative, and typical activities. This new and expanded edition of Product Lifecycle Management is fully updated to reflect the many advances made in PLM since the release of the first edition. It includes descriptions of PLM technologies and examples of implementation projects in industry. Product Lifecycle Management will broaden the reader’s understanding of PLM, nurturing the skills needed to implement PLM successfully and to achieve world-class product performance across the lifecycle. “A 20-year veteran of PLM, I highly recommend this book. A clear and complete overview of PLM from definition to implementation. Everything is there - reasons, resources, strategy, implementation and PLM project management.” Achim Heilmann, Manager, Global Technical Publications, Varian Medical Systems “Product Lifecycle Management is an important technology for European industry. This state-of-the art book is a reference for those implementing and researching PLM.” Dr. Erastos Filos, Head of Sector Intelligent Manufacturing Systems, European Commission “This book, written by one of the best experts in this field, is an ideal complement for PLM courses at Bachelor and Master level, as well as a well-founded reference book for practitioners.” Prof. Dr.-Ing. Dr. h.c. Sandor Vajna, University of Magdeburg, Germany “This comprehensive book can help drive an understanding of PLM at all levels – from CEOs to CIOs, and from professors to students – that will help this important industry continue to expand and thrive.” James Heppelmann, President and Chief Executive Officer, PTC “PLM is a mission-critical decision-making system leveraged by the world’s most innovative companies to transform their process of innovation on a continuous basis. That is a powerful value proposition in a world where the challenge is to get better products to the market faster than ever before. That is the power of PLM.” Tony Affuso, Chairman and CEO, Siemens PLM Software |
data lifecycle management policy: Guidebook for Managing Data from Emerging Technologies for Transportation Kelley Klaver Pecheux, Benjamin B. Pecheux, Gene Ledbetter, Chris Lambert (Systems consultant), 2020 With increased connectivity between vehicles, sensors, systems, shared-use transportation, and mobile devices, unexpected and unparalleled amounts of data are being added to the transportation domain at a rapid rate, and these data are too large, too varied in nature, and will change too quickly to be handled by the traditional database management systems of most transportation agencies. The TRB National Cooperative Highway Research Program's NCHRP Research Report 952: Guidebook for Managing Data from Emerging Technologies for Transportation provides guidance, tools, and a big data management framework, and it lays out a roadmap for transportation agencies on how they can begin to shift - technically, institutionally, and culturally - toward effectively managing data from emerging technologies. Modern, flexible, and scalable big data methods to manage these data need to be adopted by transportation agencies if the data are to be used to facilitate better decision-making. As many agencies are already forced to do more with less while meeting higher public expectations, continuing with traditional data management systems and practices will prove costly for agencies unable to shift. |
data lifecycle management policy: Information Literacy in the Workplace Serap Kurbanoğlu, Joumana Boustany, Sonja Špiranec, Esther Grassian, Diane Mizrachi, Loriene Roy, 2018-01-25 This book constitutes the refereed post-conference proceedings of the 5th European Conference on Information Literacy, ECIL 2017, held in Saint Malo, France, in September 2017. The 84 revised papers included in this volume were carefully reviewed and selected from 358 submissions. The papers cover a wide range of topics in the field of information literacy and focus on information literacy in the workplace. They are organized in the following topical sections: workplace information literacy, employibility and career readiness; data literacy and research data management; media literacy; copyright literacy; transliteracy, reading literacy, digital literacy, financial literacy, search engine literacy, civic literacy; science literacy; health information literacy; information behavior; information literacy in higher education; information literacy in K-12; information literacy instruction; information literacy and libraries; and theoretical framework. |
