Data Management Fundamentals Questions and Answers
Which of the following is NOT a valid Data Governance programme Key Performance Indicator (KPI)?
Access to data for Multidimensional databases use a variant of SQL called MDX or Multidimensional expression.
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:
Naming standards for data domains should:
The Data Warehouse has a set of storage areas, including:
What key components make up the Data Governance Charter?
Data governance program must contribute to the organization by identifying and delivering on specific benefits.
Three data governance operating models types include:
Types of metadata include:
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.
Uniqueness, as a dimension of data quality, states no entity exists more than once within the data set.
Activities that drive the goals in the context diagram are classified into the following phases:
SLA Stands for:
When selecting a DMM framework one should consider of it is repeatable.
The accepted tenets of bioethics provide a starting point for the principles of data ethics. Which of the following tenets of bioethics is NOT included in the DMBOK2 Chapter on Data Handling Ethics?
Examples of data enhancement includes:
Defining quality content requires understanding the context of its production and use, including:
No recorded negative ethical outcomes does not mean that the organization is processing data ethically. Legislation cannot keep up with the evolution of the data environment so how do we stay compliant?
Data replication can be active or passive.
Typically, DW/BI projects have three concurrent development tracks, including:
Confidentiality classification schemas might include two or more of the five confidentiality classification levels. Three correct classifications levels are:
Basic profiling of data involves analysis of:
The goal of data architecture is to:
The list of V’s include:
To push up the urgency level requires adding of the sources of complacency or increasing of their impact.
An organization will create an uncover valuable Metadata during the process of developing Data Integration and Interoperability solutions.
Which of the following would NOT be an interest of Data Governance?
Data Governance focuses exclusively on:
Creating the CDM involves the following steps:
Information gaps represent enterprise liabilities with potentially profound impacts on operational effectiveness and profitability.
Where does the ethical responsibility lie with respect to managing data to reduce risks of misrepresentation, misuse, or misunderstanding?
Product Master data can only focus on an organization’s internal product and services.
Examples of concepts that can be standardized within the data quality knowledge area include:
ANSI standard 859 has three levels of control of data, based on the criticality of the data and the perceived harm that would occur if data were corrupt or otherwise unavailable, including:
Data stewardship is the least common label to describe accountability and responsibility for data and processes to ensure effective control and use of data assets.
Practitioners identify development of staff capability to be a primary concern of Data Governance. Why would this be a main concern?
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:
Most document programs have policies related to:
Database monitoring tools measure key database metrics, such as:
The process of building architectural activities into projects also differ between methodologies. They include:
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.
An advantage of a centralized repository include: Quick metadata retrieval, since the repository and the query reside together.
A content strategy should end with an inventory of current state and a gap assessment.
Data Stewards are most likely to be responsible for:
Business glossary is not merely a list of terms. Each term will be associated with other valuable metadata such as synonyms, metrics, lineage, or:
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.
Inputs in the data storage and operations context diagram include:
The warehouse has a set of storage areas, including:
Operational reports are outputs from the data stewards.
Data security issues, breaches and unwarranted restrictions on employee access to data cannot directly impact operational success.
Please select the correct General Accepted Information Principles:
MPP is an abbreviation for Major Parallel Processing.
Temporal aspects usually include:
The goals of data storage and operations include:
A staff member has been detected inappropriately accessing client records from
usage logs. The security mechanism being used is an:
Please select the correct definition of Data Management from the options below.
Archiving is the process of moving data off immediately accessible storage media and onto media with lower retrieval performance.
A goal of metadata management is to manage data related business terminology in
order toc
The business case for enterprise warehousing is:
A Metadata repository contains information about the data in an organization, including:
Data quality rules and standards are a critical form of Metadata. Ti be effective they need to be managed as Metadata. Rules include:
When it comes to Data Governance, what does the Operations Plan include?
During the initial scoping of a project, a data model can be used to:
Master data is an aggregation of:
Some common data quality business rule types are:
The purpose for adding redundancy to a data model (denormalisation) is to:
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 data-vault is an object-orientated, time-based and uniquely linked set of normalized tables that support one or more functional areas of business.
Preparation and pre-processing of historical data needed in a predictive model may be performed in nightly batch processes or in near real-time.
Operational Metadata describes details of the processing and accessing of data. Which one is not an example:
The key architecture domains include:
Examples of interaction models include:
A database uses foreign keys from code tables for column values. This is a way of implementing:
Within the Data Handling Ethics Context Diagram a key deliverable is the Ethical Data Handling Strategy.
Lack of automated monitoring represents serious risks, including compliance risk.
Business continuity is an aspect of Governance. What should a business continuity plan include?
Examples of concepts that can be standardized within the data architecture knowledge area include:
Instant Messaging (IM) allows a user to message each other in real-time.
Emergency contact phone number would be found in which master data
management program?
For each subject area logical model: Decrease detail by adding attributes and less-significant entities and relationships.
When constructing an organization’s operating model cultural factors must be taken into consideration.
Inputs in the Data Integration and Interoperability context diagram include:
Category information is one of the types of data that can be modelled.
Identify indicative components of a Data Strategy.
A limitation of the centralized approach include: Maintenance of a decentralized repository is costly.
Examples of technical metadata include:
Veracity refers to how difficult the data is to use or to integrate.
Which of the following is NOT required to effectively track data quality incidents?
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.
A successful Data Governance program requires that all enterprise data be certified.
Which of the following is NOT a preventative action for creating high quality data?
The most common drivers for initiating a Mater Data Management Program are:
According to the DMBoK2, by creating Data Management Services, IT involves the Data Governance Council:
Data profiling is a form of data analysis used to inspect data and assess quality.
The loading of country codes into a CRM is a classic:
Data governance requires control mechanisms and procedures for, but not limited to, identifying, capturing, logging and updating actions.
Data modelling tools are software that automate many of the tasks the data modeller performs.
Please select the transition phases in Bridges’ Transition process:
The deliverables of the data modelling process include:
When trying to integrate a large number of systems, the integration complexities can
be reduced by:
Data profiling examples include:
What position should be responsible for leading the Data Governance Council (DGC)?
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.
Please select the correct general cost and benefit categories that can be applied consistently within an organization.
A deliverable in the data security context diagram is the data security architecture.
Please select valid modelling schemes or notations
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?
A DMZ is bordered by 2 firewalls. These are between the DMZ and the:
A security mechanism that searches for customer bank account details in outgoing
emails is achieving the goal of:
SOA stand for Service Orchestrated Architecture
When starting a Data Governance initiative it is important to understand what the Business cannot achieve due to data issues because:
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.
Data and text mining use a range of techniques, including:
There are three techniques for data-based change data capture, namely:
What areas should you consider when constructing an organization's Data Governance operating model?
Metadata is described using three sets od categories, including:
Business Intelligence tool types include:
Which of the following is a core principle of any Data Governance program?
The acroymn ACID stands for.
Most people who work with data know that it is possible to use data to misrepresent facts. Which of the following is NOT a way in which data is used to misrepresent facts?
An input in the Metadata management context diagram does not include:
The Data Governance Council (DGC) manages data governance initiatives, issues, and escalations.
Possible application coupling designs include:
GDPR came into affect in May. 2018. What organization is responsible for awarding compliance certificates for organizations?
Data warehousing describes the operational extract, cleaning, transformation, control and load processes that maintain the data in a data warehouse.
Tools required to manage and communicate changes in data governance programs include
Please select the correct types of data stewards:
The 'Data Governance Steering Committee' is best described as:
Which of these best describes the purpose of a Communications Plan in Data Governance?
A change management program supporting Data Governance should focus communication on what?
Layers of data governance are often part of the solution. This means determining where accountability should reside for stewardship activities and who the owners of the data are.
Data security internal audits ensure data security and regulatory compliance policies are followed should be conducted regularly and consistently.
Data science depends on:
Enterprise data architecture description must include both [1] as well as [2]
The accuracy dimension of data quality refers to the degree that data correctly respresents ‘real-life’ entities.
Change only requires change agents in special circumstances, especially when there is little to no adoption.
In Data Modelling, the generalization of the concept of person and organization into a party enables:
Developing complex event processing solutions require:
An application DBA leads the review and administration of procedural database objects.
Master data management includes several basic steps, which include: Develop rules for accurately matching and merging entity instances.
The language used in file-based solutions is called MapReduce. This language has three main steps:
A communication plan includes an engagement model for stakeholders, the type of information to be shared, and the schedule for sharing information.
Characteristics that minimise distractions and maximise useful information include, but not limited to, consistent object attributes
Quality Assurance Testing (QA) is used to test functionality against requirements.
