リアルなDA0-001最新試験GoShiken 2025年最新ののDA0-001練習テスト問題集を提供しています
全問DA0-001問題集でandCompTIA Data+ Certification Examトレーニングコース受験生を学習してパスさせるCompTIA Data+ Certification Exam試験無料問題集！
Comptia Data+認定は、データ管理における候補者の知識とスキルを実証する国際的に認められた認定です。この認定は、トップIT企業によって認識されており、より良い雇用機会とより高い給与につながる可能性があります。認定は3年間有効であり、候補者は継続教育ユニット（CEU）を獲得するか、試験の最新バージョンに合格することで認定を更新できます。
認証は世界中の組織に認められており、認定された専門家はキャリアを進め、新しい機会を追求するために最適な立場にあります。この認証はまた、雇用主に求職者のスキルと知識を評価する手段を提供し、より情報に基づいた採用決定を下すのに役立ちます。
質問 # 85
Andy is a pricing analyst for a retailer. Using a hypothesis test, he wants to assess whether people who receive electronic coupons spend more on average.
What should Andy's null hypothesis be?
- A. People who receive electronic coupons do not spend more on average.
- B. People who receive electronic coupons spend more on average.
- C. People who receive electronic coupons spend less on average.
- D. People who do not receive electronic coupons spend more on average.
正解：A
解説：
The null hypothesis presumes the status quo. Andy is testing whether or not people who receive an electronic coupon spend more on average, so, the null hypothesis states that people who receive the coupon do spend more on average.
質問 # 86
A data analyst needs to present the results of an online marketing campaign to the marketing manager. The manager wants to see the most important KPIs and measure the return on marketing investment. Which of the following should the data analyst use to BEST communicate this information to the manager?
- A. A spreadsheet of the raw data from all marketing campaigns and channels
- B. A summary with statistics, conclusions, and recommendations from the data analyst
- C. A sell-service dashboard that allows the manager to look at the company's annual budget performance
- D. A real-time monitor that allows the manager to view performance the day the campaign was launched
正解：B
解説：
A summary with statistics, conclusions, and recommendations from the data analyst is the best way to communicate the results of an online marketing campaign to the marketing manager. A summary can provide a concise and clear overview of the most important KPIs and measure the return on marketing investment, as well as highlight the main findings and insights from the data analysis. A summary can also include actionable suggestions and best practices for improving the campaign performance and achieving the marketing objectives. A summary is different from other options, such as a real-time monitor, a self-service dashboard, or a spreadsheet of raw data, which may not provide enough context, interpretation, or guidance for the manager. Therefore, the correct answer is D. References: How to Write a Data Analysis Report: 6 Essential Tips, How to Write a Marketing Report (with Pictures) - wikiHow
質問 # 87
A data analyst is using a two-tailed, independent t-test to determine whether the type of stretching, dynamic or static, has any influence on a dancer's flexibility. Which of the following is the alternative hypothesis?
- A. There is a difference in a dancer's flexibility between static and dynamic stretching.
- B. A dancer's flexibility is improved through static stretching.
- C. The means of the static and dynamic stretching groups do not differ from each other.
- D. The change in a dancer's flexibility is not equal to zero.
正解：A
質問 # 88
Which of the following data sampling methods involves dividing a population into subgroups by similar characteristics?
- A. Systematic
- B. Simple random
- C. Convenience
- D. Stratified
正解：D
解説：
Stratified sampling is a data sampling method that involves dividing a population into subgroups by similar characteristics, such as age, gender, income, etc. Then, a simple random sample is drawn from each subgroup. This method ensures that each subgroup is adequately represented in the sample and reduces the sampling error. Reference: CompTIA Data+ Certification Exam Objectives, page 11.
質問 # 89
A data analyst needs to create a dashboard to help identify trends in the data sets. Which of the following is an appropriate consideration for dashboard development?
- A. A comparison of data sets
- B. A report from the data source
- C. Data sources and attributes
- D. Frequently asked questions
正解：C
解説：
When creating a dashboard to identify trends in data sets, the most appropriate consideration is the data sources and attributes. This is because the quality, reliability, and structure of the data sources directly influence the dashboard's ability to accurately reflect trends. Attributes, such as the type of data and the time frame it covers, are crucial for trend analysis. A well-designed dashboard should provide a clear and intuitive representation of the data, allowing for easy identification of trends and patterns.
Frequently asked questions (B) can inform the design of the dashboard but are not a direct consideration for the development process itself. A report from the data source might be an output of the dashboard but does not guide its development. A comparison of data sets (D) could be a feature of the dashboard, but the underlying data sources and attributes must be considered first to ensure accurate and meaningful comparisons.
References:
* Best practices in dashboard design emphasize the importance of understanding and consolidating different data sources and creating a mix of useful metrics, which aligns with the choice of data sources and attributes1.
* Fundamental dashboard design principles include the clear and efficient display of information, which is dependent on the proper selection and use of data sources and attributes2.
* Effective dashboard communication is achieved by using colors, shapes, sizes, labels, and legends meaningfully, all of which rely on the underlying data sources and attributes3.
質問 # 90
When would you show time on a standard line chart?
- A. Color
- B. Y-axis
- C. Legend
- D. X-axis
正解：D
質問 # 91
A data analyst has a set with more than 40.000 rows in the sample schema below:
The analyst would like to create one column that contains the customers' birth dates. Which of the following data quality dimensions would BEST explain the reason for compilation?
- A. Data accuracy
- B. Data integrity
- C. Data completeness
- D. Data duplication
正解：B
解説：
Explanation
Data integrity is the dimension that measures the consistency and validity of data across different data sources.
In this case, the data analyst wants to create one column that contains the customers' birth dates, but the data is stored in different formats and locations in the sample schema. For example, some customers have their birth dates in the customer table, while others have their birth years in the sales table. To compile the data into one column, the data analyst needs to ensure that the data is consistent and valid across the tables. Therefore, data integrity is the best explanation for the reason for compilation. References: Data Quality Dimensions - DATAVERSITY, The 6 Data Quality Dimensions with Examples | Collibra
質問 # 92
A data analyst needs to collect a similar proportion of data from every state. Which of the following sampling methods would be the most appropriate?
- A. Random sampling
- B. Stratified sampling
- C. Systematic sampling
- D. Convenience sampling
正解：B
解説：
Explanation
The best sampling method for the data analyst's need is C. Stratified sampling.
Stratified sampling is a type of probability sampling that involves dividing the population into homogeneous groups or strata based on some characteristic, such as state, and then randomly selecting a proportional number of individuals from each stratum. Stratified sampling ensures that every group is adequately represented in the sample, and reduces the sampling error and variability12 Systematic sampling is not correct, because it involves selecting every nth individual from the population, starting from a random point. Systematic sampling does not guarantee that every state will have a similar proportion of data in the sample, and may introduce bias or error if there is a hidden pattern or order in the population12 Convenience sampling is not correct, because it involves selecting individuals who are easily accessible or available to the researcher. Convenience sampling is a type of non-probability sampling that does not involve random selection, and may result in a biased or unrepresentative sample12 Random sampling is not correct, because it involves selecting individuals from the population at random, without any grouping or stratification. Random sampling may not produce a sample that has a similar proportion of data from every state, especially if the population is large or heterogeneous. Random sampling may also have a higher sampling error and variability than stratified sampling12
質問 # 93
You are creating a dashboard that shows the total revenue for your organization broken out by a variety of factors. Which one of these is a measure, rather than a dimension?
- A. Department.
- B. Geographic region.
- C. Month.
- D. Revenue.
正解：D
質問 # 94
Given the following tables:
Which of the following will be the dimensions from a FULL JOIN of the tables above?
- A. Two rows and three columns
- B. Three rows and four columns
- C. Four rows and two columns
- D. Four rows and four columns
正解：D
質問 # 95
Jenny wants to study the academic performance of undergraduate sophomores and wants to determine the average grade point average at different points during an academic year.
What best describes the data set she needs?
- A. Variable.
- B. Population.
- C. Observation.
- D. Sample.
正解：D
解説：
Correct answer A. Sample.
Jenny does not have data for the entire population of all undergraduate sophomores. While a specific grade point average is an observation of variable, jenny needs sample data.
質問 # 96
Which of the following is an example of a discrete data type?
- A. 2.5mi (4km)
- B. 8in (20cm)
- C. 10.7lbs (4.9kg)
- D. 5 kids
正解：D
解説：
Explanation
A discrete data type is a data type that can only take on a finite number of values, such as integers or categories. An example of a discrete data type is the number of kids, as it can only be a whole number. The other options are examples of continuous data types, as they can take on any value within a range. The length in inches or centimeters, the distance in miles or kilometers, and the weight in pounds or kilograms are all continuous data types. Reference: CompTIA Data+ (DA0-001) Practice Certification Exams | Udemy
質問 # 97
A data analyst needs to create a weekly recurring report on sales performance and distribute it to all sales managers. Which of the following would be the BEST method to automate and ensure successful delivery for this task?
- A. Upload the report to the server.
