[2026年01月09日]DA0-001日本語認定ガイド問題と解答トレーニング
DA0-001日本語認定お試しセット最新DA0-001日本語のPDF問題集
質問 # 176
サイト信頼性チームは、Web サイトの安定性を監視したいと考えています。問題が発生したときにプロアクティブに診断できるようにする 次の成果物のうち、ニーズに最も適しているものはどれですか?
- A. 毎日更新され、タイプ別に分類されたエラーを報告するポータル
- B. 前日の Web サイトの停止を示す毎日の概要メール
- C. リアルタイムで更新される Web サイトのパフォーマンスのセルフサービス ダッシュボード
- D. サイト訪問とユーザーアクションの週次ログレポート
正解：C
解説：
The best deliverable that would suit the site reliability team's needs is A) A self-serve dashboard of website performance that updates in real time.
A self-serve dashboard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance. A self-serve dashboard of website performance that updates in real time would allow the site reliability team to easily and quickly access the information they need about the stability of their website, such as uptime, response time, error rate, traffic volume, etc. A self-serve dashboard would also enable the team to proactively diagnose issues when they occur, by providing alerts, notifications, or drill-down options. A self-serve dashboard would also be more interactive and engaging than a report or an email.
A weekly log report of site visits and user actions would not be a good deliverable for the site reliability team's needs, because it would not provide timely or relevant information about the stability of their website. A weekly log report would be too infrequent and delayed to monitor and diagnose issues when they occur. A weekly log report would also focus on the behavior and actions of the users, rather than the performance and functionality of the website.
A portal that is refreshed daily and reports errors classified by type would not be a good deliverable for the site reliability team's needs, because it would not provide real-time or comprehensive information about the stability of their website. A portal that is refreshed daily would be too slow and outdated to monitor and diagnose issues when they occur. A portal that reports errors classified by type would be too narrow and limited to capture the full picture of the website performance.
A daily summary email indicating website outages for the previous day would not be a good deliverable for the site reliability team's needs, because it would not provide real-time or actionable information about the stability of their website. A daily summary email would be too late and retrospective to monitor and diagnose issues when they occur. A daily summary email indicating website outages would also be too passive and generic to help the team resolve or prevent issues in the future.
質問 # 177
ジェニーは、学部 2 年生の学業成績を調査し、1 学年のさまざまな時点での成績平均点を求めたいと考えています。
彼女が必要とするデータセットを最もよく表しているのはどれですか?
- A. 観察。
- B. 変数。
- C. サンプル。
- D. 人口。
正解：C
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 # 178
次のうち、標準偏差を最もよく表しているのはどれですか?
- A. データの分散方法の尺度
- B. 一連の値の分散量の尺度
- C. 2 つの変数間の関係を確立するために使用される尺度
- D. 変数間の有意差を見つけるために使用される尺度
正解：B
解説：
Explanation
A measure of the amount of dispersion of a set of values. This is because standard deviation is a type of statistical measure that quantifies how much the values in a data set vary or deviate from the mean or the average of the data set. Standard deviation can be used to describe the spread or the distribution of the data, as well as to identify any outliers or extreme values in the data. For example, a low standard deviation indicates that the values are close to the mean, while a high standard deviation indicates that the values are far from the mean. The other options are not correct descriptions of standard deviation. Here is why:
A measure that is used to establish a relationship between two variables is not a correct description of standard deviation, but rather a description of correlation or regression, which are types of statistical measures that quantify how two variables are related or associated with each other. Correlation or regression can be used to test or model the dependence or the influence of one variable on another variable, as well as to predict or estimate the value of one variable based on the value of another variable.
A measure of how data is distributed is not a correct description of standard deviation, but rather a description of frequency or probability, which are types of statistical measures that quantify how often or how likely a value or an event occurs in a data set. Frequency or probability can be used to describe the occurrence or the chance of the data, as well as to compare or contrast different categories or groups of the data.
A measure that is used to find the significant difference between variables is not a correct description of standard deviation, but rather a description of hypothesis testing or inferential statistics, which are types of statistical methods that use sample data to make generalizations or conclusions about a population or a parameter. Hypothesis testing or inferential statistics 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.
質問 # 179
以下の画像を考えてみます。
次のファイル形式のうちどれが表示されますか?
- A. JSON
- B. HTML
- C. XML
- D. CSV
正解：A
解説：
The image depicts a snippet of code in the JSON format, which stands for JavaScript Object Notation. JSON is a lightweight data-interchange format that is easy for humans to read and write and easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language and is commonly used to transmit data in web applications.
* CSV, or Comma-Separated Values, is a simple file format used to store tabular data, such as a spreadsheet or database. It uses commas to separate values.
* XML, or eXtensible Markup Language, is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable.
* HTML, or HyperText Markup Language, is the standard markup language for documents designed to be displayed in a web browser.
References:
JSON.org - Introducing JSON1
W3Schools - JSON Introduction2
Mozilla Developer Network - JSON3
質問 # 180
次のどれがスター スキーマの特徴ですか?
- A. 表形式の構造になっています。
- B. 非構造化データを格納します。
- C. 非正規化されたディメンション テーブルがあります。
- D. トランザクションデータを保存します。
正解：C
解説：
In data warehousing, a star schema consists of:
* A central fact table (containing measures such as sales, quantities, amounts)
* Multiple surrounding dimension tables (such as date, product, customer, location) A core characteristic of a star schema is that the dimension tables are denormalized:
* Each dimension table is usually wide and contains descriptive attributes in a single table (rather than being broken into multiple normalized tables).
* This design simplifies queries and improves performance for analytical workloads.
Why the other options are incorrect:
* A. It has a tabular structure.All relational schemas (OLTP and OLAP) are tabular; this is not unique to star schemas.
* B. It stores transactional data.Transactional data is typically stored in normalized OLTP relational databases, not in star schemas (which are optimized for analytics).
* C. It stores unstructured data.Star schema is a structured relational design, not used for unstructured data (e.g., text blobs, images).
Therefore, the defining characteristic listed in the options is: It has denormalized dimension tables (D).
CompTIA Data+ Reference (concept alignment):
* DA0-001 Exam Objectives - Data concepts and environments: schema design (star vs snowflake).
* Common data warehousing references describe star schema as: fact table + denormalized dimension tables optimized for analytics.
質問 # 181
新しいツールを入手することを意味する場合でも、特定の状況に最も適した分析ツールを常に選択する必要があります。
- A. いいえ。
- B. そうです。
正解：A
質問 # 182
キーまたはパスワードを持っているユーザーのみがデータを読み取れるように、データを別の形式に変換するために使用できるのは次のうちどれですか?
- A. データマスキング。
- B. データ送信。
- C. データの暗号化。
- D. データ保護。
正解：C
解説：
Data encryption can be used to translate data into another form so it can only be read by a user who has a key or a password. Data encryption is a process of transforming data using an algorithm or a cipher to make it unreadable to anyone except those who have the key or the password to decrypt it. Data encryption is a common method of protecting data from unauthorized access, modification, or theft. Reference: Guide to CompTIA Data+ and Practice Questions - Pass Your Cert
質問 # 183
アナリストは、過去 5 年間の履歴データ セットを各年ごとに作成したいと考えています。この履歴データ セットを作成するのに最適な方法は、次のどれですか。
- A. データの連結
- B. データの転置
- C. データ追加
- D. データの正規化
正解：A
質問 # 184
金融サービス会社の顧客リストを以下に示します。
データ アナリストは、クレジットカードの数、年齢、収入という 3 つの数値変数の平均に基づいて、0 から 100 までのスケールで購入可能性スコアを作成したいと考えています。スコア計算ですべての変数に同じ重みを持たせるために、アナリストは次のどれを変数に対して行う必要がありますか。
- A. 変数を正規化します。
- B. 変数のパーセンタイルを計算します。
- C. 変数の標準偏差を計算します。
- D. 変数を再コード化します。
正解：A
解説：
Normalizing the variables means scaling them to a common range, such as 0 to 1 or -1 to 1, so that they have the same weight in the score calculation. Recoding the variables means changing their values or categories, which would alter their meaning and distribution. Calculating the percentiles of the variables means ranking them relative to each other, which would not account for their actual magnitudes. Calculating the standard deviations of the variables means measuring their variability, which would not make them comparable.
References: CompTIA Data+ Certification Exam Objectives, page 10
質問 # 185
XXX-XXX-XXXX としてフォーマットされた電話番号が考慮されるデータ型は、次のうちどれですか?