Several global regulations have significant implications on data management practices. Examples include:
The Zachman Framweork’s communication interrogative columns provides guidance on defining enterprise architecture. Please select answer(s) that is(are) coupled correctly:
Logical abstraction entities become separate objects in the physical database design using one of two methods.
E-discovery is the process of finding electronic records that might serve as evidence in a legal action.
Various Regulations require evidence of clear data lineage and accuracy. How can we as data managers best serve our enterprises in achieving this goal?
A metadata repository is essential to assure the integrity and consistent use of an enterprise data model across business processes.
Which of the following are must-do for any successful Data Governance programme?
Those responsible for the data-sharing environment have an obligation to downstream data consumers to provide high quality data.
Adoption of a Data Governance program is most likely to succeed:
Big data management requires:
Data quality management is a key capability of a data management practice and organization.
Do experts feel a Data Lake needs data management?
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?
The implementation of a Data Warehouse should follow guiding principles, including:
The most informal enterprise data model is the most detailed data architecture design document.
Content needs to be modular, structured, reusable and device and platform independent.
A System of Reference is an authoritative system where data consumers can obtain reliable data to support transactions and analysis, even if the information did not originate in the system reference.
Examples of technical metadata include:
Data architects facilitate alignment between [1] and [2]
A sandbox is an alternate environment that allows write-only connections to production data and can be managed by the administrator.
In data modelling practice, entities are linked by:
What are the business objectives for building a business glossary?
The accuracy dimension has to do with the precision of data values.
Open by default' document control will assist data sharing by:
Dimensions of data quality include:
Issues caused by data entry processes include:
What position is responsible for the quality and use of their organization's data
assets?
The steps followed in managing data issues include:
The deliverables in the data architecture context diagram include:
Data replication has two dimensions of scaling: diagonal and lateral
Content management includes the systems for organizing information resources so that they can specially be stored.
Analytics models are associated with different depths of analysis, including:
When constructing models and diagrams during formalisation of data architecture there are certain characteristics that minimise distractions and maximize useful information. Characteristics include:
The ethics of data handling are complex, but is centred on several core concepts. Please select the correct answers.
A deliverable in the data modelling and design context diagram is the logical data model.
Device security standards include:
Machine learning explores the construction and study of learning algorithms.
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?
The data warehouse and marts differ from that in applications as the data is organized by subject rather than function.
The Shewhart chart contains the following elements:
A critical step in data management organization design is identifying the best-fit operating model for the organization.
Metrics tied to Reference and Master Data Quality include:
Reduced risk is a benefit of high quality data.
Security Risks include elements that can compromise a network and/or database.
CIF stands for:
Some document management systems have a module that may support different types of workflows such as:
A control activity in the metadata management environment includes loading statistical analysis.
Real-time data integration is usually triggered by batch processing, such as historic data.
A node is a group of computers hosting either processing or data as part of a distributed database.
What techniques should be used and taught to produce the required ethical data handling deliverables?
Enterprise data architecture influences the scope boundaries of project and system releases. An example of influence is data replication control.
Data models are critical to effective management of data. They:
Which of these is not a goal of Data Governance and Stewardship?
Big data is often defined by three characteristics. They are:
Assessment criteria are broken into levels, and most capability maturity models use five (5) levels. This is important since:
A business driver for Master Data Management program is managing data quality.
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.
Discovering and documenting metadata about physical data assets provides:
SOA is an abbreviation for service orientated architecture.
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.
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.
Orchestration is the term used to describe how multiple processes are organized and executed in a system.
Please select the correct component pieces that form part of an Ethical Handling Strategy and Roadmap.
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
An Operational Data Mart is a data mart focused on tactical decision support.
DBAs exclusively perform all the activities of data storage and operations.
All data is of equal importance. Data quality management efforts should be spread between all the data in the organization.
Please select the correct name for the PDM abbreviation when referring to modelling.
According to the DMBoK, Data Governance is central to Data Management. In practical terms, what other functions of Data Management are required to ensure that your Data Governance programme is successful?
Data integrity is the state of being partitioned – protected from being whole.
Wat data architecture designs represent should be clearly documented. Examples include:
Sample value metrics for a data governance program include:
There is a global trend towards increasing legislative protection of individual's information privacy. Which of these is an emerging topic related to online ethical behaviours?
During the intial scoping of a project, a data model can be used to:
