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TESTED 30 Apr 2025
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Some document management systems have a module that may support different types of workflows such as:
The CAP theorem asserts that the distributed system cannot comply with all the parts of the ACID. A distributed system must instead trade-off between the following properties:
In a global organization which must operate under many local jurisdictions, each with their own legislative and compliance laws, which type of Data Governance Operating Model Type would best apply?
Three classic implementation approaches that support Online Analytical Processing include:
Achieving security risk reduction in an organisation begins with developing what?
There are three basic approaches to implementing a Master Data hub environment, including:
The most informal enterprise data model is the most detailed data architecture design document.
The load step of ETL is physically storing or presenting the results of the transformation in the target system.
In the context of big data the Three V’s refer to: Volume, Velocity and Validity
Which of the following is NOT required to effectively track data quality incidents?
The implementation of a Data Warehouse should follow guiding principles, including:
As an often-overlooked aspects of basic data movement architecture, Process controls include:
Data modelling is most infrequently performed in the context of systems and maintenance efforts, known as SDLC.
Use business rules to support Data Integration and Interoperability at various points, to:
A goal of data governance is to enable an organisation to manage its data as a liability.
One of the key differences between operational systems and data warehouses is:
Data modeller: responsible for fata model version control an change control
The Zachman Framweork’s communication interrogative columns provides guidance on defining enterprise architecture. Please select answer(s) that is(are) coupled correctly:
The goal of Data Governance is to enable an organization to manage data as an asset. To achieve this overall goal, a DG program must be:
Data Integration and Interoperability (DII) describes processes related to the movement and consolidation of data within and between data stores, applications and organizations.
Organizations are legally required to protect privacy by identifying and protecting sensitive data. Who usually identifies the confidentiality schemes and identify which assets are confidential or restricted?
The IT security policy provides categories for individual application, database roles, user groups and information sensitivity.
A e-discovery readiness assessment should examine and identify opportunities for the commercial response program.
Which statement best describes the relationship between documents and records?
Bold means doing something that might cause short term pain, not just something that looks good in a marketing email.
One of the percentages to measure success of a records management system implantation is the percentage of the identified corporate records declared as such and put under records control.
An authoritative system where data is created/captured, and/or maintained through
a defined set of rules and expectations is called:
An application DBA leads the review and administration of procedural database objects.
A Metadata repository contains information about the data in an organization, including:
A content strategy should end with an inventory of current state and a gap assessment.
Data science involves the iterative inclusion of data sources into models that develop insights. Dat science depends on:
ETL is the basic process which is central to all areas in Data Integration and Interoperability. It is an abbreviation for extract, transition and load.
Data Governance is at the centre if the data management activities, since governance is required for consistency within and balance between functions.
When we consider the DMBoK2 definition of Data Governance, and the various practitioner definitions that exist in the literature, what are some of the key elements of Data Governance?
If the target system has more transformation capability than either the source or the intermediary application system, the order of processes may be switched to ELT – Extract Load Tranform.
Part of alignment includes developing organizational touchpoints for data governance work. Some examples of touchpoints include: Procurement and Contracts; Budget and Funding; Regulatory Compliance; and the SDLC framework.
A deliverable in the data modelling and design context diagram is the logical data model.
Communications are essential to the success of a DMM or Data Governance assessment. Communications are important because:
The data in Data warehouses and marts differ. Data is organized by subject rather than function
Business glossary is not merely a list of terms. Each term will be associated with other valuable metadata such as synonyms, metrics, lineage, or:
A security mechanism that searches for customer bank account details in outgoing
emails is achieving the goal of:
Subtype absorption: The subtype entity attributes are included as nullable columns into a table representing the supertype entity
A Business Glossary forces a business to adopt a single definition of a business term.
In a SQL injection attack, a perpetrator inserts authorized database statements into a vulnerable SQL data channel, such as a stored procedure.
Field overloading: Unnecessary data duplication is often a result of poor data management.
