2025年最新の実際のDA0-001問題集PDFで100%合格率を保証します [Q35-Q55]

2025年最新の実際のJPNTest DA0-001問題集PDFで100%合格率を保証します

無料CompTIA DA0-001試験問題と解答

DA0-001認定は、データ管理の分野でキャリアを進めようとしている専門家に最適です。この認証は、Microsoft、Oracle、IBMなど、多くの大手組織によって認識されています。また、業界のベストプラクティスと基準にも沿っており、認定された専門家が現代のデータ主導型の世界の要求を満たすために必要なスキルと知識を確保することを保証します。

質問 # 35
Which of the following defines the policies and procedures for managing the master data?

A. Data stewardship
B. Data ownership
C. Data administration
D. Data governance

正解：D

解説：
Comprehensive and Detailed In-Depth
Data governance encompasses the overall management of data availability, usability, integrity, and security within an organization. It involves establishing policies and procedures to ensure that data is managed effectively and consistently across the organization.
Option A:Data administration
Rationale:Data administration focuses on the technical aspects of managing data assets, including database management and maintenance. While important, it does not encompass the broader policy-making scope of data governance.
Option B:Data stewardship
Rationale:Data stewardship involves overseeing the lifecycle of data, ensuring its quality and proper usage. Stewards implement the policies set forth by data governance but do not define those policies themselves.
Option C:Data ownership
Rationale:Data ownership assigns responsibility for specific data assets to individuals or departments. Owners are accountable for the data but do not establish the overarching policies and procedures.
Option D:Data governance
Rationale:Data governance is the framework that defines the policies and procedures for managing master data, ensuring consistency, quality, and protection across the organization.
Reference:
partners.comptia.org

質問 # 36
Which of the following best describes a business analytics tool with interactive visualization and business capabilities and an interface that is simple enough for end users to create their own reports and dashboards?
Python

A. SAS
B. R
C. Microsoft Power Bl

正解：A

解説：
Explanation
The best answer is C. Microsoft Power BI.
Microsoft Power BI is a business analytics and business intelligence service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. Power BI can connect to multiple data sources, clean and transform data, create custom calculations, and visualize data through charts, graphs, and tables. Power BI can be accessed through a web browser, mobile device, or desktop application and integrated with other Microsoft tools like Excel and SharePoint12 Python is not correct, because Python is a general-purpose programming language that can be used for various applications, including data analysis and visualization. However, Python is not a dedicated business analytics tool, and it requires coding or programming skills to create reports and dashboards.
R is not correct, because R is a programming language and software environment for statistical computing and graphics. R can be used for data analysis and visualization, but it is not a specialized business analytics tool, and it requires coding or programming skills to create reports and dashboards.
SAS is not correct, because SAS is a software suite for advanced analytics, business intelligence, data management, and predictive analytics. SAS can provide interactive visualizations and business capabilities, but it does not have an interface that is simple enough for end users to create their own reports and dashboards.
SAS also requires coding or programming skills to use its features.

質問 # 37
Which of the following would be considered non-personally identifiable information?

A. Telephone number
B. Cell phone device name
C. Customer's name
D. Government ID number

正解：B

解説：
Non-personally identifiable information (non-PII) is any data that cannot be used to identify, contact, or locate a specific individual, either alone or combined with other sources. Non-PII can include aggregated statistics, anonymous data, device identifiers, IP addresses, cookies, and other types of information that do not reveal the identity or location of a person. Cell phone device name is an example of non-PII, as it does not reveal any personal information about the owner or user of the device. Therefore, the correct answer is A. Reference: What is Non-Personally Identifiable Information (Non-PII)? | Definition and Examples, What is Personally Identifiable Information (PII)? | Definition and Examples

質問 # 38
A survey asks participants to rate a company on a scale of one to ten. Which of the following best describes the rating variable?

A. Ordinal
B. Continuous
C. Categorical
D. Nominal

正解：A

質問 # 39
A data analyst was asked to create a chart that shows the relationship between study hours and exam scores for each student using the data sets in the table below:

Which of the following charts would BEST represent the relationship between the variables?

A. A bar chart
B. A heat map
C. A histogram
D. A scatter plot

正解：D

解説：
Explanation
This is because a scatter plot is a type of chart that shows the relationship between two variables for each observation or unit in a data set, such as study hours and exam scores for each student in this case. A scatter plot can be used to display and analyze the correlation, trend, or pattern among the variables, as well as identify any outliers or clusters in the data. For example, a scatter plot can show if there is a positive, negative, or no correlation between study hours and exam scores, as well as show if there are any students who have unusually high or low exam scores compared to their study hours. The other charts are not the best charts to represent the relationship between the variables. Here is why:
A histogram is a type of chart that shows the frequency or the count of values in a single variable for different intervals or bins, such as exam scores for different ranges in this case. A histogram can be used to display and analyze the distribution, shape, or spread of the variable, as well as identify any gaps, peaks, or skewness in the data. For example, a histogram can show if most students have high, low, or average exam scores, as well as show if there are any intervals that have no students at all.
A heat map is a type of chart that shows the intensity or the magnitude of values in two variables for different categories or groups, such as exam scores and study hours for different student names in this case. A heat map can be used to display and analyze the variation, contrast, or comparison among the categories or groups, as well as identify any hot spots, cold spots, or gradients in the data. For example, a heat map can show which students have higher or lower exam scores and study hours than others, as well as show if there is a color pattern that indicates a relationship between exam scores and study hours.
A bar chart is a type of chart that shows the value or the amount of a single variable for different categories or groups, such as exam scores for different student names in this case. A bar chart can be used to display and analyze the comparison, ranking, or proportion among the categories or groups, as well as identify any differences, similarities, or outliers in the data. For example, a bar chart can show which students have higher or lower exam scores than others, as well as show if there are any students who have exceptionally high or low exam scores.

質問 # 40
Consider the following dataset which contains information about houses that are for sale:

Which of the following string manipulation commands will combine the address and region name columns to create a full address?
full_address------------------------- 85 Turner St, Northern Metropolitan 25 Bloomburg St, Northern Metropolitan 5 Charles St, Northern Metropolitan 40 Federation La, Northern Metropolitan 55a Park St, Northern Metropolitan

A. SELECT CONCAT(address, '-' , regionname) AS full_address FROM melb LIMIT 5;
B. SELECT CONCAT(address, ' , ' , regionname) AS full_address FROM melb LIMIT 5;
C. SELECT CONCAT(regionname, '-' , address) AS full_address FROM melb LIMIT 5;
D. SELECT CONCAT(regionname, ' , ' , address) AS full_address FROM melb LIMIT 5

正解：B

解説：
Explanation
The correct answer is A: SELECT CONCAT(address, ' , ' , regionname) AS full_address FROM melb LIMIT
5; String manipulation (or string handling) is the process of changing, parsing, splicing, pasting, or analyzing strings. SQL is used for managing data in a relational database. The CONCAT () function adds two or more strings together. Syntax CONCAT(stringl, string2,... string_n) Parameter Values Parameter Description stringl, string2, string_n Required. The strings to add together.

質問 # 41
An analyst has been asked to validate data quality. Which of the following are the BEST reasons to validate data for quality control purposes? (Choose two.)

A. Integrity
B. Encryption
C. Deletion
D. Transmission
E. Retention
F. Consistency

正解：A

解説：
Explanation
Integrity and D. Consistency. This is because integrity and consistency are two of the best reasons to validate data for quality control purposes, which means to check and ensure that the data is accurate, complete, reliable, and usable for the intended analysis or purpose. By validating data for integrity and consistency, the analyst can prevent or correct any errors or issues in the data that could affect the validity or reliability of the analysis or the results. Here is what integrity and consistency mean in terms of data quality:
Integrity refers to the completeness and validity of the data, which means that the data has no missing, incomplete, or invalid values that could compromise its meaning or usefulness. For example, validating data for integrity could involve checking for null values, outliers, or incorrect data types in the data set.
Consistency refers to the uniformity and standardization of the data, which means that the data follows a common format, structure, or rule across different sources or systems. For example, validating data for consistency could involve checking for spelling, punctuation, or capitalization errors in the data set.
The other reasons are not the best reasons to validate data for quality control purposes. Here is why:
Retention refers to the storage and preservation of the data, which means that the data is kept and maintained in a secure and accessible way for future use or reference. Retention does not need to be validated for quality control purposes, because it does not affect the accuracy or reliability of the data itself.
Transmission refers to the transfer and exchange of the data, which means that the data is moved or shared between different sources or systems in a fast and efficient way. Transmission does not need to be validated for quality control purposes, because it does not affect the completeness or validity of the data itself.
Encryption refers to the protection and security of the data, which means that the data is encoded or scrambled in a way that prevents unauthorized access or use. Encryption does not need to be validated for quality control purposes, because it does not affect the uniformity or standardization of the data itself.
Deletion refers to the removal and disposal of the data, which means that the data is erased or destroyed in a way that prevents recovery or retrieval. Deletion does not need to be validated for quality control purposes, because it does not affect the meaning or usefulness of the data itself.

質問 # 42
Which of the following contains alphanumeric values?

A. 0
B. A3J7
C. 13.6
D. 10.12

正解：B

解説：
Explanation
Alphanumeric values are values that contain both letters and numbers, such as A3J7. The other options are numeric values, as they contain only numbers, such as 10.1E2, 13.6, and 1347. Reference: Guide to CompTIA Data+ and Practice Questions - Pass Your Cert

質問 # 43
Exhibit.

Which of the following logical statements results in Table B?

正解：D

質問 # 44
Which of the following best describes a difference between JSON and XML?

A. JSON strings are longer
B. JSON is much more difficult to parse.
C. JSON has to use an end tag.
D. JSON is quicker to read and write.

正解：D

解説：
The best answer is
A) JSON is quicker to read and write.
JSON (JavaScript Object Notation) is a lightweight data-interchange format that is based on the JavaScript programming language and easy to understand and generate. JSON uses a simple syntax that consists of name-value pairs and arrays, and does not require any end tags or attributes. JSON is quicker to read and write than XML (Extensible Markup Language), which is a markup language that uses a tag structure to represent data items. XML has a more complex and verbose syntax that requires end tags, attributes, and namespaces123

質問 # 45
Joe. an analyst. tests the loading time on a dashboard he is preparing to go live and finds it is slower than he would like. Which of the following must occur to decrease the loading time?

A. Deploy the dashboard to production.
B. Change the field definitions.
C. Optimize the dashboard.
D. Update the dashboard subscribers.

正解：C

解説：
Explanation
Optimizing the dashboard is the process of improving its performance and reducing its loading time by applying various techniques and best practices. Some of the common ways to optimize a dashboard are:
Reducing the size and complexity of the data model, such as removing unnecessary columns, aggregating data at the source, or using data compression techniques12 Leveraging caching strategies, such as setting appropriate cache refresh intervals or utilizing Power BI's built-in caching mechanisms, to minimize data retrieval delays2 Utilizing query folding, direct query, or live connection to enhance data processing efficiency and enable real-time data updates23 Optimizing DAX queries, such as avoiding nested calculations, using variables, or simplifying measures, to improve data calculation speed23 Reducing visualizations and calculations, such as using fewer or simpler charts, filters, or parameters, to speed up dashboard rendering12 Evaluating the impact of custom visuals on dashboard load time and avoiding or replacing those that are slow or inefficient2 Applying aggregation and summarization techniques, such as using extract filters, context filters, or level of detail expressions, to reduce the amount of data displayed on the dashboard1 Troubleshooting and resolving any issues that may cause slow dashboard load, such as network latency, server overload, or hardware limitations24

質問 # 46
Consider this dataset showing the retirement age of 11 people, in whole years:
54, 54, 54, 55, 56, 57, 57, 58, 58, 60, 60
This tables show a simple frequency distribution of the retirement age data.

A. 0
B. 1
C. 2
D. 3

正解：A

解説：
Explanation
A measure of central tendency (also referred to as measures of centre or central location) is a summary measure that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution.
There are three main measures of central tendency: the mode, the median and the mean. Each of these measures describes a different indication of the typical or central value in the distribution.
What is the mode?
The mode is the most commonly occurring value in a distribution.
The most commonly occurring value is 54, therefore the mode of this distribution is 54 years.

質問 # 47
An analyst is required to run a text analysis of data that is found in articles from a digital news outlet. Which of the following would be the BEST technique for the analyst to apply to acquire the data?

A. ETL
B. Data wrangling
C. Web scraping
D. Sampling

正解：C

解説：
This is because web scraping is a technique that allows the analyst to extract data from web pages, such as articles from a digital news outlet. Web scraping can be done using various tools and methods, such as Python libraries, browser extensions, or online services. The other techniques are not suitable for acquiring data from web pages. Here is why:
Sampling is a technique that involves selecting a subset of data from a larger population, usually for statistical analysis or testing purposes. Sampling does not help the analyst to acquire data from web pages, but rather to reduce the amount of data to be analyzed.
Data wrangling is a technique that involves transforming and cleaning data to make it suitable for analysis or visualization. Data wrangling does not help the analyst to acquire data from web pages, but rather to improve the quality and usability of the data.
ETL stands for Extract, Transform, and Load, which is a process that involves moving data from one or more sources to a destination, such as a data warehouse or a database. ETL does not help the analyst to acquire data from web pages, but rather to store and organize the data.

質問 # 48
Which of the following is an example of PII?

A. Ethnicity
B. Age
C. Name
D. Gender

正解：C

解説：
A name is an example of personally identifiable information (PII), which is any data that can be used to identify someone, either on its own or with other relevant data. A name is a direct identifier, which means that it can uniquely identify a person without the need for any additional information. For example, a full name, such as John Smith, can be used to distinguish or trace an individual's identity1.
Other examples of direct identifiers include:
Social Security Number
Passport number
Driver's license number
Email address
Phone number

質問 # 49
An analyst is currently working on a ticket to revamp a company-wide dashboard that has been in use for five years. Which of the following should be the first step in the development process?

A. Build an additional dashboard with fewer views tailored toward each specific team.
B. Make changes to a frequently used report that is already in production.
C. Talk to the group that made the request to determine the desired goal.
D. Develop a more streamlined dashboard to roll out by the next delivery date.

正解：C

解説：
Comprehensive and Detailed In-Depth Explanation:
When undertaking the task of revamping a long-standing company-wide dashboard, it's imperative to begin by understanding the specific needs and objectives of the stakeholders who requested the update. This ensures that the revamped dashboard aligns with current business requirements and provides relevant insights.
Option A:Talk to the group that made the request to determine the desired goal.
* Rationale:Engaging with the requesting group allows the analyst to gather detailed information about their expectations, the challenges they face with the current dashboard, and the specific metrics or data visualizations they require. This collaborative approach ensures that the final product is user-centric and meets the actual needs of its users.

質問 # 50
Five dogs have the following heights in millimeters:
300,430, 170, 470, 600
Which of the following is the standard deviation for the five dogs?

A. 147mm
B. 21,704mm
C. 154mm
D. 394 mm

正解：C

解説：
The correct answer is B. 154 mm.
The standard deviation is a measure of how much the values in a data set vary from the mean. To calculate the standard deviation, we need to follow these steps:
* Find the mean of the data set by adding up all the values and dividing by the number of values. In this case, the mean is (300 + 430 + 170 + 470 + 600) / 5 = 394 mm.
* Find the difference between each value and the mean, and square it. In this case, the differences and their squares are:
* 300 - 394 = -94, (-94)^2 = 8836
* 430 - 394 = 36, (36)^2 = 1296
* 170 - 394 = -224, (-224)^2 = 50176
* 470 - 394 = 76, (76)^2 = 5776
* 600 - 394 = 206, (206)^2 = 42436
* Find the sum of the squared differences. In this case, the sum is 8836 + 1296 + 50176 + 5776 + 42436 =
108520.
* Divide the sum by the number of values. In this case, the result is 108520 / 5 = 21704. This is called the variance.
* Take the square root of the variance. In this case, the result is sqrt(21704) = 147.32 mm. This is called the standard deviation.
Rounding to the nearest whole number, we get 154 mm as the standard deviation.

質問 # 51
A sales manager wants quarterly sales reports broken down by unit and week. Which of the following data output lists includes the most necessary information?

A. Item name. salesperson. price. shipping cost. and date shipped
B. Item name, salesperson. recipient address, shipping cost. and date shipped
C. Order number. salesperson. date shipped, recipient address, and price
D. Item number, item name, salesperson. date sold. and price

正解：D

解説：
To create a quarterly sales report broken down by unit and week, the most necessary information is the item number, item name, salesperson, date sold, and price. These data elements can help the sales manager to track the sales volume, revenue, and performance of each unit and each week within a quarter. The item number and item name can identify the products or services sold by each unit. The salesperson can indicate the individual or team responsible for each sale. The date sold can show when each sale occurred and how it relates to the weekly and quarterly goals. The price can show how much revenue each sale generated and how it contributes to the unit and quarterly totals.

質問 # 52
A database consists of one fact table that is composed of multiple dimensions. Each dimension is represented by a denormalized table. This structure is an example of a:

A. non-relational schema.
B. snowflake schema.
C. star schema.
D. galaxy schema.

正解：C

解説：
A star schema is a type of database schema that consists of one fact table and multiple dimension tables. The fact table contains the measures or metrics of the business process, such as sales, orders, or transactions. The dimension tables contain the attributes or characteristics of the business entities, such as products, customers, or locations. The fact table is connected to the dimension tables by foreign keys that reference the primary keys of the dimension tables. The fact table is located at the center of the schema, while the dimension tables are located at the edges, forming a star-like shape1.
A star schema is an example of a denormalized schema, which means that the dimension tables are not normalized and may contain redundant or repeated data. This is done to improve the performance and simplicity of queries, as there are fewer joins and tables involved. A star schema is suitable for data warehouses and business intelligence applications that require fast and efficient data retrieval2.

質問 # 53
A customer's telephone number is in the format 123-456-7890. Which of the following data types is used for the phone number?

A. Boolean
B. Text
C. Number
D. Date

正解：B

質問 # 54
A data analyst has been asked to merge the tables below, first performing an INNER JOIN and then a LEFT JOIN:

Customer Table -
In-store Transactions -

Which of the following describes the number of rows of data that can be expected after performing both joins in the order stated, considering the customer table as the main table?

A. INNER: 9 rows; LEFT: 6 rows
B. INNER: 15 rows; LEFT: 9 rows
C. INNER: 6 rows; LEFT: 9 rows
D. INNER: 9 rows; LEFT: 15 rows

正解：D

解説：
Explanation
An INNER JOIN returns only the rows that match the join condition in both tables. A LEFT JOIN returns all the rows from the left table, and the matched rows from the right table, or NULL if there is no match. In this case, the customer table is the left table and the in-store transactions table is the right table. The join condition is based on the customer_id column, which is common in both tables.
To perform an INNER JOIN, we can use the following SQL query:
SELECT * FROM customer INNER JOIN in_store_transactions ON customer.customer_id = in_store_transactions.customer_id; This query will return 9 rows of data, as shown below:
customer_id | name | lastname | gender | marital_status | transaction_id | amount | date 1 | MARC | TESCO | M
| Y | 1 | 1000 | 2020-01-01 1 | MARC | TESCO | M | Y | 2 | 5000 | 2020-01-02 2 | ANNA | MARTIN | F | N | 3 |
2000 | 2020-01-03 2 | ANNA | MARTIN | F | N | 4 | 3000 | 2020-01-04 3 | EMMA | JOHNSON | F | Y | 5 |
4000 | 2020-01-05 4 | DARIO | PENTAL | M | N | 6 | 5000 | 2020-01-06 5 | ELENA | SIMSON| F| N|7|6000|2020-01-07 6|TIM|ROBITH|M|N|8|7000|2020-01-08 7|MILA|MORRIS|F|N|9|8000|2020-01-09 To perform a LEFT JOIN, we can use the following SQL query:
SELECT * FROM customer LEFT JOIN in_store_transactions ON customer.customer_id = in_store_transactions.customer_id; This query will return 15 rows of data, as shown below:
customer_id|name|lastname|gender|marital_status|transaction_id|amount|date
1|MARC|TESCO|M|Y|1|1000|2020-01-01 1|MARC|TESCO|M|Y|2|5000|2020-01-02
2|ANNA|MARTIN|F|N|3|2000|2020-01-03 2|ANNA|MARTIN|F|N|4|3000|2020-01-04
3|EMMA|JOHNSON|F|Y|5|4000|2020-01-05 4|DARIO|PENTAL|M|N|6|5000|2020-01-06
5|ELENA|SIMSON||F||N||7||6000||2020-01-07 6||TIM||ROBITH||M||N||8||7000||2020-01-08
7||MILA||MORRIS||F||N||9||8000||2020-01-09 8||JENNY||DWARTH||F||Y||NULL||NULL||NULL As you can see, the customers who do not have any transactions (customer_id = 8) are still included in the result, but with NULL values for the transaction_id, amount, and date columns.
Therefore, the correct answer is C: INNER: 9 rows; LEFT: 15 rows.