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| Section | Objectives |
|---|---|
| Topic 1: Decision-Making Frameworks | - Cost-Benefit Analysis - Risk Analysis and Assessment - Rational Decision Models - Evidence-Based Decision Making |
| Topic 2: Data-Driven Culture and Communication | - Ethical Considerations in Data Use - Building Data-Informed Organizations - Presenting Data Insights - Stakeholder Communication |
| Topic 3: Data Analysis Fundamentals | - Data Types and Measurement Scales - Descriptive Statistics - Data Quality and Cleaning - Data Visualization Techniques |
| Topic 4: Business Intelligence and Analytics | - Data Mining Concepts - Key Performance Indicators (KPIs) - Dashboards and Reporting - Predictive Analytics Basics |
>> Data-Driven-Decision-Making시험패스 인증덤프문제 <<
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질문 # 30
According to quality management principles, which two continuous improvement commitments should every individual in an organization make?
Choose 2 answers.
정답：A,B
설명：
Quality management emphasizescontinuous improvement at the individual levelas a foundation for organizational excellence. In data-driven decision making, this involves a commitment by every individual to enhance both theirskillsandeffectivenessover time.
Increasing one's skills ensures that employees remain competent, adaptable, and capable of using analytical tools and data effectively. Improving effectiveness focuses on applying those skills efficiently to produce better outcomes, reduce errors, and add value to organizational processes.
Independent work processes and expert-level objectives are not universal expectations for all employees and may not align with collaborative quality frameworks. Continuous improvement is incremental and inclusive, encouraging consistent growth rather than elite specialization.
Therefore, the correct answers areA and B.
질문 # 31
What is the purpose of the quality management principle of dedication to fact-based decision-making?
정답：D
설명：
The principle offact-based decision-makingemphasizes using reliable data and objective analysis rather than intuition or opinion. In data-driven decision making, this principle exists primarily toreduce bias and increase trust in organizational plans and decisions.
When decisions are grounded in verified data, assumptions are challenged, personal biases are minimized, and outcomes are more predictable. This builds confidence among stakeholders and supports transparency and accountability.
Customer loyalty, waste elimination, and quality effectiveness may be indirect benefits, but the core purpose is ensuring that decisions are objective, defensible, and evidence-based. Therefore, the correct answer isD.
질문 # 32
Which type of analytics classification uses experimental design and optimization to suggest a course of action?
정답：A
설명：
Prescriptive analyticsis the analytics classification that uses experimental design and optimization techniques to suggest a specific course of action. In data-driven decision making, prescriptive analytics represents the most advanced stage of analytics, as it not only predicts outcomes but also recommends decisions that lead to optimal results.
Descriptive analytics summarizes historical data to explain what has already happened, while predictive analytics uses statistical and probabilistic models to estimate what is likely to happen in the future. Diagnostic analytics focuses on understanding why something happened by identifying root causes. In contrast, prescriptive analytics answers the critical question:what should be done.
Prescriptive analytics relies on methods such as optimization models, simulation, decision trees, and experimental design. These techniques evaluate multiple scenarios, constraints, and objectives to identify the best possible action. For example, organizations use prescriptive analytics to optimize pricing, allocate resources efficiently, schedule operations, or determine optimal investment strategies.
Within data-driven decision-making frameworks, prescriptive analytics bridges analysis and action by directly supporting managerial decision-making. It transforms analytical insights into concrete recommendations that can be implemented to improve performance and outcomes. Therefore, the correct answer isC, as prescriptive analytics explicitly uses experimental design and optimization to suggest a course of action.
질문 # 33
A student with a degree is presumed to already have a bachelor's degree. Which type of data does this represent?
정답：C
설명：
This question refers to categorizing information rather than measuring it numerically. The phrase "a student with a degree" identifies a classification or label, not a value with mathematical meaning. Nominal data are used to place observations into distinct categories without any inherent numerical order or ranking. In this case, the student is being grouped according to degree status, which is a named category. Interval and ratio data are numerical measurement scales, so they do not apply here. Ordinal data involve ranked categories, such as low, medium, and high, or freshman through senior, where order matters. Here, the information does not describe rank or position; it simply identifies a class of person based on a characteristic. Even though the phrase mentions a bachelor's degree, the key issue is that the information is categorical rather than numeric.
Therefore, this is best understood as nominal data. In data analysis, recognizing nominal variables is important because they are usually summarized with counts, percentages, or category-based comparisons rather than means or standard deviations.
질문 # 34
How should a marketing consulting firm perform a cluster analysis for a new granola bar?
정답：D
설명：
Cluster analysisis an unsupervised learning technique used to group observations based on similarity. In data- driven decision making, it is commonly used formarket segmentation, allowing firms to identify distinct customer groups with similar preferences or behaviors.
For a new granola bar, cluster analysis helps determine which consumer segments exist, such as health- conscious buyers, convenience-focused consumers, or price-sensitive shoppers. This enables targeted marketing strategies and product positioning.
Understanding reasons for purchase requires survey or causal analysis, not clustering. Competitor benchmarking and trend analysis involve different analytical techniques.
Therefore, the correct answer isB, determining different segments or groups to target.
질문 # 35
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2026 ITDumpsKR 최신 Data-Driven-Decision-Making PDF 버전 시험 문제집과 Data-Driven-Decision-Making 시험 문제 및 답변 무료 공유: https://drive.google.com/open?id=1JQNMiALaCn3OF2tNK9KN2AdUhCZH7idV