Executive Summary
Get ready for your data governance exams with these tips. Learn about CDMP® certification requirements, professional writer exams, and exam strategies: master efficient study techniques and preparation methods. Understand the importance of data governance and stewardship, data quality, and best practices in business operations. Register for membership and explore quiz options.
Webinar Details
Title: How to Prepare for the Data Governance CDMP® Specialist Exams
Date: 04 August 2023
Presenter: Howard Diesel
Meetup Group: Data Professionals
Write-up Author: Howard Diesel
Contents
- Choosing the Right Specialist Exams for Data Governance
- Tips for Effective Exam Preparation in Data Science and Data Governance
- CDMP® Certification Requirements and Exams
- Important notes for the professional writer exam
- Exam Strategies and Success Criteria
- Tips for Efficiently Taking Multiple Choice Tests
- Efficient Study Techniques and Exam Preparation
- Overview of Data Governance Exam Levels and Content
- Data Governance Activities and Strategies
- Data Governance Best Practices and Definitions
- Data Governance in Business
- Data Governance and Data Stewardship
- The Importance of Data Quality in Business Operations
- Quiz Options and Completion
- Discussion on Course Content and Exam Preparation
- Data Governance Specialist Exam Preparation
- Registering for Membership
Choosing the Right Specialist Exams
To successfully pass the specialist exams, it is essential to thoroughly comprehend the in-depth knowledge covered in the fundamentals course. It is strongly advised to take the specialist exams only after completing the fundamentals course, as this will ensure that you are adequately prepared for the assessments. The specialist exams consist of questions that vary in complexity and the number of marks allotted.
Figure 1 The list of Specialist exams on offer to choose from
Figure 2 Choosing the right Specialist exam
Tips for Effective Exam Preparation in Data Science and Data Governance
Spending too much time learning big data and data science may not yield a significant return on investment for the exam. For associate-level exams, up to 60% of marks can be obtained through search and control. It is important to recognise the level of the exam question to efficiently allocate time and manage guessing and flagging techniques. Adobe is recommended for searching the Data Management Body of Knowledge (DMBOK) due to its better search capabilities than Edge or Chrome. Sample quizzes will be used to explain the data governance structure and assess knowledge and exam technique. Discussion and feedback on the sample quizzes will help identify challenges and clarify data governance exam expectations.
Figure 3 Tips for Effective Exam Preparation
CDMP® Certification Requirements and Exams
To obtain the CDMP® Associate level in Fundamentals, a score between 60 and 69 is required. The Associate level remains until all three levels (Fundamentals, Specialists) are completed. Scoring between 70 and 79 in the Fundamentals and both Specialities qualifies for the Practitioner level. The Master level requires an 80% or higher score in Fundamentals and both Specialist exams. The Data Management Fundamentals exam includes four and eleven marks, followed by Chapters (10 marks), six and two marks sections. The final CDMP® certificate displays Master, Practitioner, and Associate levels. An authorised CV submission is mandatory for CDMP® certification approval, costing $50. Warning points exist for the Fundamentals exam, particularly for Embark Version One questions.
Figure 4 CDMP® Certification Levels
Figure 5 Question list and numbers for the Data Management Fundamentals exam
Figure 6 Badgr.io Pathway
Figure 7 Exam warning points, take note!
Important notes for the professional writer exam
There are questions about the differences between DMBOK version one and version two, particularly regarding types of metadata. To assist with answering these questions, screenshots of the DMBOK version one section are available. When taking the exam, be cautious of negative questions that use “not” and double negatives. Additionally, consider scenarios with true/false answers and four distractors. If there is a communication failure or unstable internet connection, the timer may continue running during an exam pause. Lastly, when taking a video of your desk, clearly show one hard copy or one second device. If using a hard copy, do not use a second device, and if using a PDF on the second device, do not have a book on the desk.
Exam Strategies and Success Criteria
Before taking the exam, completing the Excel spreadsheet containing 321 questions is recommended. Answering all questions within an hour leads to a score of 60-65. However, additional studying is required to achieve a higher score and reach the Master’s level. Use DMBOK summary notes and DMBOK mind maps for studying. During the exam, set a timer for 60 minutes for the first pass without doing lookups or searching. The Standard Version allows for just over one minute per mark, avoiding wasting time searching. If uncertain about a question, flag it and guess, then move on to manage time efficiently.
Figure 8 CDMP Specialist Exam Critical Success Factors
Figure 9 Exam Technique
Tips for Efficiently Taking Multiple-Choice Tests
Be careful when answering questions on Canvas. Eliminate obviously incorrect answers and avoid using “always” and “never”. Flag questions you’re unsure about and contact support immediately if you experience any technical issues. After finishing the course, practice by answering test questions instead of reading the book.
Efficient Study Techniques and Exam Preparation
To succeed in the CDMP® exam, prioritise understanding, summarise content, utilise study materials, complete practice questions within a timeline, access additional resources, and take dedicated time to understand data governance categories and percentage marks.
Figure 10 Efficient Study Techniques and Exam Preparation for Success
Overview of Data Governance Exam Levels and Content
The speaker discusses the Data Management Body of Knowledge (DMBOK) and outlines the major and minor sections of the data governance exam, including organisation roles, responsibilities, and relationships with other knowledge areas. The exam has two difficulty levels: associate and practitioner, which emphasise understanding the content in the DMBOK and its practical application, respectively. Exam candidates are advised to prepare thoroughly before attempting the exam.
