GDPR and PIPEDA are examples of:
An input in the Metadata management context diagram does not include:
Effective data management involves a set of complex, interrelated processes that enable an organisation to use its data to achieve strategic goals.
Poorly managed Metadata leads to, among other, redundant data and data management processes.
There are three recovery types that provide guidelines for how quickly recovery takes place and what it focuses on.
Machine learning explores the construction and study of learning algorithms.
According to the DMBoK, Data Governance is central to Data Management. In practical terms, what other functions of Data Management are required to ensure that your Data Governance programme is successful?
Several global regulations have significant implications on data management practices. Examples include:
The first two steps of the Reference data Change request process, as prescribed DMBOk2, include:
Data Stewards are most likely to be responsible for:
Implementing a BI portfolio is about identifying the right tools for the right user communities within or across business units.
Which statement best describes the relationship between documents and records?
A data governance strategy defines the scope and approach to governance efforts. Deliverables include:
The key architecture domains include:
Data Management maturity has many goals for accomplishment including having a positive effect on culture. This is important to a Data Governance program for the following reason:
