合格できるIIBA CBDAのPDF問題集！最近更新された152問あります [Q57-Q79]

合格できるIIBA CBDAのPDF問題集！最近更新された152問あります

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質問 # 57
An online retailer of men's athletic apparel is seeking to become the market leader in the industry. To deliver on this strategy, the analytics team continuously collects data on the prices of competitor products and uses this information to adjust the retailer's prices. What type of analytics is the retailer using to maintain their pricing structure?

A. Descriptive
B. Prescriptive
C. Diagnostic
D. Predictive

正解：B

解説：
Explanation
Prescriptive analytics is the type of analytics that the retailer is using to maintain their pricing structure, because it is a technique that uses data and models to recommend the best course of action for a given situation. Prescriptive analytics can help the retailer optimize their prices based on the data collected from the competitors, the market conditions, and the customer preferences, and thus achieve their strategic goal of becoming the market leader. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 3:
Analyze Data
*Understanding the Guide to Business Data Analytics, page 17
*CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 11

質問 # 58
A Human Resource manager recently learned that their competitor reduced employee attrition rates by 20% after implementing personality tests as part of their screening process. Intrigued by the idea, the manager suggests collecting data on personality tests and attrition rates over the next year. The data from this year is then analyzed to explore possible relationships. What type of analytics has the team been asked to perform?

A. Prescriptive
B. Descriptive
C. Diagnostic
D. Predictive

正解：B

解説：
Explanation
Descriptive analytics is a type of analytics that summarizes and visualizes the data to provide an overview of what has happened or is happening, such as the attrition rates and the personality test scores of the employees12. The team has been asked to perform descriptive analytics to explore possible relationships between the data variables, without making any predictions or prescriptions for the future. References: 1:
Guide to Business Data Analytics, IIBA, 2020, p. 182: Business Analytics: Data Analysis & Decision Making,
S. Christian Albright and Wayne L. Winston, 2015, p. 5.

質問 # 59
A fifty-year-old brick and mortar business is interested in determining the potential for selling their current products online. The sales director has asked the analytics team to predict future sales for their most popular product. A simple question is formed "Would you buy this product online?" The sales director would like to survey students from local colleges and universities within a 50km radius.As a result, the team will conclude:

A. The survey will establish a poor study population
B. Focusing on a 50km radius will allow the team to complete the analysis quickly
C. The sample size being considered may be too large to work with
D. The research question will be easily answered with currently available data

正解：A

解説：
According to the Guide to Business Data Analytics, a study population is the subset of the population that meets the eligibility criteria for the research question. A study population should be representative of the population of interest and relevant to the business problem or opportunity. In this situation, the survey will establish a poor study population because the students from local colleges and universities within a 50km radius may not reflect the characteristics, preferences, and behaviours of the potential online customers for the fifty-year-old brick and mortar business. The students may have different demographics, income levels, shopping habits, and needs than the target market for the business. Therefore, the survey results may not be generalizable or applicable to the population of interest and may not provide valid and reliable insights for predicting future sales.
References: Guide to Business Data Analytics, page 48-49; CBDA Exam Blueprint, page 7; Population vs.
Sample | Definitions, Differences & Examples - Scribbr

質問 # 60
The finance manager has reported that customers are taking much longer to remit payments this year than last.
They would like help in finding a solution to address the situation. One suggestion was to offer a 10% discount to entice customers to pay their invoices in full within the first 30 days. Before offering the discount, the finance manager would like the analytics team to do some research to determine if there is value in addressing the accounts receivable problem. Which of the following is a valid question to ask in this situation?

A. How does credit score impact the customer's ability to pay?
B. Are sales decreasing when accounts receivables are increasing?
C. Have discounts been offered before?
D. Should the discount offered be set at 10% or 15%?

正解：C

解説：
According to the Guide to Business Data Analytics, one of the steps in conducting business data analytics is to identify the research questions that will guide the analysis and help answer the business problem or opportunity. The research questions should be relevant, specific, measurable, achievable, and testable. In this situation, the business problem is the delay in customer payments and the potential solution is to offer a discount. A valid question to ask in this situation is whether discounts have been offered before, and if so, what was the effect on customer behavior and profitability. This question is relevant because it can help assess the feasibility and effectiveness of the proposed solution. It is also specific, measurable, achievable, and testable, as it can be answered by collecting and analyzing historical data on customer payments and discounts.
References: Guide to Business Data Analytics, page 47-48; CBDA Exam Blueprint, page 7; [Introduction to Business Data Analytics: A Practitioner View], page 15.

質問 # 61
An online retailer of men's athletic apparel is seeking to become the market leader in the industry. To deliver on this strategy, the analytics team continuously collects data on the prices of competitorproducts and uses this information to adjust the retailer's prices. What type of analytics is the retailer using to maintain their pricing structure?

A. Descriptive
B. Prescriptive
C. Diagnostic
D. Predictive

正解：B

解説：
Prescriptive analytics is the type of analytics that the retailer is using to maintain their pricing structure, because it is a technique that uses data and models to recommend the best course of action for a given situation. Prescriptive analytics can help the retailer optimize their prices based on the data collected from the competitors, the market conditions, and the customer preferences, and thus achieve their strategic goal of becoming the market leader. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 3:
Analyze Data
*Understanding the Guide to Business Data Analytics, page 17
*CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 11

質問 # 62
A supermarket chain wants to improve supplier relations. One of the targets to track and help achieve this goal is to improve the average transaction time per order by 10%.From a SMART target perspective, what is missing?

A. is not attainable as weather conditions can slow down order times
B. S * should provide a target for each supplier
C. R - is not relevant to the goal as supplier relations is only dependent on quality of deliveries
D. T - There is no mention of the time-frame by which this target must be met

正解：D

解説：
SMART is an acronym that stands for Specific, Measurable, Achievable, Relevant, and Time-bound, which are criteria for setting effective and realistic goals1. From a SMART target perspective, what is missing in this scenario is the time-frame by which the target must be met. A time-bound target specifies the deadline or the duration for achieving the target, which helps to create a sense of urgency, motivation, and accountability2.
Without a time-frame, the target is vague and indefinite, and it is difficult to monitor and evaluate the progress and the results. For example, a time-bound target could be to improve the average transaction time per order by 10% within the next six months.
The other options are not correct explanations of what is missing. The target is attainable, as it is realistic and feasible, and it does not depend on factors that are beyond the control of the organization, such as weather conditions. The target is specific, as it provides a clear and precise description of what needs to be achieved, and it does not need to provide a target for each supplier, as that would make the target too complex and cumbersome. The target is relevant, as it is aligned with the goal of improving supplier relations, and it does not assume that supplier relations is only dependent on quality of deliveries, as transaction time is also an important factor that affects the efficiency, satisfaction, and trust of the suppliers.
References:1: Introduction to Business Data Analytics: An Organizational View, IIBA, 2019, p. 122:
Introduction to Business Data Analytics: A Practitioner View, IIBA, 2019, p. 12. : Introduction to Business Data Analytics: An Organizational View, IIBA, 2019, p. 12. : Introduction to Business Data Analytics: A Practitioner View, IIBA, 2019, p. 12.

質問 # 63
While creating a dataset for analysis, the analyst reviews the data collected and finds a large percentage of records are missing values. Which activity would the analyst perform in order to use this dataset?

A. Factor analysis
B. Clustering
C. Weighting
D. Scale validation

正解：C

解説：
Explanation
Weighting is a technique that assigns different values or weights to different records or variables in a dataset, based on their importance or relevance. Weighting can be used to handle missing values by giving them a lower weight or imputing them with a weighted average of other values. Weighting can also help to adjust for sampling bias or non-response bias in the data collection process. References:
*Understanding the Guide to Business Data Analytics, page 16
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 3:
Analyze Data
*CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 4

質問 # 64
An analyst at an Insurance company has been asked to share results and provide insights into any impacts to the business since a new government regulation took effect. The analyst is in the process of reviewing the analyzed data to identify any patterns. When interpreting results, what would be one of the questions the analyst will be asking?

A. Are the right data dimensions being used?
B. Is the data accurate based on the sources being used?
C. What do the results mean in the context of the business?
D. How will the recipients receive the results?

正解：C

解説：
According to the IIBA's Guide to Business Data Analytics, one of the steps in the data analysis process is to interpret and report results, which involves explaining the meaning, significance, and implications of the results in the context of the business problem and the stakeholders' needs1. When interpreting results, one of the questions the analyst will be asking is what do the results mean in the context of the business, which means how the results relate to the business situation, objectives, and outcomes, and how they can be used to support decision making and action taking2. For example, the analyst may ask how the new government regulation affects the business performance, operations, or strategy, and what recommendations or changes are needed to comply with the regulation and achieve the business goals.
The other options are not correct questions for interpreting results. How will the recipients receive the results is a question for presenting results, not interpreting results. Presenting results is a subsequent step after interpreting results, and it involves choosing the best format, medium, and style to communicate the results to the audience3. Are the right data dimensions being used is a question for analyzing data, not interpreting results. Analyzing data is a prior step before interpreting results, and it involves applying the appropriate techniques, tools, and methods to manipulate, transform, and explore the data4. Is the data accurate based on the sources being used is a question for sourcing data, not interpreting results. Sourcing data is a prior step before analyzing data, and it involves identifying, collecting, and validating the data from the relevant sources5.
References:1: Guide to Business Data Analytics, IIBA, 2020, p. 572: Introduction to Business Data Analytics:
A Practitioner View, IIBA, 2019, p. 253: Guide to Business Data Analytics, IIBA, 2020, p. 584: Guide to Business Data Analytics, IIBA, 2020, p. 555: Guide to Business Data Analytics, IIBA, 2020, p. 45. : Guide to Business Data Analytics, IIBA, 2020, p. 57. : Introduction to Business Data Analytics: A Practitioner View, IIBA, 2019, p. 25. : Guide to Business Data Analytics, IIBA, 2020, p. 58. : Guide to Business Data Analytics, IIBA, 2020, p. 55. : Guide to Business Data Analytics, IIBA, 2020, p. 45.

質問 # 65
The analytics team has been asked to provide an estimate of the number of customers they expect to have in 12 months. They debated how accurate that figure needs to be and determined that based on the availability of good data, they could predict within + or - 10%. This is an example of a:

A. ROM estimate
B. Definitive estimate
C. Parametric estimate
D. Delphi estimate

正解：A

解説：
A ROM estimate is a rough order of magnitude estimate that provides a quick and approximate estimate of the cost, time, or effort required for a project or a task. A ROM estimate is based on expert opinion or experience from past projects, and it usually has a large range of variation, such as + or - 10%. A ROM estimate is useful when there is limited information or data available, or when a high-level estimate is needed for planning or budgeting purposes. However, a ROM estimate also has a high degree of uncertainty and variability, and it should be refined as more details become available12 References: 1: Project Estimation Techniques Business Analysts Should Know About 2: Estimation techniques for business analysts - The Functional BA

質問 # 66
A large retail chain has asked their analytics team to complete a study on their customers' purchasing patterns.
The analyst assigned to the study has decided to draw further insight by grouping customers based on their purchasing habits.This clustering approach is an example of:

A. Untrained learning
B. Trained learning
C. Supervised learning
D. Unsupervised learning

正解：D

解説：
Unsupervised learning is a category of data analysis techniques that does not require labeled data or predefined outcomes. Unsupervised learning aims to discover patterns, structures, or relationships in the data without any guidance or supervision. Clustering is a common example of unsupervised learning, where the data is grouped into clusters based on some similarity or distance measure. Clustering can help reveal customer segments, market trends, or product preferences, among other insights.
References:Guide to Business Data Analytics, page 39; Introduction to Business Data Analytics: A Practitioner View, page 10.

質問 # 67
An analyst calculates the average, median, and mode values for a dataset.What type of analytics is the analyst performing?

A. Prescriptive
B. Descriptive
C. Diagnostic
D. Predictive

正解：B

解説：
Descriptive analytics is the type of analytics that summarizes and visualizes data to provide an overview of what has happened or is happening. Descriptive analytics uses techniques such as statistics, charts, graphs, and dashboards to display data in an understandable and meaningful way. Descriptive analytics can help analysts explore data, identify patterns, and communicate insights. Calculating theaverage, median, and mode values for a dataset is an example of descriptive analytics, as it provides a measure of central tendency for the data distribution. References:
* Certification in Business Data Analytics (IIBA ® - CBDA), IIBA, accessed on January 20, 2024.
* Business Data Analytics Certification - CBDA Competencies | IIBA®, IIBA, accessed on January 20,
2024.
* Guide to Business Data Analytics, IIBA, 2020, p. 15.
* The 4 Types Of Analytics Explained (With Examples), Analytics for Decisions, accessed on January 20,
2024.

質問 # 68
A dataset contains 10 measures of workplace sustainability. The analytics team is in need of producing a single score of sustainability. Which of the following techniques if used would achieve this objective?

A. Logistic regression
B. K means clustering
C. Linkage algorithms
D. Factor analysis

正解：D

解説：
Factor analysis is the technique that, if used, would achieve the objective of producing a single score of sustainability, because it is a technique that reduces the dimensionality of a data set by identifying the underlying factors or latent variables that explain the variation and correlation among the observed variables.
Factor analysis can help the analytics team combine the 10 measures of workplace sustainability into a smaller number of factors, and then derive a composite score ofsustainability based on the factor loadings and weights.
Factor analysis can also help the analytics team simplify and interpret the data, and identify the key drivers of sustainability. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 3:
Analyze Data
*Understanding the Guide to Business Data Analytics, page 17
*Business Data Analytics (IIBA®-CBDA Exam preparation) | Udemy, Section 3: Analyze Data, Lecture 15:
Factor Analysis

質問 # 69
A business analyst manager is planning budgets for the new year, and training opportunities for his team of business analysts. The manager sends out a survey to the team to obtain their top interests within the seven areas of training opportunities. The team results were compared against the manager's personal rating. What can be deduced from the following chart with regards to the survey results?

A. The team's top interests in training opportunities were aligned with the manager's, which included Teamwork and Adaptability
B. The team had equal interest across all training areas
C. The manager's rating did not match with the team's rating for any of the training areas
D. The team's top interests in training opportunities were aligned with the manager's, which included Negotiation & Conflict Resolution and Facilitation

正解：D

解説：
The chart shows the personal rating of the manager and the average team rating on different areas of training opportunities. Both the manager and the team rated "Negotiation & Conflict Resolution" and "Facilitation" highly, indicating a shared interest in these areas. These areas are also relevant for business analysts, as they involve skills such as communication, collaboration, problem-solving, and stakeholder management12 References: 1: 6 Charts You Can Use to Create Effective Reports | SurveyMonkey 2: Business Analysis Core Concept Model™ (BACCM™) - IIBA BABOK Guide v3

質問 # 70
A software company launched a new product in late 2016. The product manager is reviewing a Box and Whisker plot used to compare year-over-year sales, from 2017 to 2018. What is the conclusion he can make from this chart?

A. 2017 minimum and maximum sales are higher than 2018, but the 2017 median result is lower than 2018 1st quartile result
B. 2017 minimum and maximum sales are higher than 2018, and the 2017 median result is higher than the 2018 median result
C. 2018 minimum and maximum sales are higher than 2017, and the 2018 quartile results are higher than 2017 quartile results
D. 2018 minimum and maximum sales are higher than 2017, and the 2018 1st quartile is higher than 2017 median result

正解：D

質問 # 71
Which attributes from the Order entity will need to be normalized to avoid redundancies?
. Orderld
. OrderDate
. Itemld
. ItemName
. Quantity
. ItemPrice

A. Item Name
Quantity
B. ItemName
ItemPrice
C. OrderDate
ItemPrice
D. OrderDate
ItemName

正解：B

解説：
The attributes ItemName and ItemPrice need to be normalized to avoid redundancies because they depend on the attribute ItemId, which is not part of the primary key of the Order entity. This is a case of partial dependency, which violates the second normal form (2NF) of database normalization. To achieve 2NF, the Order entity should be split into two entities: Order and Item, where Item contains the attributes ItemId, ItemName, and ItemPrice, and Order contains the attributes OrderId, OrderDate, ItemId, and Quantity. This way, the ItemName and ItemPrice are stored only once for each ItemId, and the Order entity references them through a foreign key12 References: 1: Balancing Data Integrity and Performance: Normalization vs ... 2:
Normalization Process in DBMS - GeeksforGeeks

質問 # 72
A brainstorming session is conducted to identify the research questions to be explored within an analytics project. During the brainstorming activity which of the following should happen?

A. Participants should add questions as they come to mind without restriction on time limit
B. Participants should make sure the questions are unique and realistic
C. The number of questions generated should be limited to contain scope
D. Participants should avoid critiquing suggested questions raised by the group

正解：D

解説：
According to the Guide to Business Data Analytics, brainstorming is a technique used to generate a large number of ideas or questions in a short period of time1. The purpose of brainstorming is to encourage creativity and divergent thinking, not to evaluate or judge the ideas or questions. Therefore, participants should avoid critiquing suggested questions raised by the group, as this could inhibit the flow of ideas and discourage participation. The other options are not consistent with the principles of brainstorming, as they could limit the quantity or quality of the questions generated.
References:1: Guide to Business Data Analytics, IIBA, 2020, p. 32.

質問 # 73
A consumer goods manufacturer has recently completed an analytics study to understand how to improve its operational excellence. From the top highlights, online sales outperformed other channels in sales growth and there was a direct relationship between positive customer reviews and increased internet sales. Which strategic business decision may be logically derived from these results?

A. Improve quality of the products
B. Encourage customers to complete online reviews
C. Create an empowered and collaborative work culture
D. Improve operational efficiencies

正解：B

解説：
The strategic business decision that may be logically derived from the results is to encourage customers to complete online reviews, because the results show that there is a direct relationship between positive customer reviews and increased internet sales. By increasing the number and quality of online reviews, the consumer goods manufacturer can boost its online sales performance, which outperformed other channels in sales growth. Online reviews can also help the manufacturer gain customer feedback, improve customer loyalty, and enhance its brand reputation. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 5: Use Results to Influence Business Decision Making
*Understanding the Guide to Business Data Analytics, page 9
*CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 6

質問 # 74
A clinical research organization is using predictive analytics to improve patient safety and decrease costs on its clinical trials. To ensure that a standard set of tools/techniques is identified and best practices adhered to, teams are required to create scenarios to generate appropriate data for initial analysis. This practice is required because it is almost certain that data will be difficult to come by for most research. Which concern would lead the team to establish scenario development as a required technique?

A. Data reliability
B. Data reproducibility
C. Data privacy
D. Data validity

正解：D

解説：
Data validity refers to the extent to which data accurately represents the phenomenon or concept that it is intended to measure1. Data validity is essential for predictive analytics, as it affects the quality and credibility of the analysis results and the subsequent decisions or actions based on them. If data is invalid, the predictions may be inaccurate, misleading, or irrelevant. However, data validity may be challenging to ensure in clinical research, as data may be scarce, incomplete, inconsistent, or subject to errors or biases2. Therefore, the team may establish scenario development as a required technique to address this concern. Scenario development is a form of document analysis that involves creating hypothetical situations or stories based on assumptions, evidence, and logic to explore the possible outcomes or implications of a problem or opportunity3. Scenario development can help the team generate appropriate data for initial analysis by simulating different conditions, variables, or events that may affect the clinical trials, and by testing the validity of the data against the scenarios4.
References:1: Validity in data collection methods - OpenLearn - Open University, 2: Data Quality in Clinical Research - NCBI - NIH, 3: Scenario Analysis: How It Works and Examples - Investopedia, 4: Predictive Analytics using simulation models - AnyLogic

質問 # 75
A company wants to gauge the thoughts of their employees towards a new company product. On the 25th of March the interviewer makes a list of all employees who were at work on that day and then chooses a subset of those employees to interview. Which term describes the list of all employees present on March 25th?

A. Population of interest
B. Survey sample
C. Sample weights
D. Sampling frame

正解：D

解説：
The sampling frame is the term that describes the list of all employees present on March 25th, because it is a technique that defines the set of elements from which a sample is drawn. The sampling frame should ideally match the population of interest, which is the group of elements that the researcher wants to study or make inferences about. In this case, the population of interest is the employees of the company, and the sampling frame is the subset of employees who were at work on a specific day. The survey sample is the technique that selects a portion of the sampling frame to participate in the survey. The sample weights are the technique that assigns different values or importance to each element in the sample, based on their representation in the population. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 2: Source Data
*Understanding the Guide to Business Data Analytics, page 14
*CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 14

質問 # 76
After analyzing sales data, the analytics team finds that the older the customer, the more expensive the neckties purchased. The team felt this was a breakthrough insight but on closer analysis realized that other factors could account for this relationship. This is a clear indication that:

A. Causation has no relationship with correlation
B. Causation between variables does not imply correlation
C. Correlation between variables does not imply causation
D. Correlation between variables implies causation

正解：C

解説：
Explanation
The analytics team found a correlation between the age of the customer and the price of the neckties purchased, meaning that as one variable changes, the other tends to change in the same direction. However, this correlation does not imply causation, meaning that one variable does not necessarily cause the other to change. There could be other factors, such as income, preference, or quality, that affect both variables and create a spurious relationship. Therefore, the team realized that they need to investigate further to determine if there is a causal link between the variables, or if the correlation is coincidental12 References: 1: Correlation vs. Causation | Difference, Designs & Examples - Scribbr 2: Correlation vs Causation: Understanding the Differences - Statistics By Jim

質問 # 77
A data scientist is performing statistical analysis and is interested in graphically depicting the data set according to the associated quartiles Minimum, First Quartile, Median, Second Quartile, Third Quartile.
Which technique would allow for the display of this statistical five number summary?

A. Gaussian distribution
B. Box plot
C. Scatter plot
D. Multivariate histogram

正解：B

解説：
Explanation
A box plot is the technique that would allow for the display of the statistical five number summary, because it is a technique that shows the distribution of a data set using a rectangular box and whiskers. A box plot can help the data scientist visualize the minimum, maximum, median, first quartile, and third quartile of the data set, as well as any outliers or skewness. A box plot can also help the data scientist compare the variation and symmetry of different groups or categories of data. Options A, B, and C are not suitable for displaying the statistical five number summary, because they are techniques that show the frequency, relationship, or density of the data, but not the quartiles or outliers. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 3:
Analyze Data
*Understanding the Guide to Business Data Analytics, page 18
*16 Best Types of Charts and Graphs for Data Visualization [+ Guide]

質問 # 78
A future state data model is created to depict how information will be structured in a proposed solution but the analyst is also interested in modeling how and when data is transformed throughout various processes across the organization.In which model would the analyst find this information?

A. Physical data model
B. Process flows
C. Data transformation model
D. Data flow diagram

正解：D

解説：
A data flow diagram (DFD) is a graphical representation of how data flows and transforms through a system or process. A DFD shows the sources and destinations of data, the data inputs and outputs, the data transformations and logic, and the data stores and flows. A DFD can help the analyst model howand when data is transformed throughout various processes across the organization, as well as identify potential data quality issues, bottlenecks, and redundancies. A DFD can also complement a future state data model by showing the relationships and dependencies among the data entities and attributes. References:
* Certification in Business Data Analytics (IIBA ® - CBDA), IIBA, accessed on January 20, 2024.
* Business Data Analytics Certification - CBDA Competencies | IIBA®, IIBA, accessed on January 20,
2024.
* Guide to Business Data Analytics, IIBA, 2020, p. 19-20.
* Data Flow Diagram - Everything You Need to Know About DFD, Visual Paradigm, accessed on January 20, 2024.

質問 # 79
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