DMF-1220 Data Management Fundamentals Questions and Answers

Content needs to be modular, structured, reusable and device and platform independent.

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

One common KPI of e-discovery is cost reduction.

Operational reports are outputs from the data stewards.

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

Integration of ETL data flows will usually be developed within tools specialised to manage those flows in a proprietary way.

Data Warehouse describes the operational extract, cleansing, transformation, control and load processes that maintain the data in a data warehouse.

Drivers for data governance most often focus on reducing risk or improving processes. Please select the elements that relate to the reduction in risk:

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

Part of alignment includes developing organizational touchpoints for data governance work. Some examples of touchpoints include: Procurement and Contracts; Budget and Funding; Regulatory Compliance; and the SDLC framework.

Change only requires change agents in special circumstances, especially when there is little to no adoption.

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

Consistent input data reduces the chance of errors in associating records. Preparation processes include:

All data is of equal importance. Data quality management efforts should be spread between all the data in the organization.

Enterprise data architecture usually include the following work streams:

DMMA ratings represent a snapshot of the organization’s capability level.

Data architects facilitate alignment between [1] and [2]

Data governance requires control mechanisms and procedures for, but not limited to, assignment and tracking of action items.

Real-time data integration is usually triggered by batch processing, such as historic data.

SOR Stands for:

A deliverable in the data architecture context diagram includes an implementation roadmap.

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

The warehouse has a set of storage areas, including:

Inputs in the reference and master data context diagram include:

The deliverables in the data architecture context diagram include:

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

Inputs in the data quality context diagram include:

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.

Three data governance operating models types include:

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

SOA stands for:

Metadata is described using different set of categories, including:

Enterprise data architecture project-related activities include:

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

Media monitoring and text analysis are automated methods for retrieving insights from large unstructured or semi-structured data, such as transaction data, social media, blogs, and web news sites.

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

In the Data Warehousing and Business Intelligence Context Diagram, a primary deliverable is the DW and BI Architecture.

Type of Reference Data Changes include:

Examples of business metadata include:

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.

Veracity refers to how difficult the data is to use or to integrate.

An effective team is based on two simple foundations: trust and a common goal.

Logical abstraction entities become separate objects in the physical database design using one of two methods.

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 can be assessed based on whether it is required by:

Data profiling is a form of data analysis used to inspect data and assess quality.

The ethics of data handling are complex, but is centred on several core concepts. Please select the correct answers.

ANSI 859 recommends taking into account the following criteria when determining which control level applies to a data asset:

In Resource Description Framework (RDF) terminology, a triple store is composed of a subject that denotes a resource, the predicate that expresses a relationship between the subject and the object, and the object itself.

In matching, false positives are three references that do not represent the same entity are linked with a single identifier.

Service accounts are convenient because they can tailor enhanced access for the processes that use them.

There are numerous methods of implementing databases on the cloud. The most common are:

Validity, as a dimension of data quality, refers to whether data values are consistent with a defined domain of values.

Obfuscating or redacting data is the practice of making information anonymous ot removing sensitive information. Risks are present in the following instances:

The Data Governance Council (DGC) manages data governance initiatives, issues, and escalations.

A deliverable in the data modelling and design context diagram is the logical data model.

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

SOA is an abbreviation for service orientated architecture.

Data and text mining use a range of techniques, including:

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

Test environments serve many uses:

Tools required to manage and communicate changes in data governance programs include

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.

Inputs in the data modelling and design context diagram include:

The most important reason to implement operational data quality measurements is to inform data consumers about levels of data effectiveness.

Data management organizational constructs include the following type of model.

Deliverables in the document and content management context diagram include:

Please select the correct types of data stewards:

Please select the types of DBA specializations: