DMF-1220 Exam Questions

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

Customer relationship management systems manage Master Data about customers.

Key processing steps for MDM include:

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

Product Master data can only focus on an organization's internal product and services.

Business requirements is an input in the Data Warehouse and Business Intelligence context diagram.

Primary deliverables of the Data Warehouse and Business Intelligence context diagram include:

A goal of Data warehouse and business intelligence is to support and enable ineffective business analysis and decision making by knowledge workers.

The implementation of a Data Warehouse should follow these guiding principles:

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.

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

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

CIF stands for:

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

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

Operational reports are outputs from the data stewards.

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

The Data Warehouse has a set of storage areas, including:

The impact of the changes from new volatile data must be isolated from the bulk of the historical, non-volatile DW dat

Typically, DW/BI have three concurrent development tracks:

Business Intelligence tool types include:

An implemented warehouse and its customer facing BI tool is a data product.

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

Three classic implementation approaches that support Online Analytical Processing include:

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

A data dictionary is necessary to support the use of a DW.

With reliable Metadata an organization does not know what data it has, what the data represents and how it moves through the systems, who has access to it, or what it means for the...

Deliverables in the Metadata Management context diagram include:

Poorly managed Metadata leads to, among other, redundant data and data management processes.

The goals of Metadata management include:

Metadata is described using a different set of categories, not including:

Business metadata focuses largely on the content and condition of the data and includes details related to data governance.

Operational Metadata describes details of the processing and accessing of dat

Technical Metadata provides data about the technical data, the systems that store data, and the processes that move between systems.

Metadata is essential to the management of unstructured data as it id to the management of structured data.

The minority of operational metadata is generated as data is processed.

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

Examples of business metadata include:

Examples of technical metadata include:

The business glossary should capture business terms attributes such as:

The acronym CMDB stands for:

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.

SOA stand for Service Orchestrated Architecture

All metadata management solutions include architectural layers including:

An advantage of a centralized repository include: High availability since it is independent of the source systems.

A limitation of the centralized approach include: Maintenance of a decentralized repository is costly.

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

Deliverables in the data quality context diagram include:

The term data quality refers to only the characteristics associated with high quality data.

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