The most useful tool for determining whether the goals of IT are aligned with the organization's goals is a balanced scorecard. A balanced scorecard is a strategic managementsystem that translates an organization's vision and mission into a set of objectives and measures across four perspectives: financial, customer, internal process, and learning and growth. A balanced scorecard helps align IT goals with organizational goals by linking them to a common strategy map that shows how IT contributes to value creation and performance improvement in each perspective. A balanced scorecard also helps monitor and evaluate IT performance against predefined targets and indicators.
Enterprise dashboard, enterprise architecture (EA), and key performance indicators (KPIs) are not the most useful tools for determining whether the goals of IT are aligned with the organization's goals. These tools may help communicate, design, or measure IT goals or activities, but they do not provide a comprehensive framework for aligning IT goals with organizational goals across multiple dimensions.

The design phase of the system development life cycle (SDLC) is where an IS auditor would expect to find that controlshave been incorporated into system specifications, because this is where the system requirements are translated intodetailed design specifications that include the technical, functional, and security aspects of the system34. The implementation phase iswhere the system is deployed and tested, the development phase is where the system is codedand unit tested, and thefeasibility phase is where the system objectives and scope are defined. References: 3: CISA Review Manual (Digital Version), Chapter 4, Section 4.2.2 4: CISA Online Review Course, Module 4, Lesson 2

Data analytics is the process of collecting, transforming, analyzing, and visualizing data to gain insights and support decision making1. Data analytics can be used to facilitate the testing of a new account creation process by applying various techniques and methods to evaluate the quality, functionality, performance, and security of the process. One of the approaches that would utilize data analytics to test the new account creation process is to review new account applications submitted in the past month for invalid dates of birth.
This approach would involve the following steps:
Extract the data of new account applications from the source system, such as a database or a web service, using appropriate tools and methods.
Transform and clean the data to ensure its accuracy, completeness, consistency, and validity, using techniques such as data profiling, data cleansing, data mapping, and data validation2.
Analyze the data to identify any anomalies, errors, or outliers in the date of birth field, using methods such as descriptive statistics, exploratory data analysis, hypothesis testing, or anomaly detection3.
Visualize the data to present the findings and insights in a clear and understandable way, using tools and techniques such as charts, graphs, dashboards, or reports.
By reviewing new account applications submitted in the past month for invalid dates of birth, the tester can use data analytics to:
Verify if the new account creation process is working as expected and meets the business requirements and specifications for the date of birth field.
Detect any defects or issues in the new account creation process that may cause invalid dates of birth to be accepted or rejected incorrectly.
Measure and monitor the performance and reliability of the new account creation process in terms of data quality, accuracy, and completeness.
Evaluate and improve the test coverage and effectiveness of the new account creation process by identifying any gaps or risks in the test cases or scenarios.
Therefore, option C is the correct answer.
Option A is not correct because attempting to submit new account applications with invalid dates of birth is not a data analytics approach, but a functional testing approach that involves executing test cases or scenarios manually or automatically to validate the behavior and functionality of the new account creation process.
Option B is not correct because reviewing the business requirements document for date of birth field requirements is not a data analytics approach, but a requirements analysis approach that involves examining and understanding the needs and expectations of the stakeholders for the new account creation process.
Option D is not correct because evaluating configuration settings for date of birth field requirements is not a data analytics approach, but a configuration testing approach that involves verifying if the settings and parameters of the new account creation process are correct and consistent with the requirements.
References:
What is Data Analytics? Definition and Examples1
Data Transformation: Definition and Examples2
Data Analysis: Definition and Examples3
Data Visualization: Definition and Examples
Functional Testing: Definition and Examples
Requirements Analysis: Definition and Examples
Configuration Testing: Definition and Examples