- A. 数値
- B. 日付
- C. フロート
- D. テキスト
正解：D
質問 # 186
タブ区切りの spre ファイルとして正しいのはどれですか?
- A. tap
- B. az
- C. tar
- D. sv
正解：D
解説：
A tab-delimited spreadsheet file is a type of flat text file that uses tabs as delimiters to separate data values in a table. The file extension for a tab-delimited spreadsheet file is usually .tsv, which stands for tab-separated values. Therefore, the correct answer is C. References: [Tab-separated values - Wikipedia], [What is a TSV File? | How to Open, Edit & Convert TSV Files]
質問 # 187
以下の表を考慮すると、次のようになります。
次の変数のうち、一貫性がないと考えられるのはどれですか?また、その変数には個別の値がいくつ必要ですか?
- A. 性別、2
- B. 名前、1 つ
- C. レベル、3
- D. リージョン、5
- E. コード、4
正解：A
質問 # 188
大数の法則を最もよく表しているのは次のうちどれですか?
- A. サンプルサイズが 2 倍になる場合。サンプルは母集団全体を示しています。
- B. サンプルサイズが小さくなるにつれて、標準偏差は母集団全体の平均に近づきます。
- C. サンプルサイズが減少するにつれて、その平均は母集団全体の平均に近づきます。
- D. サンプルサイズが大きくなるにつれて、平均値は母集団全体の平均値に近づきます。
正解：D
解説：
The best answer is B. As a sample size grows, its mean gets closer to the average of the whole population.
The law of large numbers, in probability and statistics, states that as a sample size grows, its mean gets closer to the average of the whole population. This is due to the sample being more representative of the population as it increases in size. The law of large numbers guarantees stable long-term results for the averages of some random events1 A: As a sample size decreases, its standard deviation gets closer to the average of the whole population is not correct, because it confuses the concepts of standard deviation and mean. Standard deviation is a measure of how much the values in a data set vary from the mean, not how close the mean is to the population average.
Also, as a sample size decreases, its standard deviation tends to increase, not decrease, because the sample becomes less representative of the population.
C: As a sample size decreases, its mean gets closer to the average of the whole population is not correct, because it contradicts the law of large numbers. As a sample size decreases, its mean tends to deviate from the average of the whole population, because the sample becomes less representative of the population.
D: When a sample size doubles, the sample is indicative of the whole population is not correct, because it does not specify how close the sample mean is to the population average. Doubling the sample size does not necessarily make the sample indicative of the whole population, unless the sample size is large enough to begin with. The law of large numbers does not state a specific number or proportion of samples that are indicative of the whole population, but rather describes how the sample mean approaches the population average as the sample size increases indefinitely.
質問 # 189
40 フィールドを含むデータ セットを 20 フィールドに削減する必要があり、複数のフィールドにわたる同様のデータが含まれている場合、次の概念のうちどれを適用する必要がありますか?
- A. 統合
- B. 重複
- C. 標準化
- D. コンプライアンス
正解：A
解説：
Consolidation is the process of combining multiple elements into a single, more effective or coherent whole. In the context of data analytics, consolidation would involve merging similar fields to reduce the overall number of fields in a dataset. This is particularly useful when a dataset contains redundant or similar data across multiple fields, as it helps to simplify the data structure and improve efficiency. Techniques such as dimensionality reduction are often applied to achieve this, where the goal is to retain the most informative and representative features of the data while reducing the number of total features.
Reference:
Applied Dimensionality Reduction - 3 Techniques using Python1.
Seven Techniques for Data Dimensionality Reduction2.
Best practices when working with datasets3.
Effectively Handling Large Datasets4.
質問 # 190
電力会社の運用責任者は、州全体の停電と電力復旧の活動を監視するために、会社のリソースをどこに割り当てるべきかを特定するのに役立つデータを必要としています。具体的には、ディレクターは次のことを確認したいと考えています。
*郡の停電
* 状態
* 停止の全体的な傾向
説明書：
ダッシュボード上の適切なスペースに合わせて各ビジュアライゼーションを選択し、適切な配色を選択してください。すべてのビジュアライゼーションを選択したら、該当する場合は適切なタイトルとラベルを選択してください。
タイトルとラベルは複数回使用できます。
シミュレーションの初期状態に戻したい場合は、[すべてリセット] ボタンをクリックしてください。
正解：
解説：
Power outages
Explanation:
This is a simulation question that requires you to create a dashboard with visualizations that meet the director' s needs. Here are the steps to complete the task:
* Drag and drop the visualization that shows the county outages on the top left space of the dashboard.