- B. Print out a copy.
- C. Implement subscription access delivery.
- D. Use scheduled report delivery.
正解：D
質問 # 98
Refer to the exhibit.
Given the following data:
Which of the following BEST describes the data set?
- A. The data is inconsistent.
- B. There is data bias.
- C. The data is outliers.
- D. The data is incomplete.
正解：A
解説：
This is because inconsistency is a type of data quality issue that occurs when the data does not follow a common format, structure, or rule across different sources or systems, which can affect the efficiency and performance of the analysis or process. Inconsistency can be caused by having different spellings, punctuations, capitalizations, or abbreviations for the same or similar values in a data set, such as "M", "m", "Male", or "male" for gender in this case. Inconsistency can be eliminated or reduced by using data cleansing techniques, such as standardizing or normalizing the data values. The other options are not correct descriptions of the data set. Here is why:
Data bias is a type of data quality issue that occurs when the data is not representative or proportional of the population or the parameter, which can affect the validity and reliability of the analysis or process. Data bias can be caused by having a sample that is too small, too large, or too skewed for the population or the parameter, such as having only male customers for a product that targets both genders in this case. Data bias can be eliminated or reduced by using sampling techniques, such as stratified or cluster sampling.
The data is incomplete is a type of data quality issue that occurs when the data is absent or missing in a data set, which can affect the accuracy and reliability of the analysis or process. The data is incomplete can be caused by various factors, such as human error, system error, or non-response. The data is incomplete can be addressed by using various methods, such as replacing or imputing the missing values with some reasonable estimates, such as mean, median, mode, or regression.
The data is outliers is a type of data quality issue that occurs when the data has values that are unusually high or low compared to the rest of the data set, which can affect the quality and validity of the analysis or process. The data is outliers can be caused by various factors, such as measurement error, natural variation, or extreme events. The data is outliers can be addressed by using various methods, such as removing or filtering out the outliers, or using robust statistics that are less sensitive to outliers, such as median, interquartile range, or box plot.
質問 # 99
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. Web scraping
- B. ETL
- C. Sampling
- D. Data wrangling
正解：A
解説：
Explanation
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 # 100
Refer to the exhibit.
Given the diagram below:
Which of the following data schemas shown?
- A. Data Lake
- B. Key-value pairs
- C. Online transactional processing
- D. Relational database
正解：D
解説：
A relational database is a type of database that organizes data into tables, where each table has a fixed number of columns and a variable number of rows. Each row in a table represents a record or an entity, and each column represents an attribute or a property of that entity. The tables are linked by common fields, called keys, which enable the database to establish relationships between the data. A relational database schema is a diagram that shows the structure and organization of the tables, columns, keys, and constraints in a relational database. The diagram given in the question is an example of a relational database schema, as it shows two tables: "Runs" and "Experiments", with their respective columns, data types, and primary keys. The "Runs" table also has a foreign key that references the "ExperimentId" column in the "Experiments" table, indicating a relationship between the two tables. Therefore, the correct answer is D. Reference: What is a database schema? | IBM, Database Schema - Javatpoint
質問 # 101
Which of following is a non-relational database?
- A. PostgreSQL
- B. SQLite
- C. MySQL
- D. Neo4j
正解：D
解説：
Neo4j is a type of non-relational database that uses a graph model to store dat a. A graph database is a database that represents data as nodes and edges, where nodes are entities and edges are relationships between them. A graph database can store complex and diverse data that is not easily structured in tables. A graph database can also perform fast and efficient queries on the data by traversing the connections between the nodes
質問 # 102
A data analyst has been asked to derive a new variable labeled "Promotion_flag" based on the total quantity sold by each salesperson. Given the table below:
Which of the following functions would the analyst consider appropriate to flag "Yes" for every salesperson who has a number above 1,000,000 in the Quantity_sold column?
- A. Logical
- B. Date
- C. Aggregate
- D. Mathematical
正解：A
解説：
Explanation
A logical function is a type of function that returns a value based on a condition or a set of conditions. For example, the IF function in Excel can be used to check if a certain condition is met, and then return one value if true, and another value if false. In this case, the data analyst can use a logical function to check if the Quantity_sold column is greater than 1,000,000, and then return "Yes" if true, and "No" if false. This would create a new variable called Promotion_flag that indicates whether the salesperson has sold more than
1,000,000 units or not. References: CompTIA Data+ Certification Exam Objectives, Logical functions (reference)
質問 # 103
A data analyst is creating a report that will provide information about various regions, products, and time periods. Which of the following formats would be the MOST efficient way to deliver this report?
- A. A dashboard with filters at the top that the user can toggle
- B. A static report with a different page for every filtered view
- C. A daily email with snapshots of regional summaries
- D. A workbook with multiple tabs for each region
正解：A
質問 # 104
Afinancial institution is reporting on sales performance to a company at the account level. Due to the sensitive nature of the government the does il with, some account information is not shown. Which of the following fields should be masked?
- A. Sales volume
- B. Start date
- C. Customer name
- D. Product name
正解：C
質問 # 105
Which of the following data cleansing issues will be fixed when a DISTINCT function is applied?
- A. Missing data
- B. Redundant data
- C. Invalid data
- D. Duplicate data
正解：D
解説：
Explanation
This is because duplicate data refers to data that is repeated or copied in a data set, which can affect the quality and validity of the analysis. A DISTINCT function is a type of function that removes duplicate values from a column or a table, leaving only unique values. For example, a DISTINCT function in SQL that can achieve this is:
The other data cleansing issues will not be fixed by applying a DISTINCT function. Here is why:
Missing data refers to data that is absent or incomplete in a data set, which can affect the accuracy and reliability of the analysis. A DISTINCT function does not help with missing data, because it does not fill in or impute the missing values.
Redundant data refers to data that is unnecessary or irrelevant for the analysis, which can affect the efficiency and performance of the analysis. A DISTINCT function does not help with redundant data, because it does not remove or filter out the redundant values.
Invalid data refers to data that is incorrect or inaccurate in a data set, which can affect the validity and reliability of the analysis. A DISTINCT function does not help with invalid data, because it does not validate or correct the invalid values.
質問 # 106
Most data that exists in the world is structured data.
- A. False
- B. True
正解：A
質問 # 107
The process of performing initial investigations on data to spot outliers, discover patterns, and test assumptions with statistical insight and graphical visualization is called:
- A. an exploratory data analysis.
- B. a performance analysis.
- C. a link analysis.
- D. a t-test.
正解：A
解説：
This is because exploratory data analysis is a type of process that performs initial investigations on data to spot outliers, discover patterns, and test assumptions with statistical insight and graphical visualization, such as box plots, histograms, scatter plots, etc. Exploratory data analysis can be used to understand and summarize the data, as well as to generate hypotheses or questions for further analysis or research. For example, exploratory data analysis can be used to identify and visualize the characteristics, features, or behaviors of the data, as well as to measure their distribution, frequency, or correlation. The other options are not types of processes that perform initial investigations on data to spot outliers, discover patterns, and test assumptions with statistical insight and graphical visualization. Here is what they mean:
A t-test is a type of statistical method that tests whether there is a significant difference between the means of two groups or samples, such as whether there is a difference between the average exam scores of two classes in this case. A t-test can be used to test or verify a claim or an assumption about the data, as well as to measure the confidence or the error of the estimation.
A performance analysis is a type of process that measures whether the data meets certain goals or objectives, such as targets, benchmarks, or standards. A performance analysis can be used to identify and visualize the gaps, deviations, or variations in the data, as well as to measure the efficiency, effectiveness, or quality of the outcomes. For example, a performance analysis can be used to determine if there is a gap between a student's test score and their expected score based on their previous performance.
A link analysis is a type of process that determines whether the data is connected to other datapoints, such as entities, events, or relationships. A link analysis can be used to identify and visualize the patterns, networks, or associations among the datapoints, as well as to measure the strength, direction, or frequency of the connections. For example, a link analysis can be used to determine if there is a connection between a customer's purchase history and their loyalty program status.
質問 # 108
During data cleansing, an analyst conducts measures of central tendency on a data set. Which of the following data is the analyst attempting to identify?
- A. Outlying
- B. Invalid
- C. Duplicate
- D. Missing
正解：A
質問 # 109
......
CompTIA DA0-001認定試験は、献身と準備が必要な厳しいテストです。この試験は、90分以内に90個の多肢選択問題に回答する必要があります。合格するには、最低900点中720点以上を獲得する必要があります。この認定は3年間有効であり、継続教育を受けるか、再度試験を受けることで更新する必要があります。全体的に、CompTIA DA0-001認定試験は、データ管理の専門知識を持つプロフェッショナルが自分の能力を証明し、キャリアを進めるための優れた方法です。
有効な学習方法でCompTIAのDA0-001試験をパス：https://www.goshiken.com/CompTIA/DA0-001-mondaishu.html
無料テストエンジンCompTIA Data+ Certification Exam認定試験：https://drive.google.com/open?id=1SsPKG9ogtjINd7-QOknlbT2gg4mLBiGZ