Figure 11 Data Governance Exam Categories
Figure 12 Data Governance Exam Categories Ranking
Figure 13 Data Governance Exam Question Difficulty
Data Governance Activities and Strategies
Effective data governance requires clear communication, a strong strategy, and a focus on compliance. Key components include a charter, roadmap, and metadata management. When setting up a data management office or governance team, assessing maturity, developing a strategy, understanding the operating model, and defining policies and procedures are critical. Data stewardship is crucial for operationalising data governance and requires training and support to ensure stewards understand and enforce activities in the data management process.
Figure 14 Data Governance Activities and Strategies
Data Governance Best Practices and Definitions
The importance of an incremental roadmap in achieving effective daily governance, alignment between the operating model, business model, and culture in data governance, understanding the data governance role in developing the data strategy, and the significance of risk management and security classification as key principles in data governance. Best practices include data anonymisation and avoiding the extremes of trying to solve all problems or putting too much responsibility on a committee. Additionally, change management needs to be addressed in data governance initiatives to ensure deliverables and added value. Technology alone cannot achieve a high level of data governance maturity, so building sustainable and ongoing processes and considering the impact of shadow systems is crucial. Leveraging business units and promoting self-service analytics can improve data governance. Finally, data governance can be defined as a system of decision rights and accountability roles and responsibilities, and the “Five Wives and one husband” (what, how, when, who, why) are important considerations in data governance management and improvement.
Figure 15 Data Governance Exam Standards and Best Practices
Figure 16 Data Governance Definitions
Data Governance in Business
Leveraging data as an asset requires people, processes, and technology. Data governance ensures quality control by managing, improving, and protecting data. Challenges arise with siloed applications and master data, and organisations must choose between an application-centred or data-centred approach. Siloed data governance implementations must give way to an enterprise-wide approach. Aggregating and consolidating data in an enterprise data warehouse requires clear business definitions and an understanding key performance indicators (KPIs). Clear roles and responsibilities are crucial in data governance, and the operating model must align with the business model.
Figure 17 The Importance of Data Governance, What creates the demand
Figure 18 How Data Governance fits into Organisations, Roles and Responsibilities
Data Governance and Data Stewardship
The different types of data stewards include executive data stewards, data owners, and data coordinating stewards. Their primary focus is data governance, which involves setting up different governance structures like federated, centralised, decentralised, hybrid, and replicated and understanding the pros and cons of each structure. Data governance is responsible for defining data and identifying assets, while data management focuses on doing things right. Different roles and responsibilities exist for data stewards, and data modellers have specific requirements for data stewards.
The Importance of Data Quality in Business Operations
To achieve successful data management, it is imperative to have a robust team of specialists who are experts in various key components. These include data quality, which ensures that the data is accurate, consistent, and reliable. Data integration is another crucial component, combining data from multiple sources into a unified view. The incremental rollout is also important, as it allows for the gradual implementation of new data management processes and technologies. Additionally, it is important to have strategic alignment, which involves aligning data management goals with broader business objectives. Assessments and benchmarking are also critical, as they help identify improvement areas and measure progress over time. Maturity assessment is important for understanding the current state of data management and identifying areas for improvement. Lastly, daily governance ensures that data is managed effectively on a day-to-day basis and that any issues are addressed promptly.
Figure 19 Program and Scope
Figure 20 Data Management Assessments
Quiz Options and Completion
Choose between two quizzes: one with 31 questions in 10 minutes and another with 15 questions. They are classified as Specialist Master Level and Speed Dating quizzes, respectively. Participants should select the quiz that matches their confidence and interests. Participants who have taken data governance training will be granted access to the training materials.
Discussion on Course Content and Exam Preparation
The course is divided into sections with questions weighted accordingly. The questions are more suited for practitioners than for the Master’s level. The data governance section is challenging to understand. GDPR compliance and ethics are important areas to focus on. Reviewing GDPR materials will be helpful for the exam. Understanding different categories is crucial for success.
Figure 21 Data Governance Speciality Exam Warning Points
Data Governance Specialist Exam Preparation
The specialist exam covers the Data Management Body of Knowledge (DMBOK), including the data governance chapter and related chapters 1, 2, and 17. The Fundamentals exam excludes chapters 15, 16, and 17. The Data Governance Specialist exam focuses on chapters 15, 16, and 17. Summary points help with understanding and categorising activities and best practices. Success requires good exam technique and a willingness to revise. Data governance courses cover other knowledge areas with many exam questions, such as data modelling, data stewards, definitions, and business rules. Modelware offers training courses in data modelling, data quality, governance, analysis, and planning. Be aware of the new architecture plan course. Dataversity and Chris Bradley offer courses for $1500 per person for early bird registration and $1800 for late registration. Fitz Academy’s courses cost R1311 per course. Modelware Systems offers a three-day and a two-day course together. (see below)
During the Modelware Systems’ five-day course, participants will have the opportunity to gain a deeper understanding of the maturity assessment process and develop their data modelling skills through real-world examples. Additionally, South African members who pass the exam will be eligible for rebates.
Figure 22 Exam Critical Success Factors
Figure 23 Modelware Systems Training Courses
Figure 24 Recommended Training Courses (visit our training page or contact our team for updated dates)
Registering for Membership
To register for membership, send an email to membership@dama.org.za. Abita is the contact person in charge of membership. Melinda and Paul will assist with registrations soon. Mention registration in the email, and we’ll complete it. Thank you for your cooperation.
If you would like to join the discussion, please visit our community platform, the Data Professional Expedition.
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If you would like to be a guest speaker on a future webinar, kindly contact Debbie (social@modelwaresystems.com)
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