A. Do
B. All of the above
C. Utilization
D. Act
E. Check
F. Plan
A. Formalization
B. Scope definition
C. Knowledge retention/documentation
D. Normalization
A. Ancestral origin of data DNA
B. The capture and maintenance of source structures for each attribute on the datamodel
C. Scope for reporting requirements
D. A temporal distortion of data values across systems
E. A clean line between columns in the same entity
A. Specify
B. Maintain & Use
C. Enable
D. Plan
E. Create & Acquire
A. Business metadata
B. Business requirements
C. Metadata standards
D. Process Metadata
E. Technical metadata
A. Data architecture
B. DQM Procedures
C. Data governance
D. Data quality Service Level Agreements
E. Analyses from data profiling
F. DQ Policies and guidelines
A. Make the integration between data management and data analytics possible
B. Ensuring effective and efficient retrieval and use of data and information in unstructured formats
C. Managing the performance of data transactions
D. Enduring integration competencies between semi-structured systems
E. Complying with legal obligations and customer expectations
F. Ensuring integration capabilities between structured and unstructured data
A. Disk space on the big data platform
B. Quality data modelers
C. Integration of the dictionaries to achieve common understanding
D. Conflict between software vendors
E. Common data types in the source datasets
A. Business readiness
B. Vision alignment
C. Business sponsorship
D. Linear symmetry
E. A consistent line across display methods
F. A clear and consistent focus
A. FALSE
B. TRUE
A. Control
B. Accountable
C. Informed
D. Responsible
E. Consulted
F. Reliable
