The Certified Data Management Professional (CDMP) exam confers excellence in the field of Data Strategy, a much-needed discipline in our data-rich world. The credential is extremely relevant in today’s job marketplace. CDMP is associated with high-level leadership positions. It’s also recognized by potential clients across the commercial and governmental spheres as indicating deep knowledge of Data Management. And if you’re just setting out on your data-related career journey, the CDMP is a great place to get started.
Study Tips
💌 Sign up for the CDMP Study Plan. This will help you maximize your time and energy while preparing for the test. Each week covers a different chapter or chapters of the DMBOK with key takeaways, vocabulary, and study guides you can print and use during the test. The study schedule leverages the 80/20 rule to keep you focused on the most important content likely to appear on the exam. And because certification is about more than getting top marks on the exam, the study plan includes thoughtful external resources, additional reading, and preparation for a career as a data professional.
📘 Buy the DMBOK 2nd ed. The exam is open book and the DMBOK is legitimately super useful as a reference for Data Management work. The DMBOK occupies a prime position on my desk — I frequently find myself referencing my highlights and sticky notes to address clients’ questions.
❓ Buy the CDMP exam. You have an unlimited amount of time to schedule the test date, and paying for the exam gives you access to a test bank of 200 questions that simulate the real exam.
🔖 Highlight and sticky note the DMBOK. Okay, this one’s obvious for an open book test. You’ll definitely want to use a highlighter and sticky notes to indicate key concepts. I put all sticky notes on one side of the book for easy referencing. I also recommend orienting your writing sideways on the tabs so they don’t stick out of the book as far.
❗️Indicate the start of each chapter. Use wide sticky notes or notes of a specific color to mark the start of each chapter. This was invaluable during the test to quickly find content associated with a specific topic.
🔨 Work with the chapter framework. All the chapters of the DMBOK follow the structure Introduction, Activities, Tools, Techniques, Implementation Guidelines, Governance, Works Cited / Recommended. Focus your studying on the overview and technical sections that get more play on the exam relative to implementation and organizational sections.
💙 Read in order then review by priority. The topics of the DMBOK are arranged in an intuitive order — the sequence you might assess these topics during a Data Management engagement. However, the proportion of each of the 14 topics tested on the exam ranges from 11% for foundational areas such as Data Governance to 2% for advanced activities such as Big Data. On your second reading of the DMBOK, I recommend studying in the priority order covered in this post.
⭐️ Join the CDMP Study Group. Use this community to compare notes, ask questions, and find study partners.
Study Topics
The CDMP covers 14 topics of the DMBOK —I’ve listed them in order of the prevalence with which they occur on the exam and provided a brief definition for each.
Data Governance (11%) — practices and processes to ensure formal management of data assets. Read more.
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.
Data Modeling and Design (11%) — translation of business needs into technical specifications. Read more.
Metadata Management (11%) — information about data collected. Read more.
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.
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.
Document and Content Management (6%) — technologies, methods, and tools used to organize and store an organization’s documents. Read more.
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.
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.
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.
Data Storage and Operations (6%) — characterization of hardware or software that holds, deletes, backs up, organizes, and secures an organization’s information. Read more.
Data Management Process (2%) — end-to-end management of data, including collection, control, protection, delivery, and enhancement. Read more.
Big Data (2%) — extremely large datasets, often composed of various structured, unstructured, and semi-structured data types. Read more.
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.