DMF Practice Questions
Prepare for DMF with more than an answer.
- Exam fee
- $311 USD
- Level
- Multiple
- Valid for
- 3 years
Domains covered on the exam 14
- Data Management Process2%
- Data Ethics2%
- Big Data2%
- Data Architecture6%
- Data Modeling and Design11%
- Data Storage and Operations6%
- Data Security6%
- Data Integration and Interoperability6%
- Document and Content Management6%
- Master and Reference Data Management10%
- Data Warehousing and Business Intelligence10%
- Metadata Management11%
- Data Quality11%
- Data Governance11%
- 1
A data quality team is performing a root cause analysis on an issue where customer ages are frequently recorded as negative numbers. The investigation reveals that the data entry application has no validation rule to prevent this. This is an example of a failure in which aspect of data quality management?
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Correct answer: C
The root cause is the lack of a preventative control. A preventative control, such as an input validation rule in the application, is designed to stop data quality errors from occurring at the point of entry. Detective controls (like data profiling) find errors after they have occurred, and corrective controls (like data cleansing) fix them. The most effective approach is to prevent the error in the first place.
- 2
A key principle of effective data governance is to manage data as an enterprise asset.
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Correct answer: A
A fundamental tenet of data governance, as outlined in the DAMA-DMBOK, is the recognition and management of data as a valuable enterprise asset. This perspective drives the need for formal management, protection, and quality control, similar to how an organization manages its financial or physical assets.
- 3
Which of the following are characteristics of Big Data, often referred to as the '3 Vs'?
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Correct answer: A
The original and most common definition of Big Data is characterized by the '3 Vs': Volume (enormous scale of data), Velocity (high speed of data generation and processing), and Variety (diverse types of data, including structured, semi-structured, and unstructured).
- 4
A security administrator is tasked with protecting sensitive customer data stored in a database. The requirement is to make the data unreadable to anyone who might gain unauthorized access to the database files directly, but still allow authorized applications to read the data. Which security control should be implemented?
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Correct answer: C
Encryption at Rest is the process of encrypting data when it is stored on disk or in a database. This directly addresses the requirement to make the data unreadable if the physical files are compromised. Authorized applications, possessing the correct decryption keys, can access and decrypt the data for use. RBAC controls access but doesn't protect the stored files, and data masking creates a non-production version of the data.
- 5
A data architect is creating a conceptual data model for a university. The model needs to represent that a 'Student' can enroll in many 'Courses', and a 'Course' can have many 'Students' enrolled. How should this relationship be depicted in an Entity-Relationship Diagram (ERD)?
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Correct answer: C
The business rule clearly states a many-to-many cardinality: one student can have many courses, and one course can have many students. In a conceptual model, this is represented as a direct many-to-many relationship. In a logical or physical relational model, this would be resolved into an associative (or bridge) table, such as 'Enrollment'.
erDiagram STUDENT ||--|{ ENROLLMENT : "enrolls in" COURSE ||--|{ ENROLLMENT : "has" - 6
A financial services firm is establishing a data stewardship program. The initial debate is about the placement of data stewards within the organization. According to the DAMA-DMBOK, which organizational model is most effective for ensuring stewards are empowered to make decisions about data in their subject area?
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Correct answer: B
The DAMA-DMBOK advocates for data stewards to be sourced from and embedded within business units. This model ensures they have the subject matter expertise and are close to the data's creation and use, which is essential for defining business rules, assessing quality, and making authoritative decisions. Placing them in IT centralizes technical control but divorces them from business context.
- 7
During the logical data modeling phase for a new order management system, a data modeler has designed a table for
Ordersand a separate table forOrder_Items. To ensure that an item record cannot exist without a corresponding order record, what type of constraint must be implemented?Show answer details
Correct answer: D
A foreign key constraint establishes a link between two tables, enforcing referential integrity. In this case, making the
OrderIDin theOrder_Itemstable a foreign key that references theOrderIDprimary key in theOrderstable ensures that every record inOrder_Itemsmust have a valid, existingOrderIDin theOrderstable. - 8
A data architect is designing an enterprise data model and is deciding between a highly normalized model (3NF) and a dimensional model (star schema). The primary goal of the new system is to support ad-hoc querying and reporting for business analysts with minimal join complexity and fast response times. Which model should the architect choose and why?
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Correct answer: B
While a 3NF model is excellent for transactional systems (OLTP) due to its focus on data integrity and eliminating redundancy, it often requires many complex joins for reporting, which slows down queries. A dimensional model is specifically designed for analytical systems (OLAP) by organizing data into facts and dimensions. This denormalized structure simplifies queries (fewer joins) and is optimized for the fast read performance required by business analysts.
- 9
A data governance council is trying to build a business case for a metadata management initiative. Which of the following outcomes are direct benefits of a well-implemented metadata management program? (Select TWO)
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Correct answer: B, D
- 10
A retail company's marketing team pulls a customer list for a promotional campaign and finds numerous duplicate entries for the same individual, each with slightly different address information. This issue is a failure in which data quality dimension?
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Correct answer: C
The data quality dimension of Uniqueness ensures that there is only one representation of a single real-world entity in a dataset. The presence of duplicate entries for the same customer, even with minor variations, is a direct violation of this dimension. Completeness relates to missing data, and timeliness relates to data being up-to-date.
