DMF-1220 Practice Exam Questions with Answers Data Management Fundamentals Certification

Data Storage and Operations: The design, implementation and support of stored data to maximize its value.

Data can be assessed based on whether it is required by:

The deliverables in the data architecture context diagram include:

Please select the three types of data models:

Several global regulations have significant implications on data management practices. Examples include:

Please select the two classifications of database types:

The dependencies of enterprise technology architecture are that it acts on specified data according to business requirements.

The roles associated with enterprise data architecture are data architect, data modellers and data stewards.

Malware types include:

Within each area of consideration mentioned in question 13, they should address morale adversity as per Ethical Risk Model for Sampling Projects.

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.

The load step of ETL is physically storing or presenting the results of the transformation in the target system.

Architects seek to design in a way that brings value to an organisation. To reach these goals, data architects define and maintain specifications that:

A Global ID is the MDM solution-assigned and maintained unique identifier attached to reconciled records.

Bold means doing something that might cause short term pain, not just something that looks good in a marketing email.

The need to manage data movement efficiently is a primary driver for Data Integration and Interoperability.

An Operational Data Mart is a data mart focused on tactical decision support.

CMDB provide the capability to manage and maintain Metdata specifically related to the IT assets, the relationships among them, and contractual details of the assets.

Taxonomies can have different structures, including:

Security Risks include elements that can compromise a network and/or database.

MPP is an abbreviation for Major Parallel Processing.

Machine learning explores the construction and study of learning algorithms.

Business Intelligence tool types include:

Creating the CDM involves the following steps:

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.

The business glossary application is structured to meet the functional requirements of the three core audiences:

Three data governance operating models types include:

The list of V’s include:

Characteristics that minimise distractions and maximise useful information include, but not limited to, consistent object attributes

A dimensional physical data model is usually a star schema, meaning there is one structure for each dimension.

The target of organizational change is expedition.

Changes to reference data do not need to be management, only metadata should be managed.

The neutral zone is one of the phases in the Bridges’ transition phases.

Enterprise data architecture influences the scope boundaries of project and system releases. An example of influence is data replication control.

The accuracy dimension of data quality refers to the degree that data correctly respresents ‘real-life’ entities.

Data quality issues cannot emerge at any point in the data lifecycle.

Type of Reference Data Changes include:

The goals of implementing best practices around document and content management include:

Data lineage is useful to the development of the data governance strategy.

Data and enterprise architecture deal with complexity from two viewpoints:

The DW encompasses all components in the data staging and data presentation areas, including:

The implementation of a Data Warehouse should follow guiding principles, including:

Malware refers to any infectious software created to damage, change or improperly access a computer or network.

The business glossary should capture business terms attributes such as:

Databases are categorized in three general ways:

Subtype absorption: The subtype entity attributes are included as nullable columns into a table representing the supertype entity

The operational data quality management procedures depend on the ability to measure and monitor the applicability of data.

In the Abate Information Triangle the past moves through the following echelons befor it comes insight:

Examples of transformation in the ETL process onclude:

The four A’s in security processes include:

An image processing system captures, transforms and manages images of paper and electronic documents.

There are three techniques for data-based change data capture, namely:

For each subject area logical model: Decrease detail by adding attributes and less-significant entities and relationships.

Value is the difference between the cost of a thing and the benefit derived from that thing.

An input in the Metadata management context diagram does not include:

Input in the Big Data and data science context diagram include:

Self-service is a fundamental delivery channel in the BI portfolio.

Types of metadata include:

The ISO 11179 Metadata registry, an international standard for representing Metadata in an organization, contains several sections related to data standards, including naming attributes and writing definitions.

A limitation of the centralized metadata repository approach is it may be less expensive.

The categories of the Data Model Scorecard with the highest weightings include:

Coupling describes the degree to which two systems are intertwined.

The difference between warehouses and operational systems do not include the following element:

It is unwise to implement data quality checks to ensure that the copies of the attributes are correctly stored.

Examples of concepts that can be standardized within the data architecture knowledge area include:

Principles for data asset accounting include:

The first two steps in the data science process are:

Accomplish repository scanning in two distinct approaches, including:

Effective data management involves a set of complex, interrelated processes that enable an organisation to use its data to achieve strategic goals.

A business driver for Master Data Management program is managing data quality.

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.

A control activity in the metadata management environment includes loading statistical analysis.

DBAs exclusively perform all the activities of data storage and operations.

Please select the user that best describes the following description: Uses the business glossary to make architecture, systems design, and development decisions, and to conduct the impact analysis.

Technical metadata describes details of the processing and accessing of data.

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.

Release management is critical to batch development processes that grows new capabilities.

A content strategy should end with an inventory of current state and a gap assessment.

Data Governance is at the centre if the data management activities, since governance is required for consistency within and balance between functions.

Data profiling also includes cross-column analysis, which can identify overlapping or duplicate columns and expose embedded value dependencies.

Lack of automated monitoring represents serious risks, including:

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.

Those responsible for the data-sharing environment have an obligation to downstream data consumers to provide high quality data.

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.

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.

The data in Data warehouses and marts differ. Data is organized by subject rather than function

Data handling ethics are concerned with how to procure, store, manage, use and disposeof data in ways that are aligned with ethical principles.

Three classic implementation approaches that support Online Analytical Processing include:

CIF stands for:

A general principle for managing metadata includes Responsibility.

Examples of business metadata include:

One of the deliverables in the Data Integration and Interoperability context diagram is:

The IT security policy provides categories for individual application, database roles, user groups and information sensitivity.

In gathering requirements for DW/BI projects, begin with the data goals and strategies first.

Field overloading: Unnecessary data duplication is often a result of poor data management.

SLA Stands for:

Triplestores can be classified into these categories:

Data security internal audits ensure data security and regulatory compliance policies are followed should be conducted regularly and consistently.

A node is a group of computers hosting either processing or data as part of a distributed database.

Please select the answers that correctly describes the set of principles that recognizes salient features of data management and guide data management practice.

Effective data management involves a set of complex, interrelated processes that disable an organization to use its data to achieve strategic goals.

Different levels of policy are required to govern behavior to enterprise security. For example:

What type of key is used in physical and sometimes logical relational data modelling schemes to represent a relationship?

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.

Effective document management requires clear policies and procedures, especially regarding retention and disposal of records.

Issues caused by data entry processes 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.

Managing business party Master Data poses these unique challenges:

Data governance can be understood in terms of political governance. It includes the following three function types:

The DMBOK support’s DAMA’s mission by:

Test environments serve many uses:

Data science involves the iterative inclusion of data sources into models that develop insights. Dat science depends on:

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.

The database administrator (DBA) is the most established and the most widely adopted data professional role.

Some document management systems have a module that may support different types of workflows such as:

Metadata management solutions include architectural layers including:

Structural Metadata describe srealtionships within and among resource and enables identification and retrieval.

Decentralized informality can be made more formal through a documented series of connections and accountabilities via a RACI matrix.

One common KPI of e-discovery is cost reduction.

Inputs in the data modelling and design context diagram include:

Different storage volumes include:

The number of entities in a relationship is the arity of the relationship. The most common are:

A ‘Golden Record’ means that it is always a 100% complete and accurate representation of all entities within the organization.

Issues caused by data entry processes include:

Volume refers to the amount of data. Big Data often has thousands of entities or elements in billions of records.

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.

Data governance program must contribute to the organization by identifying and delivering on specific benefits.

Lack of automated monitoring represents serious risks, including compliance risk.

Change Data Capture is a method of reducing bandwidth by filtering to include only data that has been changed within a defined timeframe.

An application DBA leads the review and administration of procedural database objects.

Elements that point to differences between warehouses and operational systems include:

The warehouse has a set of storage areas, including:

Reduced risk is a benefit of high quality data.

When constructing an organization’s operating model cultural factors must be taken into consideration.

Please select the answer that best fits the following description: Contains only real-time data.

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.

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.

Analytics models are associated with different depths of analysis, including:

Enterprise data architecture usually include the following work streams:

RACI is an acronym that is made up of the following terms.