IT服务管理－基于ITIL的全球最佳实践PDF电子书（14章版）目前网上最全章节版本编辑推荐IT服务管理论坛是一个主要由其会员负责运营的非营利性组织。它是世界IT服务管理领域行业最佳实践和标准的重要影响者和贡献者。它决不依附于任何机构、公司或产品，而完全由其会员所拥有。国际IT服务管理论坛组织，通过其全球IT服务管理论坛分会成员代表组成的国际出版执行委员会对该书授予了第一个正式的ITSMF国际性的认可。这本ITSMF的出版物获得了EXIN的肯定并将其作为ITIL基础认证考试的指定读本。EXIN是一家全球开创教育标准并在IT领域里组织、开发认证考试的独立性机构。内容简介近年来，IT服务管理已经发展成为一个独立的行业。目前，组织越来越依赖业务流程的自动化，以致IT服务的质量和这些服务与组织需求的同步性对于组织的生存起到了非常关键的作用。本书是由国际IT服务管理论坛荷兰会根据最新版ITIL书籍编写的，可作为：对IT服务管理领域的一个全面而实用的介绍，也可作为了解IT基础设施库的读本；一本自学指南，书中涵盖了准备IT服务管理基础资格认证考试所需的全部资料。本书不但全面涵盖了由ITIL认证管理协会规定的ITIL基础认证考试所必备的官方课程提纲，而且还包含了许多由编委们汇集的实践知识。这些实践知识和对IT服务管理领域的介绍使得本书对于那些即便不准备参加认证考试的读者来说，也将是受益匪浅的。任何一本出版物都不可能回答在IT服务管理这样一个争论多于定论的领域里出现的所有问题，因此本书的目的是提出一些关键问题，鼓励读者进行更多、更深入的讨论，并将本书中介绍的最佳实践与读者自己的经验进行比较，从而得出最适合组织业力流程的实施方法。我们希望这本书不仅可以满足您的阅读和研究，而且能够在实践中得到广泛的应用。目录第 1 章 引言 第 2 章 IT服务管理的背景 2.1 服务和质量 2.1.1 质量保证 2.1.2 组织成熟度 2.2 组织和政策 2.2.1 愿景、目标和政策 2.2.2 规划周期 2.2.3 文化 2.2.4 人力资源管理 2.2.5 IT客户关系管理 2.3 流程管理 2.3.1 流程 2.3.2 流程和部门 2.3.3 IT服务管理 第 3 章 ITIL简介 3.1 背景 3.2 组织 3.2.1 OGC(CCTA) 3.2.2 itSMF 3.2.3 EXIN和ISEB 3.3 ITIL出版物 3.3.1 服务交付 3.3.2 服务支持 3.3.3 安全管理 3.3.4 ICT基础设施管理 3.3.5 应用管理 3.3.6 服务管理实施规划 3.3.7 业务视角 第 4 章 事件管理 4.1 概述 4.2 目标 4.3 流程 4.3.1 事件管理活动4.3.2 与其他流程之间的关系 4.4 活动 4.4.1 接收和记录 4.4.2 归类 4.4.3 匹配 4.4.4 调查与诊断 4.4.5 解决与恢复 4.4.6 终止 4.4.7 进度跟踪与监控 4.5 流程控制 4.5.1 关键成功因素4.5.2 绩效指标 4.5.3 职责和角色 4.6 成本和可能产生的问题 4.6.1 成本 4.6.2 可能产生的问题 第 5 章 问题管理 5.1 介绍 5.1.1 对“问题”和“已知错误”的定义 5.1.2 与事件管理之间的关系 5.2 目标 5.3 流程 5.3.1 问题管理活动 5.3.2 与其他流程之间的关系 5.4 活动 5.4.1 问题控制 5.4.2 错误控制 5.4.3 主动问题管理 5.4.4 提供信息 5.5 流程控制 5.5.1 关键成功因素 5.5.2 关键绩效指标和管理报告 5.5.3 职能和角色 5.6 成本和可能产生的问题 5.6.1 成本 5.6.2 可能产生的问题 第 6 章 配置管理 第 7 章 变更管理 第 8 章 发布管理 第 9 章 服务台 第 10 章 服务级别管理 第 11 章 IT服务财务管理 第 12 章 能力管理 第 13 章 IT服务持续性管理 第 14 章 可用性管理 第 15 章 安全管理 第 16 章 ICT基础设施管理 第 17 章 应用管理 附 录 A 案例研究——敏捷信使公司(Quick Couriers) A.1 配置管理 A.2 事件管理和服务台 A.3 问题管理
2021-09-10 16:12:09
3.79MB
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2018年最新标准，本标准给出了数据管理能力成熟度评估模型以及相应的成熟度等级,定义了数据战略、数据治理、数据架构、数据应用、数据安全、数据质量、数据标准和数据生存周期等8个能力域。本标准适用于组织和机构对数据管理能力成熟度进行评估。
2021-07-15 18:34:28
499KB
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DMOBOK是DAMA国际编著的一本有关数据管理的专注，比较权威
Dedicated to the memory ofPatricia Cupoli, MLS, MBA, CCP, CDMP(May25,1948-July28,2015for her lifelong commitment to the Data Management professionand her contributions to this publicationPublished byTechnics oQ Publications2 Lindsley roadBasking ridge, NJ 07920 USAhilps://www.technicspub.comSenior editorDeborah Henderson. CDMPEditor:Susan earley, CDMPProduction editorLaura Sebastian-Coleman, CDMP, IQCPBibliography researcherElena Sykora, DGSPCollaboration tool managerEva Smith cDMPCover design by Lorena MolinariAll rights reserved. No part of this book may be reproduced or transmitted in any form or by any means, electronicor mechanical, including photocopying, recording or by any information storage and retrieval system, withoutwritten permission from the publisher, except for the inclusion of brief quotations in a review.The author and publisher have taken care in the preparation of this book, but make no expressed or impliedwarranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental orconsequential damages in connection with or arising out of the use of the information or programs contained hereinAll trade and product names are trademarks, registered trademarks or service marks of their respective companiesand are the property of their respective holders and should be treated as suchSecond editionFirst Printing 2017Copyright O 2017 DAMA InternationalISBN. Print ed9781634622349ISBN. PDF ed9781634622363IsBN. Server ed9781634622486iSBN, Enterprise ed9781634622479Library of congress control number2017941854ContentsPreface15Chapter 1: Data Management171. Introduction172. Essential Concepts182.1 Data2.2 Data and information202.3 Data as an Organizational asset202.4 Data Management principles212.5 Data Management Challenges232.6 Data Management Strategy3. Data Management frameworks333.1 Strategic Alignment Model3.2 The amsterdam Information model343,3 The DAMA-DmboK framework3.4 DMBOK Pyramid (Aiken)393.5 DAMA Data Management Framework evolved404, DAMA and the dobok435. Works Cited/ Recommended46Chapter 2: Data Handling ethics491 Introduction492. Business drivers3. Essential Concepts523.1 Ethical Principles for data3.2 Principles Behind Data Privacy Law3.3 Online data in an ethical context563.4 Risks of Unethical Data Handling Practices563. 5 Establishing an ethical data culture603.6 Data ethics and governance644. Works Cited/Recommended65Chapter 3 Data governance1. Introduction671.1 Business drivers701.2 Goals and Principles1.3 Essential Concepts722 Activities792.1 Define Data Governance for the organization792.2 Perform readiness assessment2. 3 Perform discovery and business alignment2.4 Develop Organizational Touch Points812.5 Develop Data Governance Strategy822.6 Define the DG Operating Framework822.7 Develop Goals, Principles, and policies832. 8 Underwrite Data Management projects842.9 Engage Change management852· DMBOK22.10 Engage in Issue Management862.11 Assess Regulatory Compliance Requirements872.12 Implement Data Governance882.13 Sponsor data Standards and procedures882. 14 Develop a Business Glossary902. 15 Coordinate with Architecture Groups902.16 Sponsor Data Asset valuation912.17 Embed data governance913. Tools and Techniques923.1 Online Presence/Websites923.2 Business Glossary923. 3 Workflow tools3. 4 Document Management Tools933.5 Data governance scorecards934. Implementation Guidelines934. 1 Organization and culture934.2 Adjustment and communication945. Metrics6. Works cited/ recommended95Chapter 4: Data Architecture971 Introduction971.1 Business drivers991.2 Data Architecture Outcomes and practices1001.3 Essential Concepts1012. Activities1092.1 Establish data architecture practice1102.2 Integrate with Enterprise Architecture1153. Tools1153.1 Data Modeling Tools1153.2 Asset Management Software1153.3 Graphical Design Applications4. Techniques1164. 1 Lifecycle projectionsl164.2 Diagramming Clarity1165 Implementation guidelines1175.1 Readiness assessment/ Risk Assessment1185.2 Organization and Cultural change1196. Data architecture governance1196.1 Metrics1207. Works Cited/ Recommended120Chapter 5: Data Modeling and Design1231 Introduction1231.1 Business drivers1251.2 Goals and Principles1251.3 Essential Concepts1262 Activities1522.1 Plan for Data modeling152CONTENTS·32,2 Build the data model1532.3 Review the data models1582,4 Maintain the data models1593. Tools3.1 Data Modeling tools1593.2 Lineage tools1593.3 Data Profiling Tools1603.4 Metadata Repositories1603.5 Data model patterns1603.6 Industry data models1604, Best practices16l4.1 Best Practices in Naming Conventions1614. 2 Best Practices in Database design16l5, Data model governance1625.1 Data Model and Design Quality Management1625.2 Data Modeling metrics1646. Works Cited/ Recommended166Chapter 6: Data Storage and operations1691. Introduction1691.1 Business drivers1711.2 Goals and Principles1711.3 Essential Concepts1722. Activities1932.1 Manage Database Technology1942.2 Manage databases1963. Tools2093. 1 Data Modeling tools2093.2 Database Monitoring tools2093.3 Database Management Tools2093.4 Developer Support Tools2094. Techniques2104. 1 Test in lower environments2104.2 Physical Naming Standards2104.3 Script Usage for All Changes2105 Implementation guidelines2105.1 Readiness Assessment/Risk Assessment2105.2 Organization and Cultural Change2116. Data Storage and operations governance6.1 Metric2126.2 Information Asset Tracking2136.3 Data Audits and data validation2137. Works Cited/Recommended214Chapter 7: Data Security2171. Introduction2171. 1 Business drivers1.2 Goals and Principles2221.3 Essential Concepts2234· DMBOK22. Activities2452.1 Identify Data Security Requirements2452.2 Define Data Security Policy2472.3 Define Data Security standards2483. Tools2563.1 Anti-Virus Software/ Security Software2563.2 Https2563.3 Identity Management Technology2573.4 Intrusion detection and prevention software2573.5 Firewalls(Prevention2573.6 Metadata Tracking2573.7 Data Masking/Encryption2584. Techniques2584.1 CRUD Matrix Usage2584.2 Immediate Security Patch Deployment2584.3 Data security attributes in metadata2584.4 Metrics2594.5 Security Needs in Project requirements2614.6 Efficient Search of Encrypted Data2624.7 Document sanitization625 Implementation guidelines5.1 Readiness Assessment/Risk Assessment2625.2 Organization and cultural change2635.3 Visibility into User Data Entitlement2635. 4 Data Security in an Outsourced World2645.5 Data security in Cloud environments2656. Data Security governance2656.1 Data Security and Enterprise architecture2657. Works Cited/Recommended266chapter 8: Data Integration and Interoperability2691. Introduction2691.1 Business drivers2701.2 Goals and principles2721.3 Essential Concepts2732. Data Integration Activities2862. 1 Plan and analyze2862.2 Design Data Integration Solutions2892.3 Develop data Integration Solutions2912.4 Implement and monitor2933. Tools2943.1 Data Transformation Engine/EtL Tool2943.2 Data virtualization server2943.3 Enterprise Service Bus2943.4 Business rules engine2953.5 Data and Process Modeling tools2953.6 Data Profiling tool2953.7 Metadata Repository2964. Techniques296CONTENTS·55 Implementation Guidelines2965.1 Readiness assessment/ Risk Assessment2965.2 Organization and Cultural change2976, Dll Governance2976.1 Data Sharing agreements2986.2 Dll and data lineage2986.3 Data Integration Metrics2997. Works Cited/recommended299Chapter 9: Document and Content Management3031 Introduction3031.1 Business drivers3051.2 Goals and principles3051.3 Essential Concepts3072. Activities3232. 1 Plan for lifecycle management3232.2 Manage the lifecycle3262. 3 Publish and deliver content3293. Tools3301 Enterprise Content Management Systems3302 Collaboration tools3333.3 Controlled vocabulary and metadata tools3333. 4 Standard markup and exchange formats3333.5 E-discovery Technology3364. Techniques3364. 1 Litigation response playbook3364. 2 Litigation Response Data Map3375 Implementation Guidelines3375.1 Readiness Assessment/ Risk Assessment3385.2 Organization and Cultural Change3396. Documents and content governance3406.1 Information governance frameworks3406.2 Proliferation of information3426.3 Govern for Quality Content3426.4 Metrics3437. Works Cited/ recommended344Chapter 10: Reference and Master Data3471 Introduction3471. 1 Business drivers3491.2 Goals and principles3491.3 Essential Concepts3502. Activities702.1 MDM ACtivities3712.2 Reference data activities3733. Tools and Techniques3754. Implementation guidelines3754.1 Adhere to master data architecture3764.2 Monitor data movement3766· DMBOK24.3 Manage Reference Data Change3764.4 Data Sharing Agreements3775. Organization and cultural change3786, Reference and master data governance3786.1 Metrics3797. Works Cited/Recommended379Chapter 11: Data Warehousing and Business Intelligence3811 Introduction3811.1 Business drivers3831.2 Goals and Principles3831.3 Essential Concepts3842. Activities3942.1 Understand requirements3942.2 Define and Maintain the DW/BI Architecture3952.3 Develop the data Warehouse and Data marts3962.4 Populate the data Warehouse3972.5 Implement the Business Intelligence Portfolio3982.6 Maintain data products3993. Tools4023.1 Metadata repository4023.2 Data Integration Tools4033. 3 Business Intelligence Tools Types4034. Techniques4074.1 Prototypes to Drive Requirements4074.2 Self-Service bi4084.3 Audit Data that can be queried4085 Implementation Guidelines4085.1 Readiness Assessment/Risk Assessment4085.2 Release Roadmap4095.3 Configuration Management4095.4 Organization and Cultural Change4106. DW/BI Governance4116.1 Enabling business acceptance4116.2 Customer/User Satisfaction4126. 3 Service Level Agreements416. 4 Reporting strategy6.5 Metrics442237. Works cited/ recommended414Chapter 12: Metadata Management4171 Introduction4171.1 Business drivers4201.2 Goals and Principles4201. 3 Essential Concepts422. Activities4342. 1 Define metadata Strategy4342.2 Understand Metadata Requirements4352.3 Define metadata architecture436
Dedicated to the memory ofPatricia Cupoli, MLS, MBA, CCP, CDMP(May25,1948-July28,2015for her lifelong commitment to the Data Management professionand her contributions to this publicationPublished byTechnics oQ Publications2 Lindsley roadBasking ridge, NJ 07920 USAhilps://www.technicspub.comSenior editorDeborah Henderson. CDMPEditor:Susan earley, CDMPProduction editorLaura Sebastian-Coleman, CDMP, IQCPBibliography researcherElena Sykora, DGSPCollaboration tool managerEva Smith cDMPCover design by Lorena MolinariAll rights reserved. No part of this book may be reproduced or transmitted in any form or by any means, electronicor mechanical, including photocopying, recording or by any information storage and retrieval system, withoutwritten permission from the publisher, except for the inclusion of brief quotations in a review.The author and publisher have taken care in the preparation of this book, but make no expressed or impliedwarranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental orconsequential damages in connection with or arising out of the use of the information or programs contained hereinAll trade and product names are trademarks, registered trademarks or service marks of their respective companiesand are the property of their respective holders and should be treated as suchSecond editionFirst Printing 2017Copyright O 2017 DAMA InternationalISBN. Print ed9781634622349ISBN. PDF ed9781634622363IsBN. Server ed9781634622486iSBN, Enterprise ed9781634622479Library of congress control number2017941854ContentsPreface15Chapter 1: Data Management171. Introduction172. Essential Concepts182.1 Data2.2 Data and information202.3 Data as an Organizational asset202.4 Data Management principles212.5 Data Management Challenges232.6 Data Management Strategy3. Data Management frameworks333.1 Strategic Alignment Model3.2 The amsterdam Information model343,3 The DAMA-DmboK framework3.4 DMBOK Pyramid (Aiken)393.5 DAMA Data Management Framework evolved404, DAMA and the dobok435. Works Cited/ Recommended46Chapter 2: Data Handling ethics491 Introduction492. Business drivers3. Essential Concepts523.1 Ethical Principles for data3.2 Principles Behind Data Privacy Law3.3 Online data in an ethical context563.4 Risks of Unethical Data Handling Practices563. 5 Establishing an ethical data culture603.6 Data ethics and governance644. Works Cited/Recommended65Chapter 3 Data governance1. Introduction671.1 Business drivers701.2 Goals and Principles1.3 Essential Concepts722 Activities792.1 Define Data Governance for the organization792.2 Perform readiness assessment2. 3 Perform discovery and business alignment2.4 Develop Organizational Touch Points812.5 Develop Data Governance Strategy822.6 Define the DG Operating Framework822.7 Develop Goals, Principles, and policies832. 8 Underwrite Data Management projects842.9 Engage Change management852· DMBOK22.10 Engage in Issue Management862.11 Assess Regulatory Compliance Requirements872.12 Implement Data Governance882.13 Sponsor data Standards and procedures882. 14 Develop a Business Glossary902. 15 Coordinate with Architecture Groups902.16 Sponsor Data Asset valuation912.17 Embed data governance913. Tools and Techniques923.1 Online Presence/Websites923.2 Business Glossary923. 3 Workflow tools3. 4 Document Management Tools933.5 Data governance scorecards934. Implementation Guidelines934. 1 Organization and culture934.2 Adjustment and communication945. Metrics6. Works cited/ recommended95Chapter 4: Data Architecture971 Introduction971.1 Business drivers991.2 Data Architecture Outcomes and practices1001.3 Essential Concepts1012. Activities1092.1 Establish data architecture practice1102.2 Integrate with Enterprise Architecture1153. Tools1153.1 Data Modeling Tools1153.2 Asset Management Software1153.3 Graphical Design Applications4. Techniques1164. 1 Lifecycle projectionsl164.2 Diagramming Clarity1165 Implementation guidelines1175.1 Readiness assessment/ Risk Assessment1185.2 Organization and Cultural change1196. Data architecture governance1196.1 Metrics1207. Works Cited/ Recommended120Chapter 5: Data Modeling and Design1231 Introduction1231.1 Business drivers1251.2 Goals and Principles1251.3 Essential Concepts1262 Activities1522.1 Plan for Data modeling152CONTENTS·32,2 Build the data model1532.3 Review the data models1582,4 Maintain the data models1593. Tools3.1 Data Modeling tools1593.2 Lineage tools1593.3 Data Profiling Tools1603.4 Metadata Repositories1603.5 Data model patterns1603.6 Industry data models1604, Best practices16l4.1 Best Practices in Naming Conventions1614. 2 Best Practices in Database design16l5, Data model governance1625.1 Data Model and Design Quality Management1625.2 Data Modeling metrics1646. Works Cited/ Recommended166Chapter 6: Data Storage and operations1691. Introduction1691.1 Business drivers1711.2 Goals and Principles1711.3 Essential Concepts1722. Activities1932.1 Manage Database Technology1942.2 Manage databases1963. Tools2093. 1 Data Modeling tools2093.2 Database Monitoring tools2093.3 Database Management Tools2093.4 Developer Support Tools2094. Techniques2104. 1 Test in lower environments2104.2 Physical Naming Standards2104.3 Script Usage for All Changes2105 Implementation guidelines2105.1 Readiness Assessment/Risk Assessment2105.2 Organization and Cultural Change2116. Data Storage and operations governance6.1 Metric2126.2 Information Asset Tracking2136.3 Data Audits and data validation2137. Works Cited/Recommended214Chapter 7: Data Security2171. Introduction2171. 1 Business drivers1.2 Goals and Principles2221.3 Essential Concepts2234· DMBOK22. Activities2452.1 Identify Data Security Requirements2452.2 Define Data Security Policy2472.3 Define Data Security standards2483. Tools2563.1 Anti-Virus Software/ Security Software2563.2 Https2563.3 Identity Management Technology2573.4 Intrusion detection and prevention software2573.5 Firewalls(Prevention2573.6 Metadata Tracking2573.7 Data Masking/Encryption2584. Techniques2584.1 CRUD Matrix Usage2584.2 Immediate Security Patch Deployment2584.3 Data security attributes in metadata2584.4 Metrics2594.5 Security Needs in Project requirements2614.6 Efficient Search of Encrypted Data2624.7 Document sanitization625 Implementation guidelines5.1 Readiness Assessment/Risk Assessment2625.2 Organization and cultural change2635.3 Visibility into User Data Entitlement2635. 4 Data Security in an Outsourced World2645.5 Data security in Cloud environments2656. Data Security governance2656.1 Data Security and Enterprise architecture2657. Works Cited/Recommended266chapter 8: Data Integration and Interoperability2691. Introduction2691.1 Business drivers2701.2 Goals and principles2721.3 Essential Concepts2732. Data Integration Activities2862. 