DMF-1220 Data Management Fundamentals Questions and Answers

The flow of data in a data integration solution does not have to be designed and documented.

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

Big data primarily refers specifically to the volume of the data.

Managing business party Master Data poses these unique challenges:

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

Confirming and documenting understanding of different perspectives facilitate:

Advantages if a centralized metadata repository include:

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

Test environments serve many uses:

Data access control can be organized at an individual level or group level, depending on the need.

Hierarchical database model is the newest database model

Metadata management solutions include architectural layers including:

The first two steps in the data science process are:

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

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 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.

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.

Corporate Information Factory (CIF) components include:

Device security standards include:

The goals of data security include:

XML is the abbreviation for standard mark-up language.

Please select the 3 visuals that depict DAMA’s Data Management Framework.

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

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

An advantage of a centralized repository include: Quick metadata retrieval, since the repository and the query reside together.

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

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

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

A Metadata repository contains information about the data in an organization, including:

Please select the correct definition of Data Management from the options below.

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

The Zachman Framweork’s communication interrogative columns provides guidance on defining enterprise architecture. Please select answer(s) that is(are) coupled correctly:

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

As part of its transformation, the organization must identify and respond to different kinds of roadblocks. Please select the answer that is not a roadblock:

A hacker is a person who finds unknown operations and pathways within complex computer system. Hackers are only bad.

Reference data management entails the preventative maintenance of undefined domain values, definitions and the relationship within and across domain values.

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.

A sandbox is an alternate environment that allows write-only connections to production data and can be managed by the administrator.

The goals of data security practices is to protect information assets in alignment with privacy and confidentiality regulations, contractual agreements and business requirements. These requirements come from:

The Data Model Scorecard provides 10 data model quality metrics

Category information is one of the types of data that can be modelled.

The Data Warehouse (DW) is a combination of three primary components: An integrated decision support database, related software programs and business intelligence reports.

The Shewhart chart contains the following elements:

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

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

Enterprise data architecture description must include both [1] as well as [2]

Examples of transformation in the ETL process onclude:

Differentiating between data and information. Please select the correct answers based on the sentence below: Here is a marketing report for the last month [1]. It is based on data from our data warehouse [2]. Next month these results [3] will be used to generate our month-over-month performance measure [4].

Well prepared records have characteristics such as:

BI tool types include:

Quality Assurance Testing (QA) is used to test functionality against requirements.

Machine learning explores the construction and study of learning algorithms.

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

The Belmont principles that may be adapted for Information Management disciplines, include:

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

An implemented warehouse and its customer-facing BI tools is a technology product.

Customer relationship management systems manage Master Data about customers.

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.

When selecting a DMM framework one should consider of it is repeatable.

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.

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

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

A e-discovery readiness assessment should examine and identify opportunities for the commercial response program.

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 flows map and document relationships between data and:

Data modelling tools and model repositories are necessary for managing the enterprise data model in all levels.

Three classic implementation approaches that support Online Analytical Processing include:

Data parsing is the process of analysing data using pre-determined rules to define its content or value.

Data Integration and Interoperability is dependent on these other areas of data management: