1.该套文档以PMP关于项目管理5大过程组、10大知识领域为主目录，对应各个子过程分别精选了对应该过程的实用模板，有助于将理论知识与实际工作结合；
2.所有文档集成到一个EXCEL大文件中，每个文档使用一个Sheet，而且增加了子过程与文档的超链接，并增加了部分公式，避免了填写重复信息，就像在使用项目管理系统一样，避免淹没于众多文档中无所适从。
2021-06-15 09:08:00
187KB
收录了50多个文档模板项目及开发管理类：包括立项前的分析，立项后的计划、以及进度跟踪、风险控制方面的文档模板，共计16个；需求分析类：明确清晰的需求，是项目成功的基础，在此收集了在需求分析过程中所将使用到的文档模板，共计14个；系统分析与设计类：包括体系结构设计、高层设计、详细设计、数据库设计等6个相关文档模板；软件质量保证类：软件测试是质量保证的关键活动，在此收集了软件测试相关的11个文档模板；其它类：用户手册、软件维护等方面的10个文档模板，其中还有一个软件过程规范的示例。
2021-06-13 16:27:47
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车辆管理系统功能需求设计方案
车辆管理系统是针对宁东供电局内部车辆管理而设计的，通过本系统提供的整体解决方案可以有效提高车辆管理效率，节约车辆管理成本，极大的改善公车私用现象，及油料经济管理，方便各部室及基层单位管理人员对车辆的管理和监控。
2021-06-11 15:31:20
4.88MB
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软件项目管理过程各阶段文档
1.立项
2.结项
3.规划
4.监控
5风险
6.需求管
7.需求开发
。。。。。。。。。。。。。
2021-06-09 14:05:30
524KB
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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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软件项目管理（第四版）1章：软件项目管理引言1.1引言1.2为什么软件项目管理很重要1.3什么是项目1.4软件项目和其他类型项目1.5合同管理和技术项目管理1.6软件项目管理覆盖的活动1.7计划，方法和方法学1.8软件项目的风雷方法1.9什么是管理1.10软件项目的问题1.11设定目的1.12项目相关人员1.13业务案例1.14需求规格说明1.15管理控制1.16小结二章：步进式方法:项目策划概述三章：项目群管理和项目评价四章：选择合适的项目方法五章：软件工作量估计六章：活动策划七章：风险管理八章：资源分配九章：监督与控制十章：管理合同十一章：管理人员和组织群组十二章：软件质量十三章：小型项目
2021-06-07 10:27:05
32.28MB
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PRINCE2成功的项目管理（带完整书签中文第三版）.pdf
2021-06-06 19:47:06
24.14MB
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项目管理文档（附260多个文件）：
1.项目常用管理模板
2.IT项目计划阶段完全模板
3.CMMI3级软件过程改进方法与规范：包含立项、结项、规划、监控、风险管理、需求管理、需求开发、系统预研、设计、验收测试、系统测试、配置管理、质量保证、采购、培训等多个不同类型的文档模板，大家可以根据自己行业或者公司现状进行参考编写。
4.五大过程组项目模板
2021-05-25 22:06:04
2.19MB
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