NO.241 Customer relationship management systems manage Master Data about customers.

NO.242 The purpose of enterprise application architecture is to describe the structure and functionality of applications in an enterprise.

NO.243 The dependencies of enterprise technology architecture are that it acts on specified data according to business requirements.

NO.244 The goals of Data Integration and Interoperability include:

NO.245 The DMBOK support’s DAMA’s mission by:

NO.246 Please select the transition phases in Bridges’ Transition process:

NO.247 Please select the four domains of enterprise architecture:

NO.248 The purpose of data governance is to ensure that data is managed properly, according to policies and best practices. Data governance is focused on how decisions are made about data and how people and processes are expected to behave in relation to data.

NO.249 Business metadata focuses largely on the content and condition of the data and includes details related to data governance.

NO.250 Machine learning explores the construction and study of learning algorithms.

NO.251 Class operations can be:

NO.252 Creating the CDM involves the following steps:

NO.253 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.

NO.254 Data architects facilitate alignment between [1] and [2]

NO.255 Three data governance operating models types include:

NO.256 Metrics tied to Reference and Master Data Quality include:

NO.257 Two risks with the Matching process are:

NO.258 Access to data for Multidimensional databases use a variant of SQL called MDX or Multidimensional expression.

NO.259 A deliverable in the data security context diagram is the data security architecture.

NO.260 Reference and master data require governance processes, including:

NO.261 Examples of the ‘Who’ entity category include: employee; patient; player; and suspect.