Enterprise data architecture usually include the following work streams:
ECM is an abbreviation for:
An organization will create an uncover valuable Metadata during the process of developing Data Integration and Interoperability solutions.
An input in the data architecture context diagram includes data governance.
What types of data are considered Technical Data?
In designing and building the database, the DBA should keep the following design principles in mind:
CMA is an abbreviation for Capability Maturity Assessment.
Different storage volumes include:
Please select the four domains of enterprise architecture:
Issues caused by data entry processes include:
Data models are critical to effective management of data. They:
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?
Looking at the DMBoK definition of Data Governance, and other industry definitions, what are some of the common key elements of Data Governance?
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.
Please select valid modelling schemes or notations
The business glossary should capture business terms attributes such as:
You have completed analysis of a Data Governance issue in your organisation and have presented your findings to the executive management team. However, your findings are not greeted warmly and you find yourself being blamed for the continued existence of the issue. What is the most likely root cause for this?
High quality data definition exhibit three characteristics:
Metadata management solutions include architectural layers including:
The IT security policy provides categories for individual application, database roles, user groups and information sensitivity.
Please select the answers that correctly describes the set of principles that recognizes salient features of data management and guide data management practice.
Data modelling is most infrequently performed in the context of systems and maintenance efforts, known as SDLC.
Uniqueness, as a dimension of data quality, states no entity exists more than once within the data set.
Confidentiality classification schemas might include two or more of the five confidentiality classification levels. Three correct classifications levels are:
Every DMM and Data Governance assessment must define how the assessment team will interact with its subjects (after defining the subject/stakeholder list). This is important because:
Drivers for data governance most often focus on reducing risk or improving processes. Please select the elements that relate to the reduction in risk:
In the context of big data the Three V’s refer to: Volume, Velocity and Validity
Examples of the ‘Who’ entity category include: employee; patient; player; and suspect.
DBAs exclusively perform all the activities of data storage and operations.
What is the main purpose of developing a Data Architecture Roadmap?
A DMZ is bordered by 2 firewalls. These are between the DMZ and the:
Reference and Master Data Management follow these guiding principles:
A change management program supporting formal data governance should focus communication on:
Obtaining buy-in from all stakeholders
To build models, data modellers heavily rely on previous analysis and modelling work.
Please select the transition phases in Bridges’ Transition process:
The ethics of data handling are complex, but is centred on several core concepts. Please select the correct answers.
Taxonomies can have different structures, including:
Two risks with the Matching process are:
The neutral zone is one of the phases in the Bridges’ transition phases.
Integrating data security with document and content management knowledge areas.
guides the implementation of:
The goals of implementing best practices around document and content management include:
Inputs in the data storage and operations context diagram include:
A database uses foreign keys from code tables for column values. This is a way of
implementing:
Business rules describe why business should operate internally, in order to be successful and compliant with the outside world.
The most common drivers for initiating a Mater Data Management Program are:
The advantage of a decentralized data governance model over a centralized model is:
Domains can be identified in different ways including: data type; data format; list; range; and rule-based.
Data management organizational constructs include the following type of model.
Data flows map and document relationships between data and:
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:
Service accounts are convenient because they can tailor enhanced access for the processes that use them.
A data lineage tool enables a user to:
One of the first steps in a master data management program is to:
Control activities to manage metadata stores include:
A minimal super key is:
With respect to health data, what is the difference between the privacy and the security of the data?
Which of the following is NOT an objective of a business (data) glossary?
Data Governance requires which of the following?
There are three basic approaches to implementing a Master Data hub environment, including:
Lack of automated monitoring represents serious risks, including compliance risk.
Examples of interaction models include:
Gathering and interpreting results from a DMM or Data Governance assessment are important because:
Data governance and IT governance are the same thing.
Key processing steps for MDM include:
Examples of technical metadata include:
To become data-centric, organizations need to think differently. They need to recognize:
Security Risks include elements that can compromise a network and/or database.
BI tool types include:
Wat data architecture designs represent should be clearly documented. Examples include:
Common OLAP operations include:
Data security issues, breaches and unwarranted restrictions on employee access to data cannot directly impact operational success.
Data Integration and Interoperability is dependent on these other areas of data management:
Data flows map and document relationships between data and locations where global differences occur.
What are the primary drivers of data security activities?
When constructing models and diagrams during formalisation of data architecture there are certain characteristics that minimise distractions and maximize useful information. Characteristics include:
The best way to validate that a database backup is working, is to:
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?
