**Update 8/15: it’s recently come to my attention that the certification exams are open book, which is extremely exciting because it means less time memorizing and more time working with data in a real world setting. Also, I am starting a study group on Facebook — join for help with your exam prep.**

** Update 8/15 ：最近引起我注意的是，认证考试是一本 公开的书 ，这非常令人兴奋，因为它意味着更少的时间记忆和更多的时间在真实环境中处理数据。 另外，我正在 Facebook上成立 一个 研究小组 —加入考试准备中的帮助。**

Eight years ago, data science was proclaimed “the sexiest job of the 21st century.” Yet plodding through hours of data munging still feels decidedly unsexy. If anything, the storied rise of the data science career has illustrated just how poorly most organizations are doing when it comes to managing their data.

八年前，数据科学被誉为“ 21世纪最性感的工作”。 然而，经过数小时的数据处理，仍然感觉绝对不 性感 。 如果有的话，数据科学事业的传奇般的崛起说明了大多数组织在管理数据方面做得多么糟糕。

Enter the Certified Data Management Professional (CDMP) from Data Management Association International (DAMA). The CDMP is the best data strategy certification you’ve never heard of. (And honestly, when you consider the fact that you’re probably working a job that didn’t exist ten years ago, it’s not surprising that this certification isn’t widespread just yet.)

输入认证的数据管理专业人员( CDMP从数据管理协会国际)( DAMA )。 CDMP是您从未听说过的最佳数据策略认证。 (说实话，当您考虑到自己从事的工作可能是十年前不存在的事实时，这种认证还没有广泛传播就不足为奇了。)

Data strategy is a crucial discipline that spans end-to-end management of the data lifecycle as well as associated aspects of data governance and key considerations of data ethics.

数据策略是一门至关重要的学科，它涵盖了数据生命周期的端到端管理以及数据治理的相关方面以及数据伦理的关键考虑因素。

This article outlines the hows and whys of getting the CDMP, which lays the groundwork for effective thought leadership on data strategy. It also includes a survey — you can offer your thoughts on the most important aspects of data management for data science and check out the consensus of the community.

本文概述了获取CDMP的方式和原因 ，这为有效地领导数据策略思想奠定了基础。 它还包括一项调查-您可以就数据科学中数据管理最重要的方面提出您的想法，并查看社区的共识。

In this guide:

在本指南中 ：

1. About the CDMP Exam

   关于CDMP考试

2. How to prepare for CDMP

   如何准备CDMP

3. What’s tested on the CDMP

   在CDMP上测试了什么

4. Survey —most important aspect of data management

   调查-数据管理的最重要方面

5. Why data scientists should get CDMP certified

   为什么数据科学家应该获得CDMP认证

Disclaimer: this post is not sponsored by DAMA International — views reflected are mine alone. I’m including an affiliate link to the DMBOK on Amazon, the reference guide that is required for the exam, given that it’s an open book test. Buying the exam through this link helps support my writing on Data Science and Data Strategy — thanks in advance.

免责声明 ：本帖子并非由DAMA International赞助-所反映的观点仅属于我个人。 考虑到这是一项开放式考试，因此 我会提供指向 亚马逊 DMBOK 的会员链接 ，这是考试所需的参考指南。 通过此链接购买考试有助于支持我写的有关数据科学和数据策略的文章-预先感谢。

关于CDMP考试 (About the CDMP Exam)

Training for the CDMP confers expertise across 14 areas related to data strategy (which I’ll cover in more detail in a later section). The test is open book, but the 100 questions on the exam must be completed within 90 minutes — not a lot of time to be looking things up. Therefore, it’s important to be extremely familiar with the reference material.

CDMP培训将赋予与数据策略相关的14个领域的专业知识(我将在下一部分中对其进行详细介绍)。 该考试是公开考试，但考试中的100个问题必须在90分钟内完成-查起来的时间不多。 因此，非常熟悉参考资料很重要 。

When you schedule the exam ($300), DAMA provides 40 practice questions that are pretty reflective of the difficulty of the actual exam. As a further resource, check out this article about the process of studying for a certification.

当您安排考试(300美元)时，DAMA提供了40个练习题，完全可以反映实际考试的难度。 作为进一步的资源， 请查阅有关认证学习过程的本文 。

It’s possible to sit for the exam online while monitored via webcam ($11 proctoring fee). The format of the exam is multiple choice — either 5 options or T/F. You can mark questions and come back to them. At the conclusion of test taking, you get immediate feedback on your score.

可以在线参加考试，同时通过网络摄像头进行监控(收取11美元的手续费)。 考试形式为多项选择-5种选择或T / F。 您可以标记问题，然后再返回。 考试结束时，您会立即获得有关分数的反馈。

Anything over 60% is considered passing. This is just fine if you’re interested in getting your CDMP Associate certification and moving along. If you’re interested in the advanced tiers of CDMP certification, you’ll have to pass with a 70% (CDMP Practitioner) or 80% (CDMP Master). To get certified at the highest level, CDMP Fellow, you’ll need to attain the Master Certification and also demonstrate industry experience and contribution to the field. Each of these advanced certifications also require passing two Specialist exams.

超过60％的都被视为通过 。 如果您有兴趣获得CDMP协会认证并继续前进，那很好。 如果您对CDMP认证的高级层感兴趣，则必须通过70％(CDMP从业者)或80％(CDMP Master)。 要获得最高级别的CDMP研究员认证，您需要获得Master认证，还需要证明行业经验和对该领域的贡献。 这些高级认证中的每一个都还需要通过两次专家考试 。

This brings me to my final point, which is about why — purely from a career advancement standpoint — you should chose to put yourself through the studying and exam taking process for CDMP: certification from DAMA is associated with high-end positions in leadership, management, and data architecture. (Think of CDMP as getting credentialed into a semi-secret society of data ninjas.) Increasingly, enterprise roles and federal contracts related to data management are requesting CDMP certification. Read more.

这将我带到了最后一点，这就是为什么-从职业发展的角度出发-您应该选择通过CDMP的学习和考试过程：DAMA的认证与领导，管理的高端职位相关联，以及数据架构。 (认为​​CDMP已成为进入数据忍者半秘密社会的凭证。)越来越多的企业角色和与数据管理相关的联邦合同正在要求CDMP认证。 。

Pros:

优点 ：

• Provides well-rounded knowledge base on topics related to data strategy提供与数据策略相关主题的全面的知识库
• Open book test means less time spent on route memorization开卷考试意味着更少的时间记忆在路线上
• Four tiers for different levels of data management professionals针对不同级别的数据管理专业人员的四层
• 60% score requirement to pass lowest level of certification分数要求达到60％才能通过最低级别的认证
• Associated with elite roles与精英角色相关
• Provides 3 year membership to DAMA International提供DAMA International的3年会员资格
• $311 exam fee is cheaper than other data-related certifications from Microsoft and The Open Group311美元的考试费比Microsoft和The Open Group的其他与数据相关的认证便宜

Cons:

缺点 ：

• DAMA is not backed by a major tech company (e.g. Amazon, Google, Microsoft) that is actively pushing marketing efforts and driving brand recognition for CDMP certification — this means that CDMP is likely to be recognized as valuable mainly among individuals who are already familiar with data managementDAMA不受大型科技公司(例如亚马逊，谷歌，微软)的支持，该公司正在积极推动营销工作并推动CDMP认证的品牌认可-这意味着CDMP可能主要在已经熟悉的个人中被认为是有价值的数据管理

• $311 exam fee is relatively expensive compared to AWS Cloud Practitioner cert ($100) or GPC certs ($200)

  与AWS Cloud Practitioner证书 ($ 100)或GPC证书 ($ 200)相比，$ 311考试费相对昂贵。

Alternatives:

替代方案 ：

• Microsoft Certified Solutions Associate (MCSA) — modularized certifications focusing on various Microsoft products ($330+)

  Microsoft认证解决方案合作伙伴 ( MCSA )-着重于各种Microsoft产品的模块化认证(超过$ 330)

• Microsoft Certified Solutions Expert (MCSE) — builds on the MCSA with integrated certifications on topics such as Core Infrastructure, Data Management & Analytics, and Productivity ($495+)

  Microsoft认证解决方案专家 ( MCSE )—以MCSA为基础 ，并具有针对诸如核心基础架构 ， 数据管理和分析以及生产力的主题的集成认证(超过$ 495)

• The Open Group Architecture Framework (TOGAF) —various levels of certification on high-level framework for software development and enterprise architecture methodology ($550+)

  开放组架构框架 ( TOGAF )-用于软件开发和企业架构方法的高级框架的各种级别的认证(超过$ 550)

• Scaled Agile Framework (SAFe) — role-based certifications for software engineering teams ($995)

  可扩展的敏捷框架 ( SAFe )—针对软件工程团队的基于角色的认证(995美元)

如何准备CDMP (How to prepare for CDMP)

Given that CDMP is an open book test, to study for the exam, all that’s needed is the DAMA Body of Knowledge book (DMBOK $55). It’s around 600 pages, but if you mainly focus your study time on Chapter 1 (Data Management), diagrams & schemas, roles & responsibilities, and definitions, then this should get you 80% of the way toward a passing score.

鉴于CDMP是公开考试，要学习考试，只需要DAMA知识体系书( DMBOK， 55美元)。 它大约有600页 ，但是如果您主要将学习时间集中在第1章(数据管理)，图表和模式，角色和职责以及定义上，那么这将使您获得80分的分数。

In terms of how to use DMBOK, one test taker recommended 4–6 hours per weekend for 8–10 weeks. Another approach could be reading a couple pages each morning and evening. However you tackle it, make sure you’re incorporating spaced repetition into your studying methodology.

在如何使用DMBOK方面 ，一位应试者建议每个周末4-6小时，持续8-10周。 另一种方法是每天早晨和晚上阅读几页。 无论您如何解决，请确保将间隔重复纳入您的学习方法中。

In addition to being your study guide for the exam, the DMBOK is of course useful as reference book, and you can drop it on your colleague’s desk if they need to learn data strategy or if they’ve nodded off during a webinar.

除了作为考试的学习指南之外， DMBOK当然也可以作为参考书，如果您的同事需要学习数据策略或在网络研讨会期间点了点头，您可以将其放在同事的桌子上。

在CDMP上测试了什么 (What’s tested on the CDMP)

The CDMP covers 14 topics —I’ve listed them in order of the prevalence with which they occur on the exam and provided a brief definition for each.

CDMP涵盖了14个主题-我按考试中的普遍性顺序列出了它们，并为每个主题提供了简要定义。

Data Governance ( 11%) — practices and processes to ensure formal management of data assets. Read more.

数据治理 (11％)-确保对数据资产进行正式管理的实践和流程。 。

Data Quality ( 11%) — assuring data is fit for consumption based on its accuracy, completeness, consistency, integrity, reasonability, timeliness, uniqueness/deduplication, validity, and accessibility. Read more.

数据质量 (11％)-根据数据的准确性，完整性，一致性，完整性，合理性，及时性，唯一性/重复数据删除，有效性和可访问性，确保数据适合消费。 。

Data Modelling and Design ( 11%) — translation of business needs into technical specifications. Read more.

数据建模和设计 (11％)-将业务需求转换为技术规范。 。

Metadata Management (11%) — information about data collected. Read more.

元数据管理 (11％)-有关收集的数据的信息。 。

Master and Reference Data Management (10%) — reference data is information used to categorize other data found in a database, or information that is solely for relating data in a database to information beyond the boundaries of the organization. Master reference data refers to information that is shared across a number of systems within the organization. Read more.

主数据和参考数据管理 (10％)-参考数据是用于对数据库中找到的其他数据进行分类的信息，或仅用于将数据库中的数据与组织范围之外的信息相关联的信息。 主参考数据是指在组织内的多个系统之间共享的信息。 。

Data Warehousing and Business Intelligence (10%) — a data warehouse stores information from operational systems (as well as other data resources, potentially) in a way that is optimized to support decision-making processes. Business intelligence refers to the use of technology to gather and analyze data, then translate it into useful information. Read more.

数据仓库和商业智能 (10％)- 数据仓库以一种优化的方式存储来自操作系统(以及潜在的其他数据资源)的信息，以支持决策流程。 商业智能是指使用技术来收集和分析数据，然后将其转换为有用的信息。 。

Document and Content Management (6%) — technologies, methods, and tools used to organize and store an organization’s documents. Read more.

文档和内容管理 (6％)-用于组织和存储组织文档的技术，方法和工具。 。

Data Integration and Interoperability ( 6%) — use of technical and business processes to merge data from different sources, with the goal of readily and efficiently providing access to valuable information. Read more.

数据集成和互操作性 (6％)-使用技术和业务流程来合并来自不同来源的数据，目的是容易而有效地提供对有价值信息的访问。 。

Data Architecture (6%) — specifications to describe existing state, define data requirements, guide data integration, and control data assets, according to the organization’s data strategy. Read more.

数据体系结构 (6％)-根据组织的数据策略，用于描述现有状态，定义数据需求，指导数据集成和控制数据资产的规范。 。

Data Security ( 6%) — implementation of policies and procedures to ensure people and things take the right actions with data and information assets, even in the presence of malicious inputs. Read more.

数据安全性 (6％)-实施政策和程序以确保人和物即使在存在恶意输入的情况下也对数据和信息资产采取正确的措施。 。

Data Storage and Operations ( 6%) — characterization of hardware or software that holds, deletes, backs up, organizes, and secures an organization’s information. Read more.

数据存储和运营 (6％)-表征，保存，删除，备份，组织和保护组织信息的硬件或软件。 。

Data Management Process ( 2%) — end-to-end management of data, including collection, control, protection, delivery, and enhancement. Read more.