1 Plan and analyze2862.2 Design Data Integration Solutions2892.3 Develop data Integration Solutions2912.4 Implement and monitor2933. Tools2943.1 Data Transformation Engine/EtL Tool2943.2 Data virtualization server2943.3 Enterprise Service Bus2943.4 Business rules engine2953.5 Data and Process Modeling tools2953.6 Data Profiling tool2953.7 Metadata Repository2964. Techniques296CONTENTS·55 Implementation Guidelines2965.1 Readiness assessment/ Risk Assessment2965.2 Organization and Cultural change2976, Dll Governance2976.1 Data Sharing agreements2986.2 Dll and data lineage2986.3 Data Integration Metrics2997. Works Cited/recommended299Chapter 9: Document and Content Management3031 Introduction3031.1 Business drivers3051.2 Goals and principles3051.3 Essential Concepts3072. Activities3232. 1 Plan for lifecycle management3232.2 Manage the lifecycle3262. 3 Publish and deliver content3293. Tools3301 Enterprise Content Management Systems3302 Collaboration tools3333.3 Controlled vocabulary and metadata tools3333. 4 Standard markup and exchange formats3333.5 E-discovery Technology3364. Techniques3364. 1 Litigation response playbook3364. 2 Litigation Response Data Map3375 Implementation Guidelines3375.1 Readiness Assessment/ Risk Assessment3385.2 Organization and Cultural Change3396. Documents and content governance3406.1 Information governance frameworks3406.2 Proliferation of information3426.3 Govern for Quality Content3426.4 Metrics3437. Works Cited/ recommended344Chapter 10: Reference and Master Data3471 Introduction3471. 1 Business drivers3491.2 Goals and principles3491.3 Essential Concepts3502. Activities702.1 MDM ACtivities3712.2 Reference data activities3733. Tools and Techniques3754. Implementation guidelines3754.1 Adhere to master data architecture3764.2 Monitor data movement3766· DMBOK24.3 Manage Reference Data Change3764.4 Data Sharing Agreements3775. Organization and cultural change3786, Reference and master data governance3786.1 Metrics3797. Works Cited/Recommended379Chapter 11: Data Warehousing and Business Intelligence3811 Introduction3811.1 Business drivers3831.2 Goals and Principles3831.3 Essential Concepts3842. Activities3942.1 Understand requirements3942.2 Define and Maintain the DW/BI Architecture3952.3 Develop the data Warehouse and Data marts3962.4 Populate the data Warehouse3972.5 Implement the Business Intelligence Portfolio3982.6 Maintain data products3993. Tools4023.1 Metadata repository4023.2 Data Integration Tools4033. 3 Business Intelligence Tools Types4034. Techniques4074.1 Prototypes to Drive Requirements4074.2 Self-Service bi4084.3 Audit Data that can be queried4085 Implementation Guidelines4085.1 Readiness Assessment/Risk Assessment4085.2 Release Roadmap4095.3 Configuration Management4095.4 Organization and Cultural Change4106. DW/BI Governance4116.1 Enabling business acceptance4116.2 Customer/User Satisfaction4126. 3 Service Level Agreements416. 4 Reporting strategy6.5 Metrics442237. Works cited/ recommended414Chapter 12: Metadata Management4171 Introduction4171.1 Business drivers4201.2 Goals and Principles4201. 3 Essential Concepts422. Activities4342. 1 Define metadata Strategy4342.2 Understand Metadata Requirements4352.3 Define metadata architecture436
2021-06-08 10:22:15
10.78MB
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为了确保信息系统的安全、可靠和有效，需要开展由独立的具有资格的IT审计师对以计算机为核心的信息系统进行的IT审计。本书全面透彻地介绍了IT审计的基本概念、目标、理论方法及技术；深入浅出地介绍了IT审计准则的框架、基本要求及与此相关的知识。力求做到既有理论深度，又有较强的实务性。这是国内第一本有关IT审计的书籍，由国家经贸委信息中心审校，本书将指导IT审计人员系统准确地把握IT审计的思想，正确有效地运用IT审计的方法与技术。本书可作为IT审计师的培训教材，也可作为信息系统主管的参考手册，还可作为信息管理专业或信息安全专业的本科生及研究生的教科书或参考书。目录：第1章 概论 第2章 信息系统开发过程的审计第3章 信息系统运行维护过程的审计第4章 信息系统生命周期共同业务的审计第5章 IT审计方法、技术与工具 第6章 IT审计中的评价技术 第7章 信息系统安全与风险管理第8章 IT审计标准与相关IT标准
2021-05-14 00:03:53
4.1MB
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dw2.0下一代数据仓库的构架.pdf ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~·
2019-12-21 20:27:58
43.12MB
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