A ‘Golden Record’ means that it is always a 100% complete and accurate representation of all entities within the organization.
Lack of automated monitoring represents serious risks, including compliance risk.
The best DW/BI architects will design a mechanism to connect back to transactional level and operational level reports in an atomic DW.
Data professional should not balance the short-term versus long-term business interests.
Issue management is the process for identifying, quantifying, prioritizing, and resolving Data Governance issues. Which of the following are areas where that issues might arise:
Implementing a BI portfolio is about identifying the right tools for the right user communities within or across business units.
E-discovery is the process of finding electronic records that might serve as evidence in a legal action.
Data governance requires control mechanisms and procedures for, but not limited to, identifying, capturing, logging and updating actions.
The advantage of a decentralized data governance model over a centralized model is:
Metadata is essential to the management of unstructured data as it id to the management of structured data.
Value is the difference between the cost of a thing and the benefit derived from that thing.
A goal of metadata management is to manage data related business terminology in
order toc
The purpose of data governance is to ensure that data is managed properly, according to policies and best practices. Data governance is focused on how decisions are made about data and how people and processes are expected to behave in relation to data.
The implementation of a Data Warehouse should follow these guiding principles:
Reference and Master data definition: Managing shared data to meet organizational goals, reduce risks associated with data redundancy, ensure higher quality, and reduce the costs of data integration.
Data architect: A senior analyst responsible for data architecture and data integration.
The roles associated with enterprise data architecture are data architect, data modellers and data stewards.
Data science merges data mining, statistical analysis, and machine learning with the integration and data modelling capabilities, to build predictive models that explore data content patterns.
Data integrity is the state of being partitioned – protected from being whole.
A control activity in the metadata management environment includes loading statistical analysis.
Data Governance Office (DGO) focuses on enterprise-level data definitions and data management standards across all DAMA-DMBOK knowledge areas. Consists of coordinating data management roles.
Factors that have shown to play a key role in the success in the success of effective data management organizations does not include:
Please select the 3 visuals that depict DAMA’s Data Management Framework.
A change management program supporting Data Governance should focus communication on what?
A goal of a Reference and Master Data Management program include enabling master and reference data to be shared across enterprise functions and applications.
Data governance can be understood in terms of political governance. It includes the following three function types:
Gathering and interpreting results from a DMM or Data Governance assessment are important because:
Many people assume that most data quality issues are caused by data entry errors. A more sophisticated understanding recognizes that gaps in or execution of business and technical processes cause many more problems that mis-keying.
If data is not integrated with care it presents risk for unethical data handling. These ethical risks intersect with fundamental problems in data management including: Limited knowledge of data’s origin and lineage; Data of poor quality; Unreliable Metadata; and Documentation of error remediation.
Architecture is the fundamental organization of a system, embodied in its components, their relationships to each other and the environment and the principles governing its design and evolution.
A controlled vocabulary is a defined list of explicitly allowed terms used to index, categorize, tag, sort and retrieve content through browsing and searching.
Which Data Architecture artefact contains the names of key business entities, their
relationships, critical guiding business rules and critical attributes?
The Data Warehouse (DW) is a combination of three primary components: An integrated decision support database, related software programs and business intelligence reports.
Decentralized informality can be made more formal through a documented series of connections and accountabilities via a RACI matrix.
What are some of the business drivers for the ethical handling of data that Data Governance should satisfy?
Data flows map and document relationships between data and locations where global differences occur.
Those responsible for the data-sharing environment have an obligation to downstream data consumers to provide high quality data.
Please select the correct principles of the General Data Protection Regulation (GDPR) of the EU.
All assessments should include a roadmap for phased implementation of the recommendations. This is important because:
In gathering requirements for DW/BI projects, begin with the data goals and strategies first.
The most common drivers for initiating a Mater Data Management Program are:
A metadata repository is essential to assure the integrity and consistent use of an enterprise data model across business processes.
It is recommended that organizations not print their business data glossaries for general use, why would you not want to print the glossary?
The language used in file-based solutions is called MapReduce. This language has three main steps:
A sandbox environment can either be a sub-set of the production system, walled off from production processing or a completely separate environment.
The information governance maturity model describes the characteristics of the information governance and recordkeeping environment at five levels of maturity for each of the eight GARP principles. Please select the correct level descriptions:
Common understanding of the core business concepts and terminology is the objective of which deliverable?
Emergency contact phone number would be found in which master data
management program?
A business driver for Master Data Management program is managing data quality.
The categories of the Data Model Scorecard with the highest weightings include:
Which of the following is not a step in the 'document and content management
lifecycle'?
How can the Data Governance process best support Regulatory reporting requirements?
An organization can enhance its Data Governance program and thereby improve its approach to enterprise data management. This is important for the following reason:
Effective data management involves a set of complex, interrelated processes that disable an organization to use its data to achieve strategic goals.
Within each area of consideration mentioned in question 13, they should address morale adversity as per Ethical Risk Model for Sampling Projects.
Please select the answer that best fits the following description: Contains only real-time data.
The data warehouse and marts differ from that in applications as the data is organized by subject rather than function.
Customer value comes when the economic benefit of using data outweighs the costs of acquiring and storing it, as well we managing risk related to usage. Which of these is not a way to measure value?
Oversight for the appropriate handling of data falls under both Data Governance and Legal Counsel. What are they NOT required to do?
When doing reference data management, there many organizations that have standardized data sets that are incredibly valuable and should be subscribed to. Which of these organizations would be least useful?
Data Storage and Operations: The design, implementation and support of stored data to maximize its value.
Business requirements is an input in the Data Warehouse and Business Intelligence context diagram.
A hacker is a person who finds unknown operations and pathways within complex computer system. Hackers are only bad.
To mitigate risks, implement a network-based audit appliance, which can address most of the weaknesses associated with the native audit tools. This kind of appliance has the following benefits:
Consistent input data reduces the chance of errors in associating records. Preparation processes include:
A completely distributed architecture maintains a single access point. The metadata retrieval engine responds to user requests by retrieving data from source systems in real time.
How can the Data Governance process in an organisation best support the requirements of various Regulatory reporting needs?
Which of the following is an activity for defining a Data Governance strategy?
Which of the following are must-do for any successful Data Governance programme?
Top down' and "bottom up' data analysis and profiling is best done in concert
because:
Your organization has many employees with official roles as data stewards and data custodians, but they don't seem to know exactly what they're supposed to be doing. Which of the following is most likely to be a root cause of this problem?
There are three basic approaches to implementing a Master Data hub environment, including:
In the Abate Information Triangle the past moves through the following echelons befor it comes insight:
Snowflaking is the term given to normalizing the flat, single-table, dimensional structure in a star schema into the respective component hierarchical or network structures.
The ethics of data handling are complex, but is centred on several core concepts. Please select the correct answers.
Governance ensures data is managed, but is not include the actual act of managing data.
Which of the following provides the strongest tangible reason for driving initiation of a Data Governance process in an enterprise?
Controlling data availability requires management of user entitlements and of structures that technically control access based on entitlements.
Issue management is the process for identifying, quantifying, prioritizing and resolving data governance related issues, including:
Please select correct term for the following sentence: An organization shall assign a senior executive to appropriate individuals, adopt policies and processes to guide staff and ensure program audibility.
The repeated implementation of different CRM technologies with different data
structures is mostly a failure of:
The load step of the ETL is physically storing or presenting the results of the transformation into the source system.
Characteristics that minimise distractions and maximise useful information include, but not limited to, consistent object attributes
A critical step in data management organization design is identifying the best-fit operating model for the organization.
What areas should you consider when constructing an organization's Data Governance operating model?
Traditional tool sin data visualtization have both a data and a graphical component. Advanced visualization and discovery tools use in-memory architecture to allow users to interact with the data.
Improving an organization’s ethical behaviour requires an informal Organizational Change Management (OCM) process.
TESTED 30 Apr 2025