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WorksheetsData Governance and Management Quiz
Total questions: 148
Worksheet time: 1hrs 14mins
What is the primary focus of data governance?
Implementing new technologies
Establishing rules and responsibilities for data management
Analyzing market trends
Creating data visualizations
According to DAMA International, what is Data Governance?
The technical aspects of data management
The exercise of authority and control over data assets
A system of data storage
The process of data analysis
According to the Data Governance Institute, what is Data Governance?
A set of software tools
A system of decision rights and accountabilities for information-related processes
The act of data collection
A method for data visualization
According to Gartner, what is Data Governance?
A framework for data storage
The specification of decision rights and an accountability framework
The process of data analysis
A method for data visualization
What is a simplified explanation of Data Governance?
Data storage and backup procedures
Rules, processes, and accountability that allow an organization to better manage its data
Data analysis and reporting
Implementing new data technologies
What is the primary goal of data management?
To create complex data visualizations
To develop new software applications
To deliver, control, protect, and enhance the value of data assets
To maintain network infrastructure
According to DAMA International, what does Data Management include?
Only the technical aspects of data storage
The development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles
Primarily data visualization and reporting
Just the initial collection of data
What does a Data Management Professional do?
Focuses only on the technical aspects of data
Works in any facet of data management to meet strategic organizational goals
Works only on the business side of data
Is only involved in data visualization
What is a key principle of data management?
Data is inexpensive to maintain
Data is an asset with unique properties
Data management is primarily an IT concern
Data management does not require planning
What is a key element of effective data management?
It is solely a technical process.
It is independent of business requirements.
It requires leadership commitment.
It does not need metadata to manage data.
What does effective data management require?
Data management requirements must be independent of IT decisions
Data management is purely a technical function
Leadership commitment
Data is not valuable
Which of the following is a key data management principle?
Data management is a technical function only
Data management requirements are business requirements
Data management is independent of business goals
Data has no value
What is the relationship between Data Governance and Data Management?
They are the same thing.
Data Governance sets the rules, Data Management executes them.
Data Management sets the rules, Data Governance executes them.
They are unrelated.
What is the role of Data Governance in relation to data management?
To focus on technical processes for data storage.
To ensure data is used unethically and inconsistently.
To define policies, standards, and accountability for data usage and compliance
To make data less accessible
What is the role of Data Management in relation to data governance?
To set policies and standards for data use.
To focus only on ethical data use.
To execute technical processes to manage, store, and secure data.
To ignore data accessibility.
What is the focus of Data Governance?
Ensuring data is only accessible to technical staff
Ensuring data is used ethically, consistently, and in line with regulations
Focusing on the technical infrastructure for data
Data storage
What is the focus of Data Management?
Data usage
Ensuring data is high quality, accessible, and fit for business use
Setting data usage policies
Ethical standards
Which of these best describes a Data Management Framework?
A specific data storage system
Conceptual models that describe the components, relationships, and processes of data management
A detailed data analysis report
A type of data visualization
What is the purpose of a Data Management Framework?
To create data silos
To manage only technical processes.
To align data management activities with strategic goals
To complicate data management
Data Management Frameworks help to establish:
Data silos
Common terminology, standards, and best practices for data management
Technical processes only
A new data visualization technology
What is the starting point of the Data Management Function Framework?
Storing data
Data analysis
Enabling organizations to get value from their data assets
Data security
In the Data Management Function Framework, what is depicted in the center of the diagram?
Oversight activities
Foundational activities
Lifecycle management functions
Data governance activities
According to the Data Management Function Framework, what activities span the entire data lifecycle?
Data modeling
Data storage
Foundational activities like risk management, metadata, and data quality management
Data monetization
What is the role of Data Governance in the Data Management Function Framework?
To focus on technical aspects of data
To solely support the data lifecycle
To provide oversight and ensure foundational activities are executed with discipline.
To manage data storage only
What does a Data Governance program enable an organization to do?
Become less data-driven
Only focus on direct lifecycle functions
Be data-driven by implementing strategy, principles, policies, and stewardship practices
Focus only on data storage and technical aspects
What is the DMBOK?
A type of data visualization
A data storage system
Data Management Body of Knowledge
A data analysis tool
What is one purpose of DMBOK?
To complicate data management
Providing a functional framework for the implementation of enterprise data management practices
To promote data silos
To be the basis of non-certified data management professionals
What is the relationship between Data Governance and Data Management?
They are the same thing.
Data Governance establishes the policies, while Data Management enforces them.
Data Management establishes the policies, while Data Governance enforces them.
They are unrelated.
What is the strategy in relation to implementation in the context of Data Governance and Data Management?
Data Management is the strategy, and Data Governance is the implementation.
Data Governance is the strategy, and Data Management is the implementation.
Strategy and implementation are not related to them.
There is no strategy or implementation.
According to the sources, what is the definition of Data Governance?
A set of technical tools
The exercise of authority and control over the management of data assets.
A process for data storage
The process of data analysis
What does a formal Data Governance program allow an organization to do?
To decrease the value of data assets.
To make decisions about data with less intentionality
Increase the value they get from their data assets
Focus only on technical aspects of data
According to the sources, what is the overall driver of data management?
To make data more complex
To store as much data as possible
Ensuring an organization gets value out of its data
To make data less accessible
What does Data Governance focus on?
How to store data most efficiently
How decisions are made about data and how people and processes are expected to behave in relation to data
Only the technical aspects of data management
Data visualization
What is included in the scope of a Data Governance Program?
Strategy, policy and standards
Oversight and compliance
Issue management
All of the above
What is the role of Data Governance in relation to data privacy?
To ignore data privacy rules.
To not enforce compliance and monitoring
To control private/confidential/PII through policy and compliance monitoring
Data storage only
What is a benefit of improved data quality, according to the sources?
Increased data storage costs
Less reliable data
Improved business performance
Data breaches
What does Metadata management help to establish?
Data silos
Data complexity
A business glossary to define and locate data in the organization
Data inaccessibility
What is the aim of SDLC improvements in relation to Data Governance?
To slow down development projects.
To address issues and opportunities in data management across the organization
To ignore data-specific technical debt
Data breaches
What is a purpose of Data Governance in vendor management?
To create more contracts related to data
To control contracts dealing with data
To ignore contracts related to data.
To create confusion about contracts
What is a consequence of transitioning to cloud environments?
More control over data
Less control over data
Less data volume
Simpler management of data.
Why is Data Governance important, according to the sources?
Because data is always clean.
Because data governance ensures data is managed effectively.
Why is Data Governance important, according to the sources?
Because data is always clean.
Because data is never messy.
Because executives realize data is a mess and want it cleaned up
Because executives are uninterested in data
What is a key outcome of focusing on Data Governance and ethics?
That business relies on separate excel files
Data is not used as an asset
That the Data Strategy should empower the business to harness data effectively
That dashboards do not get used
What should the Data Strategy empower the business to do?
To ignore data.
To use data ineffectively.
To harness data effectively
To create data silos.
According to the sources, who should take the lead in managing the organization's data?
Only the IT department.
Data analysts only
The business
Technical staff only
What are crucial drivers of Data Governance?
Lack of communication
Negative company culture
Effective communication, a positive company culture, and embrace change management
Resistance to change.
What is a key factor driving the evolution of Data Governance?
Less regulations
Boom of data protection regulations.
Fewer data management best practices
Fewer compliance requirements.
What was a key regulation mentioned in the sources related to Data Governance?
The 2010 California Consumer Privacy Act
The 2005 Personal Information Protection and Electronic Documents Act
The 2018 General Data Protection Regulation (GDPR)
Basel Committee on Banking Supervision
What is the main goal of data governance in relation to regulations?
To make compliance more difficult
To ignore data protection laws.
To operationalize Data Protection Laws & Regulations.
To make data less secure
What is a key driver for Data Governance according to the sources?
Data silos.
Privacy and Regulation Compliance
Lack of customer experience
Increased costs
What is another key driver for Data Governance according to the sources?
Data redundancy
Data-driven decision paralysis
Data-Driven Decision Making
Data breaches
What is another key driver for Data Governance according to the sources?
Decreased customer experience
Distrust in data
Enhance Customer Experience and user Trust in Data
Reduced security
What is another key driver for Data Governance according to the sources?
Increased costs
Reduced efficiency
Reducing Costs and Operational Efficiency
Slower processes
What can be a result of a lack of common data definitions?
Clear and accurate data
Reworks due to a mistake
Faster processes
Efficient workflows
What does a Business Glossary act as?
A tool for data breaches.
A source of confusion and inconsistency
A comprehensive reference guide that defines the key concepts, data elements, metrics, and other business terms used in the organization.
A method for data silos.
What does a Data Dictionary act as?
A guide to creating data silos.
A tool for data breaches.
A centralized resource that documents the meaning, characteristics, and relationships of various data elements used in different systems and databases.
A source of confusion and inconsistency.
What does a Data Quality Issue Resolution Process do?
Creates data quality issues
Ignores data quality issues
Addresses and rectifies data quality issues systematically.
Confuses data quality issues
What does a Data Governance Policy ensure?
That data is handled inconsistently
Data is insecure
That data is handled consistently, securely, and in alignment with organizational goals and regulatory requirements.
Data is not aligned with organizational goals
What does validation of datasets and reports ensure?
Data inaccuracy
Unreliable data
The accuracy, reliability, and integrity of data and the reports generated from that data
Inconsistent data
What does a Data Governance Operating Model provide?
A complex and unstructured approach to data management
A framework that does not need managing
A structured framework that defines how an organization's data governance program is structured, organized, and managed
A method for inconsistency and unreliability
What do DG Roles & Responsibilities define?
No specific duties or accountabilities
Duties that are not related to data assets
Specific duties and accountabilities assigned to individuals or groups to ensure the effective management, protection, and utilization of data assets
Duties and accountabilities that do not protect data
According to the sources, what does deploying Data Governance allow enterprises to do?
Make a company less data driven
Create more data silos
Transform a company into a data-driven company and structure and automate processes across multiple organizations and stakeholders
Increase costs
What is a key component to consider when designing a Data Strategy & Governance Strategy?
Focusing on technical aspects
Alignment with the Organization's Objectives & Drivers
Ignoring organizational objectives
Creating complexity.
What is one thing that a detailed and modular Data Maturity Assessment allows businesses to do?
Create data silos.
Construct a data strategy with a holistic enterprise viewpoint.
Ignore the organization's priorities.
Increase compliance discrepancies
What does a Data Maturity Assessment allow businesses to do?
Ignore potential hazards.
Increase compliance discrepancies
Recognize potential hazards and compliance discrepancies in data management
Make data management more complex
What are key initial deliverables to establish foundational Data Governance (DG) according to the BI4ALL methodology?
A complex technical architecture.
A DG Business case and a DG Policy
Ignoring Roles & Responsibilities
Focusing on technology.
What does a centralized Data Governance focus on?
A decentralized way to manage data
Department-specific data management
A single authority for setting organization-wide data standards.
Ignoring standards for data
In a centralized data governance model, who is often in charge of setting the organization's data standards?
Data Stewards
A Chief Data Officer
Individual business units.
Data Analysts
According to the sources, what is a key enabler for scaling a DG initiative throughout the business?
Ignoring the DG Strategy
The DG Strategy and DG technology.
Only focusing on technology
Only focusing on the DG Policy
What does Federated or Decentralized Governance enable companies to do?
Treat Data as a liability
Create data silos
Treat Data as a Product
Ignore data as a product
What is a common activity for Data Governance?
Creating confusion about data definitions
Ignoring Data Owners and Data Stewards
Create Data Definitions
Creating conflicts among stakeholders
What is a common activity for Data Governance?
Ignoring conflicts among stakeholders
Avoiding the establishment of a Data Governance Council
Establish a Data Governance Council
Refusing to delegate responsibility
What is a common activity for Data Governance?
Creating silos.
Ignoring the organization's goals
Align data assets and activities with organizational goals (data strategy)
Ignoring training
What is an operating model in the context of Data Governance?
An organizational chart
A framework that defines how business processes should be integrated and how data standardization should occur internally and with external trading partners.
A set of specific software tools
Only for technical aspects of data management
According to the sources, an operating model does not serve as what?
A framework for effective data governance
An organizational chart
A detailed plan for data governance
A guide for the business and technical architecture
What is an Operating Model in data governance?
An approach that does not require oversight
A way to ignore responsibilities
A framework for delineating responsibility and ownership
A way to not harmonize data
What is a key goal of a Data Governance Operating Model?
To structure the data governance program around particular individuals.
To drive the organization's actions and decisions.
To make the program unsustainable.
To avoid clear roles and responsibilities.
What is a characteristic of a centralized data governance operating model?
A single central team oversees data governance
Multiple teams oversee data governance independently
Individual departments manage their own data
Data governance is tailored to specific needs of departments
What is a key benefit of a centralized data governance operating model?
Inconsistency in policies and standards
Slow response to needs.
Consistency in policies and standards
Bottlenecks in decision-making
In a centralized data governance model, who does the business and technical support roles typically report to?
An executive sponsor
The data governance lead
A steering committee
Multiple data governance leads
What does a decentralized data governance operating model mean?
A single central team oversees data governance
Individual departments or business units manage their data governance policies independently.
Hybrid approach
A single lead controls all processes
Rui Afeteira has more than 10 years of experience.
True
False
The course includes a lesson on Data Privacy.
True
False
The final exam is worth 70% of the final grade.
True
False
The final exam will be completed online using Moodle.
True
False
Students must use the Safe Exam Browser for the exam.
True
False
Students can request a laptop from NOVA if needed.
True
False
Data Governance is about managing the technical aspects of data.
True
False
Data Management is a knowledge area of Data Governance.
True
False
Data Management focuses on the lifecycle of data.
True
False
A Data Steward is a highly technical role in Data Management.
True
False
Effective data management requires a lack of leadership commitment.
True
False
Data is not an asset.
True
False
Data Management requirements must drive Information Technology decisions.
True
False
Data Management is a cross-functional activity.
True
False
Data Management only focuses on the present.
True
False
Data Governance ensures data is used ethically and consistently.
True
False
Data Management defines the policies for data usage.
True
False
Data Management is more about the technical processes of data.
True
False
The DAMA Data Management Framework has not evolved.
True
False
Data Integration and Interoperability is a new knowledge area in the DAMA framework.
True
False
Data Governance is the implementation and Data Management is the strategy.
True
False
Data Governance provides direction and oversight for Data Management.
True
False
Data Governance ensures data is managed according to best practices.
True
False
Data Governance includes setting and enforcing policies related to data access.
True
False
Data Governance does not address issues related to data security.
True
False
A Data Governance program can help improve data quality.
True
False
Data volumes are decreasing.
True
False
Data Governance helps companies become more data-driven.
True
False
Companies are always achieving the expected outcomes with data and machine learning.
True
False
Data should be used as an asset.
True
False
The business should not take the lead in managing data.
True
False
Data protection regulations are decreasing.
True
False
The course project proposal involves Data Governance for Analytics and Generative AI.
True
False
Data Governance only focuses on regulatory compliance.
True
False
Data Governance can help improve customer experience.
True
False
Data Governance can reduce operational costs.
True
False
Data Governance helps to enable data-driven decision-making.
True
False
A Business Glossary is a resource that documents the meaning of data elements.
True
False
A Data Dictionary is a framework that defines how a data governance program is structured.
True
False
The Data Governance Operating Model outlines the responsibilities of individuals.
True
False
Data Governance is only about fixing data quality issues.
True
False
A Data Maturity Assessment is not useful for developing a data strategy.
True
False
A Data Literacy program is not related to Data Governance.
True
False
The Data Governance strategy should be defined before the Data Governance policy.
True
False
A centralized Data Governance approach is always best.
True
False
In a Federated Data Governance model, data is treated as a product.
True
False
A Data Governance Council is not important.
True
False
Data Governance activities should be aligned with organizational goals.
True
False
A one-size-fits-all approach is the best way for Data Governance.
True
False
Data standardization should occur both internally and with external trading partners.
True
False
An Operating Model serves as an organizational chart for Data Governance.
True
False
An Operating Model helps to ensure that data is managed and harmonized.
True
False
A Data Governance program should be structured around individuals.
True
False
A Data Governance Manager is not needed.
True
False
A Centralized Data Governance model is fast to respond to department-specific needs.
True
False
In a Centralized model, a single team oversees data governance.
True
False
A Chief Data Officer typically leads a Centralized Data Governance Model.
True
False
The Centralized Model operates like a project management structure.
True
False
The Centralized model works well for individual business lines but not for enterprise wide applications.
True
False
A decentralized model is when individual departments manage their own data.
True
False
Decentralized governance encourages departmental innovation.
True
False
Decentralized models have a high risk of consistent data governance.
True
False
Decentralized models can lead to duplication of efforts.
True
False
A hybrid model combines centralized and decentralized approaches.
True
False
A hybrid model is not adaptable to organizational needs.
True
False
A hybrid model is more complex to implement and manage.
True
False
A hybrid model does not require clear roles and responsibilities.
True
False
