Isaca CGEIT Dumps Questions Answers

Data stewardship is the process of defining, implementing, and enforcing policies, standards, roles, and responsibilities for the quality, security, privacy, and usage of data within an enterprise1. Data stewardship has the greatest influence on data quality assurance, as it ensures that the data is accurate, complete, consistent, timely, and fit for its intended purpose1. Data stewardship also helps to identify and resolve data quality issues, monitor and measure data quality performance, and improve data quality over time1. The other options are not as influential as data stewardship, as they are specific aspects or techniques of data management, but not comprehensive processes. Data encryption is the process of transforming data into an unreadable format to protect it from unauthorized access or modification2. Data encryption can enhance data security and privacy, but it does not directly affect data quality assurance. Data classification is the process of categorizing data based on its value, sensitivity, and risk to the enterprise. Data classification can help to apply appropriate controls and policies for data protection and compliance, but it does not directly affect data quality assurance. Data modeling is the process of creating a representation of the structure, relationships, and meaning of data within a specific domain or context. Data modeling can help to design and optimize databases and applications that use data, but it does not directly affect data quality assurance.

Risk appetite is the amount and type of risk that an organization is willing to accept in pursuit of its objectives. Risk appetite of the enterprise should be the primary consideration when developing a risk management policy for a portfolio of IT-enabled investments, because it helps to align the risk management strategy with the business strategy and goals. Risk appetite also helps to define the risk tolerance and thresholds for each investment, and to prioritize and allocate resources accordingly. Risk appetite also helps to communicate the expectations and responsibilities of the stakeholders involved in the risk management process, and to foster a risk-aware culture within the organization. References := CGEIT Review Manual, Chapter 4: Risk Optimization, Section 4.1: IT Risk Management Strategy, Subsection 4.1.1: Establishing IT Risk Appetite, Page 139.

The first step to strengthen and enforce current data governance practices after a data leakage incident is to verify data owners. Data owners are the individuals or groups who have the authority and responsibility to define, classify, protect, and manage the data assets of an enterprise1. By verifying data owners, the enterprise can ensure that the data is properly accounted for, categorized, and secured according to its value, sensitivity, and risk. Data owners can also establish data policies, standards, and procedures, as well as monitor and report on data quality, usage, and compliance1. Verifying data owners is a prerequisite for assessing data security controls, reviewing data logs, and analyzing data quality, as these activities depend on the accurate identification and assignment of data ownership roles and responsibilities. References: CGEIT Review Manual (Digital Version) or CGEIT Review Manual (Print Version), Chapter 4: Risk Optimization, Section 4.2: IT Risk Management Process, Subsection 4.2.1: IT Risk Identification, Page 163-164. Top 10 Effective Data Governance Tools.