JSON is an open, lightweight standard format for data interchange.
Several global regulations have significant implications on data management practices. Examples include:
Business Intelligence, among other things, refer to the technology that supports this kind of analysis.
Device security standard include:
The best preventative action to prevent poor quality data from entering an organisation include:
Data lineage is useful to the development of the data governance strategy.
Data Integration and Interoperability (DII) describes processes related to the movement and consolidation of data within and between data stores, applications and organizations.
How do data management professionals maintain commitment of key stakeholders to the data management initiative?
Which of the following provides the strongest tangible reason for driving initiation of a Data Governance process in an enterprise?
The library of Alexandria was one of the largest collection of books in the ancient
world. Which DMBoK knowledge area is most aligned with managing the collection?
Please select the correct General Accepted Information Principles:
Structural Metadata describe srealtionships within and among resource and enables identification and retrieval.
Select three correct attributes a data governance programme must be:
Real-time data integration is usually triggered by batch processing, such as historic data.
Enterprise data architects in an application migration project are primarily concerned with:
Because Data Governance activities require coordination across functional areas, the DG program must establish an ___________ that defines accountabilities and intersections.
A data model that consists of a single fact table linked to important concepts of the
business is a:
Repositories facilitate the collection, publishing and distribution of data in a centralized and possibly standardized way. Data is most often used to:
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?
In an information management context, the short-term wins and goals often arise from the resolution of an identified problem.
Examples of concepts that can be standardized within the data architecture knowledge area include:
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?
Please select the correct principles of the General Data Protection Regulation (GDPR) of the EU.
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:
Content refers to the data and information inside a file, document or website.
Machine learning explores the construction and study of learning algorithms.
Data handling ethics are concerned with how to procure, store, manage, use and dispose of data in ways that are aligned with ethical principles.
A data warehouse deployment with multiple ETL, storage and querying tools often
suffers due to the lack of:
The repeated implementation of different CRM technologies with different data
structures is mostly a failure of:
Latency can be:
While the focus of data quality improvement efforts is often on the prevention of errors, data quality can also be improved through some forms of data processing.
A Business Glossary forces a business to adopt a single definition of a business term.
Improving an organization’s ethical behaviour requires an informal Organizational Change Management (OCM) process.
Developing complex event processing solutions require:
A goal of Data warehouse and business intelligence is to support and enable ineffective business analysis and decision making by knowledge workers.
Examples of data enhancement includes:
Analytics models are associated with different depths of analysis, including:
All organizations have the same Master Data Management Drivers and obstacles.
Please select the option that correctly orders the models in decreasing level of detail:
A lineage data tool provides:
Data parsing is the process of analysing data using pre-determined rules to define its content or value.
SLA Stands for:
Some document management systems have a module that may support different types of workflows such as:
Field overloading: Unnecessary data duplication is often a result of poor data management.
Resource Description Framework (RDF), a common framework used to describe information about any Web resource, is a standard model for data interchange in the Web.
All assessments should include a roadmap for phased implementation of the recommendations. This is important because:
Triplestores can be classified into these categories:
A goal of a Reference and Master Data Management program include enabling master and reference data to be shared across enterprise functions and applications.
When trying to integrate a large number of systems, the integration complexities can
be reduced by:
Valuation information, as an example of data enrichment, is for asset valuation, inventory and sale.
Data quality rules and standards are a critical form of Metadata. Ti be effective they need to be managed as Metadata. Rules include:
Match rules for different scenarios require different workflows, including:
Effective document management requires clear policies and procedures, especially regarding retention and disposal of records.
Normalisation is the process of applying rules in order to organise business complexity into stable data structures.
Which of the following is not a step in the 'document and content management
lifecycle'?
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.
Data replication can be active or passive.
Data professional should not balance the short-term versus long-term business interests.
Big data management requires:
What is the best reason for capturing synonyms in a data repository?
Oversight for the DMMA process belongs to the Data Quality team.
Practitioners identify development of staff capability to be a primary concern of Data Governance. Why would this be a main concern?
Which artifact is the highest level of abstraction in the Enterprise Data Model?
A data governance strategy defines the scope and approach to governance efforts. Deliverables include:
'Planning, implementation and control activities for lifecycle management of data and
information, found in any form or medium', pertains to which knowledge area?
Factors that have shown to play a key role in the success in the success of effective data management organizations does not include:
Tools required to manage and communicate changes in data governance programs include
The Data Warehouse encompasses all components in the data staging and data presentation areas, including:
The best way to validate that a database backup is working is to:
The process of building architectural activities into projects also differ between methodologies. They include:
A key feature of Bill Inmon’s approach to data warehousing is:
Business continuity is an aspect of Governance. What should a business continuity plan include?
A primary business driver of data storage and operations is:
One of the deliverables in the Data Integration and Interoperability context diagram is:
In the Data Warehousing and Business Intelligence Context Diagram, a primary deliverable is the DW and BI Architecture.
Data asset valuation is the process of understanding and calculating the economic value of data to an organisation. Value comes when the economic benefit of using data outweighs the costs of acquiring and storing it, as
Some common data quality business rule types are:
Changes to reference data do not need to be management, only metadata should be managed.
Subtype absorption: The subtype entity attributes are included as nullable columns into a table representing the supertype entity
Bold means doing something that might cause short term pain, not just something that looks good in a marketing email.
Reference and master data require governance processes, including:
Creating the CDM involves the following steps:
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.
The acronym ETL most commonly stands for:
The European Commission Article 29 Data Protection Working Party provides a set of criteria to evaluate anonymization methods. What do they recommend?
Sustainable Data Governance depends on:
Project that use personal data should have a disciplined approach to the use of that data. They should account for:
When assessing tools to implement master data management solutions, functionality
must include:
Business people must be fully engaged in order to realize benefits from the advanced analytics.
Business Intelligence tool types include:
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?
Within projects, conceptual data modelling and logical data modelling are part of requirements planning and analysis activities, while physical data modelling is a design activity.
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 database uses foreign keys from code tables for column values. This is a way of implementing:
Please select the answer that does not represent a machine learning algorithm:
It is unwise to implement data quality checks to ensure that the copies of the attributes are correctly stored.
Test environments serve many uses:
Data Quality rules and standards are a form of data. To be effective, they need to be managed, as data and rules should be:
People often incorrectly combine the concepts of data management and information technology into one. Which of the following is NOT an example of this?
Decentralized informality can be made more formal through a documented series of connections and accountabilities via a RACI matrix.
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.
What is the final step in the development of a business-data-driven roadmap?
The goals of Metadata management include:
Content management includes the systems for organizing information resources so that they can specially be stored.
The difference between warehouses and operational systems do not include the following element:
The goals of Data Integration and Interoperability include:
A node is a group of computers hosting either processing or data as part of a distributed database.
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.
What result(s) is/are Data Handling Ethics trying to avoid?
The list of V’s include:
Data governance requires control mechanisms and procedures for, but not limited to, escalating issues to higher level of authority.
SDLC stands for:
An Operational Data Mart is a data mart focused on tactical decision support.
Examples of transformation include:
Issues caused by data entry processes include:
Data Fabric is:
Which answer is considered to be the best definition of data security?
When recovering from multiple system failures, what is the biggest difficulty faced
by a DBA?
A deliverable in the data modelling and design context diagram is the logical data model.
Select the areas to consider when constructing an organization’s operating model:
Barriers to effective management of data quality include:
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.
Over a decade an organisation has rationalised implementation of party concepts
from 48 systems to 3. This is a result of good:
Metrics tied to Reference and Master Data Quality include:
A goal of reference and master data management is for data to ensure shared data is:
What are the components of a Data Governance Readiness Assessment?
The acroymn ACID stands for.
Big data is often defined by three characteristics. They are:
SSD is the abbreviation for Solid State Dimension.
Which of the following activities is most likely to maintain bias in data analysis?
Data quality issues cannot emerge at any point in the data lifecycle.
Product Master data can only focus on an organization’s internal product and services.
Data Management maturity has many goals for accomplishment including having a positive effect on culture. This is important to a Data Governance program for the following reason:
Data profiling also includes cross-column analysis, which can identify overlapping or duplicate columns and expose embedded value dependencies.
There are three recovery types that provide guidelines for how quickly recovery takes place and what it focuses on.
Location Master Data includes business party addresses and business party location, as well as facility addresses for locations owned by organizations.
Critical Data is most often used in
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.
A goal of reference and master data is to provide authoritative source of reconciled and quality-assessed master and reference data.
Three classic implementation approaches that support Online Analytical Processing include:
Which of these is NOT a component of an enterprise wide data strategy?