data lifecycle management policy: Agile Application Lifecycle Management Bob Aiello, Leslie Sachs, 2016-06-01 Integrate Agile ALM and DevOps to Build Better Software and Systems at Lower Cost Agile Application Lifecycle Management (ALM) is a comprehensive development lifecycle that encompasses essential Agile principles and guides all activities needed to deliver successful software or other customized IT products and services. Flexible and robust, Agile ALM offers “just enough process” to get the job done efficiently and utilizes the DevOps focus on communication and collaboration to enhance interactions among all participants. Agile Application Lifecycle Management offers practical advice and strategies for implementing Agile ALM in your complex environment. Leading experts Bob Aiello and Leslie Sachs show how to fully leverage Agile benefits without sacrificing structure, traceability, or repeatability. You’ll find realistic guidance for managing source code, builds, environments, change control, releases, and more. The authors help you support Agile in organizations that maintain traditional practices, conventional ALM systems, or siloed, non-Agile teams. They also show how to scale Agile ALM across large or distributed teams and to environments ranging from cloud to mainframe. Coverage includes Understanding key concepts underlying modern application and system lifecycles Creating your best processes for developing your most complex software and systems Automating build engineering, continuous integration, and continuous delivery/deployment Enforcing Agile ALM controls without compromising productivity Creating effective IT operations that align with Agile ALM processes Gaining more value from testing and retrospectives Making ALM work in the cloud, and across the enterprise Preparing for the future of Agile ALM Today, you need maximum control, quality, and productivity, and this guide will help you achieve these capabilities by combining the best practices found in Agile ALM, Configuration Management (CM), and DevOps. |
data lifecycle management policy: Microsoft 365 Security and Compliance for Administrators Sasha Kranjac, Omar Kudović, 2024-03-29 Master the art of configuring and securing Microsoft 365, emphasizing robust security and compliance features, and managing privacy and risk in the Microsoft 365 environment Key Features Protect and defend your organization with the capabilities of the Microsoft 365 Defender family Discover, classify, and safeguard sensitive organizational data against loss, leakage, and exposure Collaborate securely while adhering to regulatory compliance and governance standards Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn today's hostile cyber landscape, securing data and complying with regulations is paramount for individuals, businesses, and organizations alike. Learn how Microsoft 365 Security and Compliance offers powerful tools to protect sensitive data and defend against evolving cyber threats with this comprehensive guide for administrators. Starting with an introduction to Microsoft 365 plans and essential compliance and security features, this book delves into the role of Azure Active Directory in Microsoft 365, laying the groundwork for a robust security framework. You’ll then advance to exploring the complete range of Microsoft 365 Defender security products, their coverage, and unique protection services to combat evolving threats. From threat mitigation strategies to governance and compliance best practices, you’ll gain invaluable insights into classifying and protecting data while mastering crucial data lifecycle capabilities in Microsoft 365. By the end of this book, you’ll be able to elevate the security and compliance posture of your organization significantly.What you will learn Maintain your Microsoft 365 security and compliance posture Plan and implement security strategies Manage data retention and lifecycle Protect endpoints and respond to incidents manually and automatically Implement, manage, and monitor security and compliance solutions Leverage Microsoft Purview to address risk and compliance challenges Understand Azure Active Directory’s role in Microsoft 365 Security Who this book is for This book is for security professionals, security administrators, and security responders looking to increase their knowledge and technical depth when it comes to Microsoft 365 security and compliance solutions and features. However, anyone aiming to enhance their security and compliance posture within the Microsoft 365 environment will find this book useful. Familiarity with fundamental Microsoft 365 concepts and navigating and accessing portals, along with basic Microsoft 365 administration experience is assumed. |
data lifecycle management policy: Product Lifecycle Management Antti Saaksvuori, Anselmi Immonen, 2005-12-06 In today`s industrial manufacturing Product Lifecycle Management (PLM) is essential in order to cope with the challenges of more demanding global competition. New and more complex products must be introduced to markets faster than ever before. Companies form large collaborative networks, and the product process must flow flexibly across company borders. This first book on Product Lifecycle Management in English language is designed to introduce the reader to the basic terms and fundamentals of PLM and to give a solid foundation for starting a PLM development project. It gives ideas and examples how PLM can be utilized in various industries. In addition, it also offers an insight into how PLM can assist in creating new business opportunities and in making real eBusiness possible. |
data lifecycle management policy: Data Protection David G. Hill, 2016-04-19 Failure to appreciate the full dimensions of data protection can lead to poor data protection management, costly resource allocation issues, and exposure to unnecessary risks. Data Protection: Governance, Risk Management, and Compliance explains how to gain a handle on the vital aspects of data protection.The author begins by building the foundatio |
data lifecycle management policy: Data Management for Researchers Kristin Briney, 2015-09-01 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 |
data lifecycle management policy: Microsoft 365 Certified Fundamentals MS-900 Exam Guide Aaron Guilmette, Yura Lee, Marcos Zanre, 2023-11-24 Get a clear understanding of the Microsoft 365 platform from concept through to execution to confidently prepare for exam, and benefit from having a handy, on-the-job desktop reference guide Key Features Practice with exam-style questions based on the latest certification exam syllabus Review the security considerations and benefits of adopting different types of cloud services Verify your knowledge of key concepts through chapter assessments, insider tips, and practice questions Purchase of this book unlocks access to web-based exam prep resources including practice questions, flashcards, and exam tips Book DescriptionThe MS-900 exam tests your understanding of Microsoft 365 services and components, along with their implementation, security, licensing, and general cloud concepts. This revised third edition helps you gain detailed actionable insights into the topics included in the latest syllabus, covering each topic according to its weight in the exam. You’ll begin by reviewing key cloud concepts, including cloud computing, services, and development models, and then explore different cloud architectures and learn what Microsoft offers as a service in the form of SaaS, IaaS, and PaaS. As you advance, you’ll get to grips with core Microsoft 365 components as well as the processes and tools used for managing Windows 10, Windows 11, and Microsoft 365 apps. This edition also includes expanded information on the Microsoft Viva Suite, formerly Workplace Analytics. The chapters shed light on security, compliance, privacy, and trust in Microsoft 365, and provide additional guidance regarding the pricing and support offered by Microsoft for different services and apps. By the end of this MS-900 book, you’ll have gained all the knowledge and skills needed to confidently appear for the exam.What you will learn Gain insight into the exam objectives and knowledge needed to take the MS-900 exam Discover and implement best practices for licensing options available in Microsoft 365 Understand the different Microsoft 365 Defender services Prepare to address the most common types of threats against an environment Identify and unblock the most common cloud adoption challenges Articulate key productivity, collaboration, security, and compliance selling points of M365 Explore licensing and payment models available for M365 Who this book is for This book is for entry as well as mid-level experienced administrators and individuals aspiring to pass the latest MS-900 exam and achieve Microsoft 365 certification. Basic knowledge of Microsoft services and cloud concepts is necessary to get the most out of this book. |
data lifecycle management policy: Data Integration Life Cycle Management with SSIS Andy Leonard, 2017-11-17 Build a custom BimlExpress framework that generates dozens of SQL Server Integration Services (SSIS) packages in minutes. Use this framework to execute related SSIS packages in a single command. You will learn to configure SSIS catalog projects, manage catalog deployments, and monitor SSIS catalog execution and history. Data Integration Life Cycle Management with SSIS shows you how to bring DevOps benefits to SSIS integration projects. Practices in this book enable faster time to market, higher quality of code, and repeatable automation. Code will be created that is easier to support and maintain. The book teaches you how to more effectively manage SSIS in the enterprise environment by drawing on the art and science of modern DevOps practices. What You'll Learn Generate dozens of SSIS packages in minutes to speed your integration projects Reduce the execution of related groups of SSIS packages to a single command Successfully handle SSIS catalog deployments and their projects Monitor the execution and history of SSIS catalog projects Manage your enterprise data integration life cycle through automated tools and utilities Who This Book Is For Database professionals working with SQL Server Integration Services in enterprise environments. The book is especially useful to those readers following, or wishing to follow, DevOps practices in their use of SSIS. |
data lifecycle management policy: AWS Certified SysOps Administrator Study Guide Jorge T. Negron, Christoffer Jones, George Sawyer, 2024-04-17 Prepare for success on the AWS SysOps exam, your next job interview, and in the field with this handy and practical guide The newly updated Third Edition of AWS Certified SysOps Administrator Study Guide: Associate (SOA-C02) Exam prepares you for the Amazon Web Services SysOps Administrator certification and a career in the deployment, management, and operation of an AWS environment. Whether you’re preparing for your first attempt at the challenging SOA-C02 Exam, or you want to upgrade your AWS SysOps skills, this practical Study Guide delivers the hands-on skills and best practices instruction you need to succeed on the test and in the field. You’ll get: Coverage of all of the SOA-C02 exam’s domains, including monitoring, logging, remediation, reliability, business continuity, and more Instruction that’s tailor-made to achieve success on the certification exam, in an AWS SysOps job interview, and in your next role as a SysOps administrator Access to the Sybex online study tools, with chapter review questions, full-length practice exams, hundreds of electronic flashcards, and a glossary of key terms The AWS Certified SysOps Administrator Study Guide: Associate (SOA-C02) Exam includes all the digital and offline tools you need to supercharge your career as an AWS Certified SysOps Administrator. |
data lifecycle management policy: Big Data Management Peter Ghavami, 2020-11-09 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. |
data lifecycle management policy: Enterprise Master Data Management Allen Dreibelbis, Eberhard Hechler, Ivan Milman, Martin Oberhofer, Paul van Run, Dan Wolfson, 2008-06-05 The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM ® data management innovators who are pioneering MDM, this book systematically introduces MDM’s key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else—everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset—bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration |
data lifecycle management policy: Climate Data Records from Environmental Satellites National Research Council, Division on Earth and Life Studies, Board on Atmospheric Sciences and Climate, Committee on Climate Data Records from NOAA Operational Satellites, 2004-08-26 The report outlines key elements to consider in designing a program to create climate-quality data from satellites. It examines historical attempts to create climate data records, provides advice on steps for generating, re-analyzing, and storing satellite climate data, and discusses the importance of partnering between agencies, academia, and industry. NOAA will use this report-the first in a two-part study-to draft an implementation plan for climate data records. |
data lifecycle management policy: Pharmaceutical Lifecycle Management Tony Ellery, Neal Hansen, 2012-06-05 A comprehensive guide to optimizing the lifecycle management of pharmaceutical brands The mounting challenges posed by cost containment policies and the prevalence of generic alternatives make optimizing the lifecycle management (LCM) of brand drugs essential for pharmaceutical companies looking to maximize the value of their products. Demonstrating how different measures can be combined to create winning strategies, Pharmaceutical Lifecycle Management: Making the Most of Each and Every Brand explores this increasingly important field to help readers understand what they can—and must—do to get the most out of their brands. Offering a truly immersive introduction to LCM options for pharmaceuticals, the book incorporates numerous real-life case studies that demonstrate successful and failed lifecycle management initiatives, explaining the key takeaway of each example. Filled with practical information on the process of actually writing and presenting an LCM plan, as well as how to link corporate, portfolio, and individual brand strategies, the book also offers a look ahead to predict which LCM strategies will continue to be effective in the future. While the development of new drugs designed to address unmet patient needs remains the single most important goal of any pharmaceutical company, effective LCM is invaluable for getting the greatest possible value from existing brands. Pharmaceutical Lifecycle Management walks you through the process step by step, making it indispensable reading for pharmaceutical executives and managers, as well as anyone working in the fields of drug research, development, and regulation. |
data lifecycle management policy: Data Mesh Zhamak Dehghani, 2022-03-08 Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh. |
data lifecycle management policy: Introduction to Storage Area Networks Jon Tate, Pall Beck, Hector Hugo Ibarra, Shanmuganathan Kumaravel, Libor Miklas, IBM Redbooks, 2018-10-09 The superabundance of data that is created by today's businesses is making storage a strategic investment priority for companies of all sizes. As storage takes precedence, the following major initiatives emerge: Flatten and converge your network: IBM® takes an open, standards-based approach to implement the latest advances in the flat, converged data center network designs of today. IBM Storage solutions enable clients to deploy a high-speed, low-latency Unified Fabric Architecture. Optimize and automate virtualization: Advanced virtualization awareness reduces the cost and complexity of deploying physical and virtual data center infrastructure. Simplify management: IBM data center networks are easy to deploy, maintain, scale, and virtualize, delivering the foundation of consolidated operations for dynamic infrastructure management. Storage is no longer an afterthought. Too much is at stake. Companies are searching for more ways to efficiently manage expanding volumes of data, and to make that data accessible throughout the enterprise. This demand is propelling the move of storage into the network. Also, the increasing complexity of managing large numbers of storage devices and vast amounts of data is driving greater business value into software and services. With current estimates of the amount of data to be managed and made available increasing at 60% each year, this outlook is where a storage area network (SAN) enters the arena. SANs are the leading storage infrastructure for the global economy of today. SANs offer simplified storage management, scalability, flexibility, and availability; and improved data access, movement, and backup. Welcome to the cognitive era. The smarter data center with the improved economics of IT can be achieved by connecting servers and storage with a high-speed and intelligent network fabric. A smarter data center that hosts IBM Storage solutions can provide an environment that is smarter, faster, greener, open, and easy to manage. This IBM® Redbooks® publication provides an introduction to SAN and Ethernet networking, and how these networks help to achieve a smarter data center. This book is intended for people who are not very familiar with IT, or who are just starting out in the IT world. |
data lifecycle management policy: Managing Big Data Integration in the Public Sector Aggarwal, Anil, 2015-11-12 The era of rapidly progressing technology we live in generates vast amounts of data; however, the challenge exists in understanding how to aggressively monitor and make sense of this data. Without a better understanding of how to collect and manage such large data sets, it becomes increasingly difficult to successfully utilize them. Managing Big Data Integration in the Public Sector is a pivotal reference source for the latest scholarly research on the application of big data analytics in government contexts and identifies various strategies in which big data platforms can generate improvements within that sector. Highlighting issues surrounding data management, current models, and real-world applications, this book is ideally designed for professionals, government agencies, researchers, and non-profit organizations interested in the benefits of big data analytics applied in the public sphere. |
data lifecycle management policy: Data Governance and Strategies Mr.Desidi Narsimha Reddy, 2024-09-05 Mr.Desidi Narsimha Reddy, Data Consultant (Data Governance, Data Analytics: Enterprise Performance Management, AI & ML), Soniks consulting LLC, 101 E Park Blvd Suite 600, Plano, TX 75074, United States. |
data lifecycle management policy: Data Protection Preston de Guise, 2020-04-29 The second edition of Data Protection goes beyond the traditional topics including deduplication, continuous availability, snapshots, replication, backup, and recovery, and explores such additional considerations as legal, privacy, and ethical issues. A new model is presented for understanding and planning the various aspects of data protection, which is essential to developing holistic strategies. The second edition also addresses the cloud and the growing adoption of software and function as a service, as well as effectively planning over the lifespan of a workload: what the best mix of traditional and cloud native data protection services might be. Virtualization continues to present new challenges to data protection, and the impact of containerization is examined. The book takes a holistic, business-based approach to data protection. It explains how data protection is a mix of proactive and reactive planning, technology, and activities that allow for data continuity. There are three essential activities that refer to themselves as data protection; while they all overlap in terms of scope and function, each operates as a reasonably self-contained field with its own specialists and domain nomenclature. These three activities are: • Data protection as a storage and recovery activity • Data protection as a security activity • Data protection as a privacy activity These activities are covered in detail, with a focus on how organizations can use them to leverage their IT investments and optimize costs. The book also explains how data protection is becoming an enabler for new processes around data movement and data processing. This book arms readers with information critical for making decisions on how data can be protected against loss in the cloud, on premises, or in a mix of the two. It explains the changing face of recovery in a highly virtualized datacenter and techniques for dealing with big data. Moreover, it presents a model for where data recovery processes can be integrated with IT governance and management in order to achieve the right focus on recoverability across the business. About the Author Preston de Guise has been working with data recovery products for his entire career—designing, implementing, and supporting solutions for governments, universities, and businesses ranging from SMEs to Fortune 500 companies. This broad exposure to industry verticals and business sizes has enabled Preston to understand not only the technical requirements of data protection and recovery, but the management and procedural aspects too. |
data lifecycle management policy: Research Data Management Joyce M. Ray, 2014 It has become increasingly accepted that important digital data must be retained and shared in order to preserve and promote knowledge, advance research in and across all disciplines of scholarly endeavor, and maximize the return on investment of public funds. To meet this challenge, colleges and universities are adding data services to existing infrastructures by drawing on the expertise of information professionals who are already involved in the acquisition, management and preservation of data in their daily jobs. Data services include planning and implementing good data management practices, thereby increasing researchers' ability to compete for grant funding and ensuring that data collections with continuing value are preserved for reuse. This volume provides a framework to guide information professionals in academic libraries, presses, and data centers through the process of managing research data from the planning stages through the life of a grant project and beyond. It illustrates principles of good practice with use-case examples and illuminates promising data service models through case studies of innovative, successful projects and collaborations. |
data lifecycle management policy: Product Lifecycle Management. Green and Blue Technologies to Support Smart and Sustainable Organizations Osiris Canciglieri Junior, Frédéric Noël, Louis Rivest, Abdelaziz Bouras, 2022-02-08 The two-volume set IFIP AICT 639 and 640 constitutes the refereed post-conference proceedings of the 18th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2021, held in Curitiba, Brazil, during July 11-14, 2021. The conference was held virtually due to the COVID-19 crisis. The 107 revised full papers presented in these proceedings were carefully reviewed and selected from 133 submissions. The papers are organized in the following topical sections: Volume I: Sustainability, sustainable development and circular economy; sustainability and information technologies and services; green and blue technologies; AI and blockchain integration with enterprise applications; PLM maturity, PLM implementation and adoption within industry 4.0; and industry 4.0 and emerging technologies: Volume II: Design, education and management; lean, design and innovation technologies; information technology models and design; and models, manufacturing and information technologies and services. |
data lifecycle management policy: Ubiquitous Security Guojun Wang, |
data lifecycle management policy: Mastering File an Print services Cybellium Ltd, Optimize Data Sharing and Document Management for Seamless Collaboration In the landscape of modern computing and network management, file and print services are the backbone of efficient data sharing and document management. Mastering File and Print Services is your comprehensive guide to understanding and harnessing the potential of these essential IT services, empowering you to create streamlined workflows that enhance collaboration and boost productivity. About the Book: As digital communication and collaboration become increasingly important, a strong foundation in file and print services becomes essential for IT professionals. Mastering File and Print Services offers an in-depth exploration of these core IT services—an indispensable toolkit for network administrators, system engineers, and enthusiasts. This book caters to both newcomers and experienced practitioners aiming to excel in designing, configuring, and managing file and print environments. Key Features: File Sharing Fundamentals: Begin by understanding the core principles of file sharing services. Learn about file access, permissions, and protocols that facilitate seamless data sharing. Print Services Essentials: Dive into print services. Explore methods for configuring and managing printers, print queues, and print jobs in a network environment. Network Attached Storage (NAS): Grasp the art of setting up NAS devices. Understand how to create shared storage solutions that enable efficient data access and backup. File and Folder Permissions: Explore techniques for managing file and folder permissions. Learn how to control access to sensitive data and maintain security. Printer Management: Understand printer management techniques. Learn how to deploy, configure, and troubleshoot printers in a networked environment. Centralized Document Management: Delve into document management strategies. Explore methods for creating centralized repositories and version control for documents. Mobile and Remote Access: Grasp techniques for enabling mobile and remote access to files and print services. Learn how to accommodate remote workers and ensure data availability. Real-World Applications: Gain insights into how file and print services are applied across industries. From businesses to educational institutions, discover the diverse applications of these services. Why This Book Matters: In a digital age driven by collaboration and data sharing, mastering file and print services offers a competitive advantage. Mastering File and Print Services empowers IT professionals, network administrators, and technology enthusiasts to leverage these crucial services, enabling them to design efficient workflows that enhance collaboration, data accessibility, and document management. Streamline Data Management for Success: In the landscape of modern computing, file and print services are essential for efficient collaboration and data sharing. Mastering File and Print Services equips you with the knowledge needed to leverage these essential IT services, enabling you to design streamlined workflows that enhance collaboration, improve data accessibility, and boost productivity. Whether you're a seasoned practitioner or new to the world of file and print services, this book will guide you in building a solid foundation for effective network management and document sharing. Your journey to mastering file and print services starts here. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com |