This visualization is a map of the state with different colors indicating the number of outages in each county. You can choose any color scheme that suits your preference, but make sure that the colors are consistent and clear. For example, you can use a gradient of red to show the counties with more outages and green to show the counties with less outages.
* Drag and drop the visualization that shows the status of the outages on the top right space of the dashboard. This visualization is a pie chart that shows the percentage of outages that are active, restored, or pending. You can choose any color scheme that suits your preference, but make sure that the colors are distinct and easy to identify. For example, you can use red for active, green for restored, and yellow for pending.
* Drag and drop the visualization that shows the overall trend of outages on the bottom space of the dashboard. This visualization is a line graph that shows the number of outages over time. You can choose any color scheme that suits your preference, but make sure that the color is visible and contrasted with the background. For example, you can use blue for the line and white for the background.
* Select appropriate titles and labels for each visualization. Titles and labels may be used more than once.
For example, you can use "County Outages" as the title for the map, "Status" as the title for the pie chart, and "Trend" as the title for the line graph. You can also use "County", "Number of Outages",
"Active", "Restored", "Pending", "Time", and "Number of Outages" as labels for the axes and legends of the visualizations.
質問 # 191
調査データを確認しているときに、アナリストは、回答者が 1 月の回答として「1 月」、「1 月」、および「01」を入力したことに気付きました。データの整合性を確保するために取るべき手順は次のうちどれですか?
- A. "January" と表示されていない回答をフィルター処理し、"January" に更新します。
- B. 「1月」が書かれていない回答を削除してください。
- C. "Jan" という回答を並べ替え、"01" に更新します。
- D. "01" を持つ応答を置き換えます。
正解：A
解説：
Filter on any of the responses that do not say "January" and update them to "January". This is because filtering and updating are data cleansing techniques that can be used to ensure data consistency, which means that the data is uniform and follows a standard format. By filtering on any of the responses that do not say "January" and updating them to "January", the analyst can make sure that all the responses for the month of January are written in the same way. The other steps are not appropriate for ensuring data consistency. Here is why:
Deleting any of the responses that do not have "January" written out would result in data loss, which means that some information would be missing from the data set. This could affect the accuracy and reliability of the analysis.
Replacing any of the responses that have "01" would not solve the problem of data inconsistency, because there would still be two different ways of writing the month of January: "Jan" and "January". This could cause confusion and errors in the analysis.
Sorting any of the responses that say "Jan" and updating them to "01" would also not solve the problem of data inconsistency, because there would still be two different ways of writing the month of January: "01" and "January". This could also cause confusion and errors in the analysis.
質問 # 192
金融サービス会社の顧客リストを以下に示します。
データ アナリストは、クレジットカードの数、年齢、収入という 3 つの数値変数の平均に基づいて、0 から 100 までのスケールで購入可能性スコアを作成したいと考えています。スコア計算ですべての変数に同じ重みを持たせるために、アナリストは次のどれを変数に対して行う必要がありますか。
- A. 変数を正規化します。
- B. 変数のパーセンタイルを計算します。
- C. 変数の標準偏差を計算します。
- D. 変数を再コード化します。
正解：A
解説：
Normalizing the variables means scaling them to a common range, such as 0 to 1 or -1 to 1, so that they have the same weight in the score calculation. Recoding the variables means changing their values or categories, which would alter their meaning and distribution. Calculating the percentiles of the variables means ranking them relative to each other, which would not account for their actual magnitudes. Calculating the standard deviations of the variables means measuring their variability, which would not make them comparable.
References: CompTIA Data+ Certification Exam Objectives, page 10
質問 # 193
次のうち、データの要素が母集団内の小さなサブグループのそれぞれからランダムに選択されるサンプリング方法を説明しているのはどれですか?
- A. クラスター
- B. 単純ランダム
- C. システマティック
- D. 層別
正解：D
解説：
This is because stratified is a type of sampling in which elements of data are selected randomly from each of the small subgroups within a population, such as age groups, gender groups, or income groups. Stratified sampling can be used to ensure that the sample is representative and proportional of the population, as well as reduce the sampling error or bias. For example, stratified sampling can be used to select a sample of voters from different political parties based on their proportion in the population. The other types of sampling are not the types of sampling in which elements of data are selected randomly from each of the small subgroups within a population. Here is why:
* Simple random is a type of sampling in which elements of data are selected randomly from the entire population, without dividing it into any subgroups. Simple random sampling can be used to ensure that every element in the population has an equal chance of being selected, as well as avoid any systematic error or bias. For example, simple random sampling can be used to select a sample of students from a school by using a lottery or a computer-generated number.
* Cluster is a type of sampling in which elements of data are selected randomly from a few large subgroups within a population, such as regions, districts, or schools. Cluster sampling can be used to reduce the cost and complexity of sampling, as well as increase the feasibility and convenience of sampling. For example, cluster sampling can be used to select a sample of households from a few neighborhoods by using a map or a list.
* Systematic is a type of sampling in which elements of data are selected at regular intervals from an ordered list or sequence within a population, such as every nth element or every kth element.
Systematic sampling can be used to simplify and speed up the sampling process, as well as ensure that the sample covers the entire range or scope of the population. For example, systematic sampling can be used to select a sample of books from a library by using an alphabetical order or a numerical order.
質問 # 194
品質保証マネージャーがIoTセンサーの許容誤差を検査しています。マネージャーが計算するのに最適な指標は次のうちどれですか？
- A. 平均
- B. 四分位範囲
- C. 中央値
- D. 標準偏差
正解：D
解説：
When examining tolerances or variation in sensor readings, the key concept is how much measurements deviate from the average. The standard CompTIA approach:
* Standard deviation measures the spread of data around the mean.
* A small standard deviation # readings are tightly clustered (low variation).
* A large standard deviation # readings vary widely (high variation), indicating potential issues with sensor consistency.
Why the other options are less appropriate:
* Median (C) and Mean (D) are measures of central tendency, not dispersion; they tell you about the center, not how tightly values cluster around it.
* Quartile range (B) (or interquartile range) is also a dispersion measure, but standard deviation is the classic choice when dealing with continuous measurements and tolerances in engineering/QA contexts.
Thus, to evaluate the tolerances in IoT sensor readings, Standard deviation (A) is the best measure.
CompTIA Data+ Reference (concept alignment):
* DA0-001 Exam Objectives - Data analysis: measures of central tendency and dispersion (standard deviation, variance, range, IQR).
* CompTIA Data+ Study content: standard deviation is emphasized as a primary measure of spread for continuous data.
質問 # 195
以下の顧客テーブルがあるとします。
次のグラフの種類のうち、アクティブな顧客と非アクティブな顧客の平均支出を表すのに最も適切なのはどれですか?
- A. 散布図
- B. 円グラフ
- C. ヒートグラフ
- D. 折れ線グラフ
正解：B
解説：
A Pie chart is the most suitable for representing the average spending of active customers versus inactive customers. Pie charts are effective for comparing parts of a whole, which makes them ideal for visually displaying the proportion of spend between two distinct groups. They are widely used to depict percentage distributions and are straightforward, allowing immediate analysis of the active vs. inactive customer spending distribution at a glance.
質問 # 196
アナリストは、個人の年齢と投票嗜好の間に関係があるかどうかを判断したいと考えています。アナリストが使用する統計手法として最適なのは次のうちどれですか。
- A. Chi-squared
- B. F-test
- C. Z-score
- D. P-value
正解：A
解説：
The Chi-squared test is used to analyze relationships between two categorical variables. In this case, age groups and voting preferences are both categorical variables, making chi-squared the most appropriate test.
質問 # 197
組織がデータ主体の意向を尊重することを保証することに焦点を当てているデータ管理作業のどのカテゴリーですか?
- A. データ品質。
- B. データプライバシー。
- C. 規制遵守。
- D. データのセキュリティ。
正解：B
質問 # 198
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ベストCompTIA DA0-001日本語学習ガイドと問題集は2026：https://jp.fast2test.com/DA0-001J-premium-file.html