数据管理流程 (2％)-数据的端到端管理，包括收集，控制，保护，交付和增强。 。

Big Data ( 2%) — extremely large datasets, often composed of various structured, unstructured, and semi-structured data types. Read more.

大数据 (2％)-极大的数据集，通常由各种结构化，非结构化和半结构化数据类型组成。 。

Data Ethics ( 2%) — code of conduct encompassing data handling, algorithms, and other practices to ensure that data is used appropriately in a moral context. Read more.

数据道德 (2％)-包含数据处理，算法和其他实践的行为准则，以确保在道德环境中正确使用数据。 。

调查 (Survey)

Out of curiosity, I’d love to hear your thoughts about the most important aspect of data management. After you make your selection in the poll below, you’ll see what the community thinks as well.

出于好奇，我很想听听您对数据管理最重要方面的想法 。 在下面的民意调查中做出选择后，您还将看到社区的想法。

What considerations drove your choice? Do you think studying for CDMP is an effective way to learn these topics? Let’s talk in the comments.

哪些因素促使您选择？ 您认为学习CDMP是学习这些主题的有效方法吗？ 让我们在评论中谈谈。

为什么数据科学家应该获得CDMP认证 (Why data scientists should get CDMP certified)

Still not convinced why data strategy is important? Let’s take a look from the perspective of a data scientist aiming to increase their knowledge and earning potential.

仍然不确定为什么数据策略很重要？ 让我们从旨在增加他们的知识和创收潜力的数据科学家的角度来看一下。

It’s been said that a data scientist sits at the nexus of statistics, computer science, and domain knowledge. Why would you want to add one more thing to your plate?

有人说数据科学家坐在统计，计算机科学和领域知识之间。 您为什么要在盘子里再添加一件事？

Successwise, you’re better off being good at two complementary skills than being excellent at one

成功地，与拥有一项相辅相成的技能相比，您最好拥有两项相辅相成的技能

Scott Adams, author and creator of the Dilbert comics, offers the idea that “every skill you acquire doubles your odds of success.” He acknowledges this may be somewhat of an oversimplification — “obviously some skills are more valuable than others, and the twelfth skill you acquire might have less value than each of the first eleven” — but the point is that sometimes it’s better to go wide than to go deep.

迪尔伯特漫画的作者和创作者斯科特·亚当斯 ( Scott Adams) 提出这样的想法 ：“您获得的每一项技能都会使成功几率翻倍。” 他承认这可能是过于简单化了几分的- “明显有些技能是比其他人更有价值，第十二技能，你获得可能具有彼此前十的价值不大” -但问题是，有时， 最好 去宽比去深入。

Setting aside the relative magnitude of the benefit (because I seriously doubt it’s 2x per skill… thank you, law of diminishing marginal returns), it seems unquestionable that broadening your skillset can lead to more significant gains relative to toiling away at learning one specific skills. In a nutshell, this is why I think it’s important for a data scientist to learn data strategy.

抛开收益的相对幅度(因为我非常怀疑每项技能是2倍……谢谢，边际收益递减的规律)，相对于辛苦学习一种特定技能，扩大技能范围似乎可以带来更大的收益，这是毫无疑问的。 简而言之，这就是为什么我认为对于数据科学家来说学习数据策略很重要。

Generally speaking, having diversity in your skillset allows you to:

一般来说， 技能组合的多样性可以使您：

1. Problem solve more effectively by drawing on cross-disciplinary learnings

   通过跨学科学习，更有效地解决问题

2. Communicate better with your teammates from other specialties

   与其他专业的队友更好地沟通

3. Get your foot in the door in terms of gaining access to new projects

   进入新项目方面， 踏上大门

Understanding data strategy transforms you from being a data consumer into an empowered data advocate at your organization. It’s worth putting up with all the tongue twister acronyms (DMBOK — really? Couldn’t they have just called it The Data Management Book?) in order to deepen your appreciation for the end-to-end knowledge generating process.

了解数据策略可以使您从成为数据使用者转变为组织中的授权数据拥护者 。 为了加深您对端到端知识生成过程的理解，值得使用所有绕口令的缩写( DMBOK-真的吗？他们难道就没有将其称为“数据管理书”吗？ ) 。

其他使您的技能多样化的文章 (Other articles to diversify your skills)

If you enjoyed reading this article, follow me on Medium, LinkedIn, and Twitter for more ideas to advance your data science skills. Join the study group for the CDMP Exam.

如果您喜欢阅读本文 ，请在Medium ， LinkedIn和Twitter上关注我，以获取更多提高您的数据科学技能的想法。 加入CDMP考试学习组 。