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What techniques should be used and taught to produce the required ethical data handling deliverables?
Looking at the DMBoK definition of Data Governance, and other industry definitions, what are some of the common key elements of Data Governance?
The IBM Data Governance Council model is organized around four key categories. Select the answer that is not a category.
Emergency contact phone number would be found in which master data
management program?
Data modelling tools are software that automate many of the tasks the data modeller performs.
The Zachman Framweork’s communication interrogative columns provides guidance on defining enterprise architecture. Please select answer(s) that is(are) coupled correctly:
An implemented warehouse and its customer facing BI tool is a data product.
A controlled vocabulary is a defined list of explicitly allowed terms used to index, categorize, tag, sort and retrieve content through browsing and searching.
Over a decade an organisation has rationalised implementation of party concepts
from 48 systems to 3. This is a result of good:
Confidentiality classification schemas might include two or more of the five confidentiality classification levels. Three correct classifications levels are:
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?
Data management professionals who understand formal change management will be more successful in bringing about changes that will help their organizations get more value from their data. To do so, it is important to understand:
The purpose of enterprise application architecture is to describe the structure and functionality of applications in an enterprise.
Operational Metadata describes details of the processing and accessing of data. Which one is not an example:
Data handling ethics are concerned with how to procure, store, manage, use and dispose of data in ways that are aligned with ethical principles.
The primary goal of data management capability assessment is to evaluate the current state of critical data management activities in order to plan for improvement.
Please select the answer that does not represent a machine learning algorithm:
Business activity information is one of the types of data that can be modelled.
Data science involves the iterative inclusion of data sources into models that develop insights. Dat science depends on:
Consistent input data reduces the chance of errors in associating records. Preparation processes include:
The difference between warehouses and operational systems do not include the following element:
A content strategy should end with an inventory of current state and a gap assessment.
Data modelling is most infrequently performed in the context of systems and maintenance efforts, known as SDLC.
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 architect: A senior analyst responsible for data architecture and data integration.
Various Regulations require evidence of clear data lineage and accuracy. How can we as data managers best serve our enterprises in achieving this goal?
Customer relationship management systems manage Master Data about customers.
A sandbox environment can either be a sub-set of the production system, walled off from production processing or a completely separate environment.
The impact of the changes from new volatile data must be isolated from the bulk of the historical, non-volatile DW data. There are three main approaches, including:
Big Data and Data Science Governance should address such data questions as:
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?
Which of the following is an activity for defining a Data Governance strategy?
An authoritative system where data is created/captured, and/or maintained through
a defined set of rules and expectations is called:
An organization will create an uncover valuable Metadata during the process of developing Data Integration and Interoperability solutions.
Information gaps represent enterprise liabilities with potentially profound impacts on operational effectiveness and profitability.
A Global ID is the MDM solution-assigned and maintained unique identifier attached to reconciled records.
An enterprise's organisation chart has multiple levels, each with a single reporting
line. This is an example of a:
The European Commission Article 29 Data Protection Working Party provides a set of criteria to evaluate anonymization methods. What do they recommend?
Which DMBok knowledge area is most likely responsible for a high percentage of
returned mail?
An effective team is based on two simple foundations: trust and a common goal.
Service accounts are convenient because they can tailor enhanced access for the processes that use them.
A ‘Golden Record’ means that it is always a 100% complete and accurate representation of all entities within the organization.
ANSI 859 recommends taking into account the following criteria when determining which control level applies to a data asset:
What areas should you consider when constructing an organization's Data Governance operating model?
Product Master data can only focus on an organization’s internal product and services.
Security Risks include elements that can compromise a network and/or database.
When measuring the value of data architecture one should be most concerned about
A deliverable in the data architecture context diagram includes an implementation roadmap.
A goal of reference and master data is to provide authoritative source of reconciled and quality-assessed master and reference data.
Valuation information, as an example of data enrichment, is for asset valuation, inventory and sale.
Data professionals involved in Business Intelligence, analytics and Data Science are often responsible for data that describes: who people are; what people do; where people live; and how people are treated. The data can be misused and counteract the principles underlying data ethics.
Data modelling tools and model repositories are necessary for managing the enterprise data model in all levels.
Which of the following is not a step in the 'document and content management
lifecycle'?
Please select the answers that correctly describes where the costs of poor quality data comes from.
DBAs and database architects combine their knowledge of available tools with the business requirements in order to suggest the best possible application of technology to meet organizational goals.
Data governance program must contribute to the organization by identifying and delivering on specific benefits.
The advantage of a decentralized data governance model over a centralized model is:
Which of the following is NOT required to effectively track data quality incidents?
The operational data quality management procedures depend on the ability to measure and monitor the applicability of data.
A data warehouse deployment with multiple ETL, storage and querying tools often
suffers due to the lack of:
Governance ensures data is managed, but is not include the actual act of managing data.
The purpose for adding redundancy to a data model (denormalisation) is to:
The best DW/BI architects will design a mechanism to connect back to transactional level and operational level reports in an atomic DW.
In the Data Warehousing and Business Intelligence Context Diagram, a primary deliverable is the DW and BI Architecture.
Archiving is the process of moving data off immediately accessible storage media and onto media with lower retrieval performance.
Development of goals, principles and policies derived from the data governance strategy will not guide the organization into the desired future state.
The database administrator (DBA) is the most established and the most widely adopted data professional role.
The implementation of a Data Warehouse should follow guiding principles, including:
Which of the following provides the strongest tangible reason for driving initiation of a Data Governance process in an enterprise?
Orchestration is the term used to describe how multiple processes are organized and executed in a system.
An image processing system captures, transforms and manages images of paper and electronic documents.
Data Governance includes developing alignment of the data management approach with organizational touchpoints outside of the direct authority of the Chief Data Officer. Select the example of such a touchpoint.
Business Intelligence, among other things, refer to the technology that supports this kind of analysis.
Data modeller: responsible for fata model version control an change control
An effective Data Governance communication program should include the following:
In a data warehouse, where the classification lists for organisation type are
inconsistent in different source systems, there is an indication that there is a lack of
focus on:
Deliverables in the data management maturity assessment context diagram include:
Drivers for data governance most often focus on reducing risk or improving processes. Please select the elements that relate to the improvement of processes:
Gathering and interpreting results from a DMM or Data Governance assessment are important because:
Within each area of consideration mentioned in question 13, they should address morale adversity as per Ethical Risk Model for Sampling Projects.
Data Integration and Interoperability (DII) describes processes related to the movement and consolidation of data within and between data stores, applications and organizations.
Communication should start later in the process as too many inputs will distort the vision.
Data mining is a sub-field of supervised learning where users attempt to model data elements and predict future outcomes through the evaluation of probability estimates.
Enterprise service buses (ESB) are the data integration solution for near real-time sharing of data between many systems, where the hub is a virtual concept of the standard format or the canonical model for sharing data in the organization.
When trying to integrate a large number of systems, the integration complexities can
be reduced by:
In the Information Management Lifecycle, the Data Governance Activity "Define the Data Governance Framework" is considered in which Lifecycle stage?
The best preventative action to prevent poor quality data from entering an organisation include:
Which of the following are must-do for any successful Data Governance programme?
Corrective actions are implemented after a problem has occurred and been detected.
The better an organization understands the lifecycle and lineage of its data, the better able it will be to manage its data. Please select correct implication of the focus of data management on the data lifecycle.
The failure to gain acceptance of a business glossary may be due to ineffective:
A change management program supporting Data Governance should focus communication on what?
Data and enterprise architecture deal with complexity from two viewpoints:
In gathering requirements for DW/BI projects, begin with the data goals and strategies first.
Uniqueness, as a dimension of data quality, states no entity exists more than once within the data set.
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.
With reliable Metadata an organization does not know what data it has, what the data represents and how it moves through the systems, who has access to it, or what it means for the data to be of high quality.
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:
Content needs to be modular, structured, reusable and device and platform independent.
When recovering from multiple system failures, what is the biggest difficulty faced
by a DBA?
When starting a Data Governance initiative it is important to understand what the Business cannot achieve due to data issues because:
It is recommended that organizations not print their business data glossaries for general use, why would you not want to print the glossary?
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.
One of the deliverables in the Data Integration and Interoperability context diagram is:
Effective data management involves a set of complex, interrelated processes that enable an organisation to use its data to achieve strategic goals.
Master data management includes several basic steps, which include: Develop rules for accurately matching and merging entity instances.
An application DBA leads the review and administration of procedural database objects.
All DMM and Data Governance assessments should identify its objectives and goals for improvement. This is important because:
A limitation of the centralized approach include: Maintenance of a decentralized repository is costly.
What area do you not consider when developing a 'Data Governance operating model?
The ethics of data handling are complex, but is centred on several core concepts. Please select the correct answers.
A roadmap for enterprise data architecture describes the architecture’s 3 to 5-year development path. The roadmap should be guided by a data management maturity assessment.
The flow of data in a data integration solution does not have to be designed and documented.
When assessing security risks it is required to evaluate each system for the following:
Data security includes the planning, development and execution of security policies and procedures to provide authentication, authorisation, access and auditing of data and information assets.
Because Data Governance activities require coordination across functional areas, the DG program must establish an ___________ that defines accountabilities and intersections.
Improving an organization’s ethical behaviour requires an informal Organizational Change Management (OCM) process.
The repeated implementation of different CRM technologies with different data
structures is mostly a failure of:
Volume refers to the amount of data. Big Data often has thousands of entities or elements in billions of records.
Change Data Capture is a method of reducing bandwidth by filtering to include only data that has been changed within a defined timeframe.
A business driver for Master Data Management program is managing data quality.
In a SQL injection attack, a perpetrator inserts authorized database statements into a vulnerable SQL data channel, such as a stored procedure.
Through similarity analysis, slight variation in data can be recognized and data values can be consolidated. Two basic approaches, which can be used together, are:
TESTED 02 May 2025