data lifecycle management policy: Azure Cookbook Reza Salehi, 2022-10-10 How do you deal with the problems you face when using Azure? This practical guide provides over 75 recipes to help you to work with common Azure issues in everyday scenarios. That includes key tasks like setting up permissions for a storage account, working with Cosmos DB APIs, managing Azure role-based access control, governing your Azure subscriptions using Azure Policy, and much more. Author Reza Salehi has assembled real-world recipes that enable you to grasp key Azure services and concepts quickly. Each recipe includes CLI scripts that you can execute in your own Azure account. Recipes also explain the approach and provide meaningful context. The solutions in this cookbook will take you beyond theory and help you understand Azure services in practice. You'll find recipes that let you: Store data in an Azure storage account or in a data lake Work with relational and nonrelational databases in Azure Manage role-based access control (RBAC) for Azure resources Safeguard secrets in Azure Key Vault Govern your Azure subscription using Azure Policy Use CLI code to construct your application or fix a particular problem |
data lifecycle management policy: Data Governance Evren Eryurek, Uri Gilad, Jessi Ashdown, Valliappa Lakshmanan, Anita Kibunguchy, 2021-04-13 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 |
data lifecycle management policy: CIO , 2004-03-01 |
data lifecycle management policy: System Lifecycle Management Martin Eigner, 2021-08-09 Years of experience in the area of Product Lifecycle Management (PLM) in industry, research and education form the basis for this overview. The author covers the development from PDM via PLM to SysLM (System Lifecycle Management) in the form commonly used today, which are necessary prerequisites for the sustainable development and implementation of IoT/IoS, Industry 4.0 and Engineering 4.0 concepts. The building blocks and properties of future-proof systems for the successful implementation of the concepts of Engineering 4.0 are thereby dedicated to holistic considerations, which also inform in detail. SysLM functions and processes in mechatronic development and design as well as across the entire product lifecycle - from requirements management to the Digital Twin - are covered as examples. SysLM trends such as low code development, cloud, disruptive business models, and bimodality provide an outlook on future developments. The author dedicates the treatment of the agile SysLM introduction to the implementation in the enterprise. The basics are deepened with examples of a concrete SysLM system. |
data lifecycle management policy: How to be FAIR with Your Data Claudia Engelhardt, Raisa Barthauer, Katarzyna Biernacka, Aoife Coffey, Ronald Cornet, Alina Danciu, Yuri Demchenko, Stephen Downes, Christopher Erdmann, Federica Garbuglia, Kerstin Germer, Kerstin Helbig, Margareta Hellström, Kristina Hettne, Dawn Hibbert, Mijke Jetten, Yulia Karimova, Karsten Kryger Hansen, Mari Elisa Kuusniemi, Viviana Letizia, Valerie McCutcheon, Barbara McGillivray, Jenny Ostrop, Britta Petersen, Ana Petrus, Stefan Reichmann, Najla Rettberg, Carmen Reverté, Nick Rochlin, Bregt Saenen, Birgit Schmidt, Jolien Scholten, Hugh Shanahan, Armin Straube, Veerle Van den Eynden, Justine Vandendorpe, Shanmugasundaram Venkataram, André Vieira, Cord Wiljes, Ulrike Wuttke, Joanne Yeomans, Biru Zhou, 2022 This handbook was written and edited by a group of about 40 collaborators in a series of six book sprints that took place between 1 and 10 June 2021. It aims to support higher education institutions with the practical implementation of content relating to the FAIR principles in their curricula, while also aiding teaching by providing practical material, such as competence profiles, learning outcomes, lesson plans, and supporting information. It incorporates community feedback received during the public consultation which ran from 27 July to 12 September 2021. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
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Belmont Forum
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Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
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Data Management Annex (Version 1.4) - Belmont Forum
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Data Governance Policy v1 - UNSW …
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Microsoft 365 lifecycle manage…
example, a retention policy that lasts for five years before data is permanently and irreversibly removed. This involves identifying …