Examples of the ‘Who’ entity category include: employee; patient; player; and suspect.
Measuring the effects of change management on in five key areas including: Awareness of the need to change; Desire to participate and support the change; Knowledge about how to change; Ability to implement new skills and behaviors; and Reinforcement to keep the change in place.
The most common drivers for initiating a Mater Data Management Program are:
Information gaps represent enterprise liabilities with potentially profound impacts on operational effectiveness and profitability.
What are the three characteristics of effective Data Governance communication?
SOA is an abbreviation for service orientated architecture.
Location Master Data includes business party addresses and business party location, as well as facility addresses for locations owned by organizations.
The difference between warehouses and operational systems do not include the following element:
Considerations for whether to integrate two data stores should include all except
the:
An organization can enhance its Data Governance program and thereby improve its approach to enterprise data management. This is important for the following reason:
Analytics models are associated with different depths of analysis, including:
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:
Data profiling examples include:
The implementation of a Data Warehouse should follow guiding principles, including:
The Data Warehouse has a set of storage areas, including:
Data handling ethics are concerned with how to procure, store, manage, use and dispose of data in ways that are aligned with ethical principles.
Why is it important to create short-term wins when rolling out a Data Governance initiative?
The goals of Metadata management include:
Data Governance focuses exclusively on:
During the intial scoping of a project, a data model can be used to:
An Operational Data Mart is a data mart focused on tactical decision support.
Once the most critical business needs and the data that supports them have been identified, the most important part of the data quality assessment is actually looking data, querying it to understand data content and relationships, and comparing actual data to rules and expectations.
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 governance and IT governance are the same thing.
Data professional should not balance the short-term versus long-term business interests.
The data warehouse and marts differ from that in applications as the data is organized by subject rather than function.
Data science involves the iterative inclusion of data sources into models that develop insights. Dat science depends on:
Data flows map and document relationships between data and:
The goals of data security include:
Emergency contact phone number would be found in which master data
management program?
Data Storage and Operations: The design, implementation and support of stored data to maximize its value.
A limitation of the centralized approach include: Maintenance of a decentralized repository is costly.
Metadata management solutions include architectural layers including:
Practitioners identify development of staff capability to be a primary concern of Data Governance. Why would this be a main concern?
Please select the answer that best fits the following description: Contains only real-time data.
SPARC published their three-schema approach to database management. The three key components were:
Inputs in the data quality context diagram include:
Different types of product Master Data solutions include:
All data is of equal importance. Data quality management efforts should be spread between all the data in the organization.
Please select the transition phases in Bridges’ Transition process:
The best way to validate that a database backup is working, is to:
The standard for a strong password is set by the:
Data and enterprise architecture deal with complexity from two viewpoints:
Types of metadata include:
SLA Stands for:
MPP is an abbreviation for Major Parallel Processing.
Enterprise data architecture description must include both [1] as well as [2]
Over a decade an organisation has rationalised implementation of party concepts
from 48 systems to 3. This is a result of good:
Data governance requires control mechanisms and procedures for, but not limited to, identifying, capturing, logging and updating actions.
The target of organizational change is expedition.
Basic profiling of data involves analysis of:
The database administrator (DBA) is the most established and the most widely adopted data professional role.
Real-time data integration is usually triggered by batch processing, such as historic data.
Examples of interaction models include:
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:
Which of the following is a Data Quality principle?
Test environments serve many uses:
Typically, DW/BI projects have three concurrent development tracks, including:
The number of entities in a relationship is the arity of the relationship. The most common are:
Implementing a BI portfolio is about identifying the right tools for the right user communities within or across business units.
A data dictionary is necessary to support the use of a DW.
A deliverable in the data security context diagram is the data security architecture.
The four main types of NoSQL databases are:
Data access control can be organized at an individual level or group level, depending on the need.
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.
Examples of transformation in the ETL process onclude:
A sandbox is an alternate environment that allows write-only connections to production data and can be managed by the administrator.
The advantage of a decentralized data governance model over a centralized model is:
Data Management Professionals only work with the technical aspects related to data.
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:
The 'Data Governance Steering Committee' is best described as:
Class operations can be:
Organizations conduct capability maturity assessments for a number of reasons, including:
Please select the correct name for the PDM abbreviation when referring to modelling.
Structural Metadata describe srealtionships within and among resource and enables identification and retrieval.
Record management starts with a vague definition of what constitutes a record.
XML is the abbreviation for standard mark-up language.
The four A’s in security processes include:
A e-discovery readiness assessment should examine and identify opportunities for the commercial response program.
Data Stewards are most likely to be responsible for:
The operational data quality management procedures depend on the ability to measure and monitor the applicability of data.
Which of the following is a directive that codifies principles and management intent
into fundamental rules governing the creation, acquisition, integrity, security, quality,
and use of data and information?
A design approach for managing the risk of errors in data marts is:
The goals of data storage and operations include:
Metrics tied to Reference and Master Data Quality include:
The minority of operational metadata is generated as data is processed.
Hierarchical database model is the newest database model
When trying to integrate a large number of systems, the integration complexities can
be reduced by:
Coupling describes the degree to which two systems are intertwined.
One of the key differences between operational systems and data warehouses is:
There are several methods for masking data:
A metadata repository is essential to assure the integrity and consistent use of an enterprise data model across business processes.
The first two steps in the data science process are:
Companies do not rely on their information systems to run their operations.
Development of goals, principles and policies derived from the data governance strategy will not guide the organization into the desired future state.
Project that use personal data should have a disciplined approach to the use of that data. They should account for:
Normalisation is the process of applying rules in order to organise business complexity into stable data structures.
The Data Model Scorecard provides 10 data model quality metrics
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.
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.
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?
There are three recovery types that provide guidelines for how quickly recovery takes place and what it focuses on.
There are numerous methods of implementing databases on the cloud. The most common are:
Please select the 2 frameworks that show high-level relationships that influence how an organization manages data.
The load step of the ETL is physically storing or presenting the results of the transformation into the source system.
What are the components of a Data Governance Readiness Assessment?
The first two steps of the Reference data Change request process, as prescribed DMBOk2, include:
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.
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?
In an information management context, the short-term wins and goals often arise from the resolution of an identified problem.
The implementation of a Data Warehouse should follow these guiding principles:
What are the primary drivers of data security activities?
The term data quality refers to both the characteristics associated with high quality data and to the processes used to measure or improve the quality of data.
Effectiveness metrics for a data governance programme includes: achievement of goals and objectives; extend stewards are using the relevant tools; effectiveness of communication; and effectiveness of education.
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.
Business people must be fully engaged in order to realize benefits from the advanced analytics.
Please select the correct definition of Data Management from the options below.
SOA stand for Service Orchestrated Architecture
Volume refers to the amount of data. Big Data often has thousands of entities or elements in billions of records.
Business glossary is not merely a list of terms. Each term will be associated with other valuable metadata such as synonyms, metrics, lineage, or:
What are some of the business drivers for the ethical handling of data that Data Governance should satisfy?
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.
What key components must be included in the Implementation Roadmap?
A Business Glossary forces a business to adopt a single definition of a business term.
Adoption of a Data Governance program is most likely to succeed:
The list of V’s include:
Business Intelligence, among other things, refer to the technology that supports this kind of analysis.
A goal of data architecture is to identify data storage and processing requirements.
Data security internal audits ensure data security and regulatory compliance policies are followed should be conducted regularly and consistently.
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.
Logical abstraction entities become separate objects in the physical database design using one of two methods.
In the Information Management Lifecycle, the Data Governance Activity "Define the Data Governance Framework" is considered in which Lifecycle stage?
The categories of the Data Model Scorecard with the highest weightings include:
One common KPI of e-discovery is cost reduction.
Vulnerability is defined as:
Improving an organization’s ethical behaviour requires an informal Organizational Change Management (OCM) process.
Which of the following is an activity for defining a Data Governance strategy?
What business function is best aligned to deliver oversight to data architecture ?
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.
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.
The neutral zone is one of the phases in the Bridges’ transition phases.
Most document programs have policies related to:
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 quality management is a key capability of a data management practice and organization.
Category information is one of the types of data that can be modelled.
Effective data management involves a set of complex, interrelated processes that disable an organization to use its data to achieve strategic goals.
Data modelling is most infrequently performed in the context of systems and maintenance efforts, known as SDLC.
Match rules for different scenarios require different workflows, including:
In a SQL injection attack, a perpetrator inserts authorized database statements into a vulnerable SQL data channel, such as a stored procedure.
A data warehouse deployment with multiple ETL, storage and querying tools often
suffers due to the lack of:
Deliverables in the document and content management context diagram include:
Assessment capabilities are evaluated against a pre-determined scale with established criteria. This is important because:
Characteristics that minimise distractions and maximise useful information include, but not limited to, consistent object attributes
What are the business objectives for building a business glossary?
When presenting a case for an organization wide Data Governance program to your Senior Executive Board, which of these potential benefits would be of LEAST importance?
Please select the two classifications of database types:
Lack of automated monitoring represents serious risks, including compliance risk.
Control activities to manage metadata stores include:
Please select correct term for the following sentence: Any collection of stored data regardless of structure or content. Some large databases refer to instances and schema.
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.
Which DMBok knowledge area is most likely responsible for a high percentage of
returned mail?
The biggest business driver for developing organizational capabilities around Big Data and Data Science is the desire to find and act on business opportunities that may be discovered through data sets generated through a diversified range of processes.
In the Data Warehousing and Business Intelligence Context Diagram, a primary deliverable is the DW and BI Architecture.
An input in the Metadata management context diagram does not include:
Data Warehouse describes the operational extract, cleansing, transformation, control and load processes that maintain the data in a data warehouse.
A complexity in documenting data lineage is:
Business requirements is an input in the Data Warehouse and Business Intelligence context diagram.
A goal of metadata management is to manage data related business terminology in
order toc
Tools required to manage and communicate changes in data governance programs include
Please select the answers that correctly describes the set of principles that recognizes salient features of data management and guide data management practice.
The second stage of Kotter’s eight stage process is:
What techniques should be used and taught to produce the required ethical data handling deliverables?
A goal of reference and master data is to provide authoritative source of reconciled and quality-assessed master and reference data.
A Data Management Maturity Assessment (DMMA) can be used to evaluate data management overall, or it can be used to focus on a single Knowledge Area or even a single process.
Metadata is essential to the management of unstructured data as it id to the management of structured data.
Small reference data value sets in the logical data model can be implemented in a physical model in three common ways:
The term data quality refers to only the characteristics associated with high quality data.
Data and text mining use a range of techniques, including:
Triplestores can be classified into these categories:
Data Standards used by the enterprise must:
Enterprise Architecture domains include:
There are three basic approaches to implementing a Master Data hub environment, including:
What ISO standard defines characteristics that can be tested by any organisation in the data supply chain to objectively determine conformance of the data to this ISO standard.
Bias refers to an inclination of outlook. Please select the types of data bias:
Activities that drive the goals in the context diagram are classified into the following phases:
Three classic implementation approaches that support Online Analytical Processing include:
Managing business party Master Data poses these unique challenges:
When selecting a DMM framework one should consider of it is repeatable.
A hacker is a person who finds unknown operations and pathways within complex computer system. Hackers are only bad.
Examples of transformation include:
If two data stores are able to be inconsistent during normal operations, then the
integration approach is:
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:
Issue management is the process for identifying, quantifying, prioritizing and resolving data governance related issues, including:
Master data management includes several basic steps, which include: Develop rules for accurately matching and merging entity instances.
The goal of data architecture is to:
Data governance requires control mechanisms and procedures for, but not limited to, escalating issues to higher level of authority.
Change only requires change agents in special circumstances, especially when there is little to no adoption.
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.