DA0-002 Practice Exam 62 — 20 Questions

Question 1

Match each ETL process step to its description.

Accepted Answer

Extract: Retrieving data from various source systems. In ETL, Extract involves retrieving data from sources, Transform involves cleaning and converting data, and Load involves writing data to a target system. Common confusions include swapping the definitions of Extract and Transform, or misattributing real-time data capture to Load.

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Extract: Converting data into a suitable format for analysis

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Transform: Retrieving data from various source systems

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Load: Capturing changes from source systems in real time

Question 2

A data analyst needs to present the distribution of customer ages to a non-technical audience. Which type of chart would be most appropriate?

Accepted Answer

Histogram. A histogram is the most appropriate chart for displaying the distribution of a single continuous variable, such as customer ages, to a non-technical audience. It groups ages into bins and shows the frequency of customers within each bin, making the shape, center, and spread of the distribution immediately visible. This aligns with the DA0-001 objective of selecting visualizations that clearly communicate data insights to stakeholders.

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Scatter plot

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Pie chart

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Line chart

Question 3

A data analyst creates a report showing sales by product category. The analyst notices that one category has a very high sales figure due to a one-time bulk order. Which of the following is the best way to communicate this insight to stakeholders?

Accepted Answer

Add a note to the chart explaining the bulk order.. It maintains data integrity while providing necessary context. Adding a note to the chart allows stakeholders to understand the anomaly without distorting the underlying data. This approach aligns with best practices in data communication, where transparency about outliers is critical for accurate interpretation.

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Delete the bulk order from the dataset.

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Remove the category with the bulk order from the report.

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Use a pie chart to show the proportion of each category.

Question 4

Which TWO of the following are valid SQL clauses used to filter and sort data?

Accepted Answer

WHERE. The WHERE clause is used to filter rows based on specified conditions, while the ORDER BY clause sorts the result set in ascending or descending order. Both are standard SQL clauses for data filtering and sorting, respectively.

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DELETE

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UPDATE

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INSERT

Question 5

Which THREE factors should be considered when choosing a chart type for a dataset?

Accepted Answer

The data types (categorical, numerical, time series). The data type (categorical, numerical, time series) determines which chart types are semantically valid. For example, a line chart requires a continuous numerical or time-series axis, while a bar chart works with categorical data. Choosing a chart that mismatches the data type can misrepresent the underlying distribution or trends.

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The animation capabilities of the software

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The color scheme of the company logo

Question 6

Refer to the exhibit. The data shows sales by product category for two years. Which product category had the highest percentage increase from 2023 to 2024?

Accepted Answer

Home & Garden. Home & Garden had the highest percentage increase from 2023 to 2024. Based on the data, its sales grew from $19,000 to $22,000, a 15.8% increase. In contrast, Clothing increased by 10% ($100,000 to $110,000), Books by 8% ($25,000 to $27,000), and Electronics by 12% ($30,000 to $33,600). Therefore, Home & Garden's percentage increase of 15.8% is the highest among all categories.

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Clothing

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Books

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Electronics

Question 7

A data scientist is working with a dataset containing 1000 features and 500 samples. The goal is to build a predictive model. Which technique should be used to reduce the number of features while retaining most of the variance?

Accepted Answer

Principal Component Analysis (PCA). Principal Component Analysis (PCA) is an unsupervised dimensionality reduction technique that transforms the original features into a set of orthogonal components, ordered by the variance they capture. Given 1000 features and only 500 samples, PCA is ideal because it reduces the feature space while retaining the maximum variance, helping to avoid overfitting and the curse of dimensionality.

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Ridge regression

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Forward selection

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Lasso regression

Question 8

A company must comply with GDPR when reporting customer data. What must be included in the report?

Accepted Answer

A notice about data processing purposes. Under GDPR, when reporting customer data, the controller must provide a notice about the purposes of data processing to ensure transparency and lawful basis for processing. This is required by Article 13 of the GDPR, which mandates that data subjects be informed of the specific purposes for which their personal data is being processed. Including this notice in the report demonstrates compliance with the accountability principle.

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Customer names and emails

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The source of the data

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Data retention period

Question 9

A data analyst is reviewing the quality of a sales report before publishing. Which THREE elements should the analyst include to ensure report quality?

Accepted Answer

Data freshness timestamp. Report quality includes documenting when data was last updated, any limitations or assumptions, and the source of the data to ensure transparency and reliability.

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Row-level security settings

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Methodology notes

Question 10

A dataset contains a column 'Education Level' with values: 'High School', 'Bachelor', 'Master', 'PhD'. An analyst computes the average by assigning numbers 1-4. Which data concept is being violated?

Accepted Answer

Treating ordinal data as interval. The analyst assigned numeric values (1-4) to 'Education Level' categories and computed an average. This treats the ordinal data as if it were interval data, assuming equal spacing between categories (e.g., the difference between 'High School' and 'Bachelor' is the same as between 'Master' and 'PhD'), which is not valid. Ordinal data only preserves order, not magnitude or equal intervals, so calculating a mean is inappropriate.

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Misclassifying data as structured

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Treating nominal data as ordinal

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Treating ratio data as interval

Question 11

A data analyst is presenting a weekly sales report to a diverse audience that includes sales managers, marketing team, and finance. The analyst wants to ensure the data is understood correctly. Which communication strategy is most effective?

Accepted Answer

Create a slide deck with key insights and contextual explanations.. A slide deck with key insights and contextual explanations tailors the presentation to a diverse audience, ensuring that sales managers, marketing, and finance can each grasp the relevant data without being overwhelmed. This approach aligns with best practices for data communication, where visual summaries and narrative context improve comprehension over raw data or overly technical jargon.

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Use a single complex chart to show all data at once.

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Email the raw data table to all stakeholders.

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Use technical terms such as 'variance' and 'standard deviation'.

Question 12

A marketing team wants to compare the growth rates of four product categories over the last quarter. Which chart type would best display this?

Accepted Answer

Bar chart. A bar chart is ideal for comparing discrete values across categories, such as the growth rates of four product categories. It allows for easy visual comparison of the heights of the bars. Option A (pie chart) is unsuitable for comparing growth rates as it shows proportions of a whole, not rates. Option B (stacked bar chart) would show cumulative totals, not individual growth rates. Option C (line chart) is better for trends over time, not for comparing discrete categories.

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Pie chart

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Stacked bar chart

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Line chart

Question 13

Which TWO of the following are characteristics of OLTP systems? (Select 2)

Accepted Answer

Designed for high transaction throughput. OLTP systems are designed for high transaction throughput, handling large volumes of short, atomic transactions efficiently. They prioritize fast data processing and immediate consistency, making option D correct.

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Typically uses a denormalized schema

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Optimized for complex analytical queries

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Stores historical data for trend analysis

Question 14

A data engineer needs to extract data from a REST API and load it into a data warehouse. The data is received in JSON format. Which data type best describes JSON?

Accepted Answer

Semi-structured. JSON (JavaScript Object Notation) is classified as a semi-structured data type because it uses a flexible, self-describing schema with key-value pairs and nested structures, but does not enforce a rigid tabular schema like relational databases. In the context of extracting data from a REST API, JSON allows for varying fields and hierarchical data, which aligns with the semi-structured category.

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Transactional

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Unstructured

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Structured

Question 15

A data analyst is troubleshooting a dashboard that displays slowly. Which two of the following are common causes of dashboard performance issues? (Select TWO.)

Accepted Answer

Large unaggregated datasets.. Large unaggregated datasets force the dashboard to process every row of raw data at query time, which dramatically increases load times and memory consumption. Aggregated or pre-summarized tables reduce the volume of data scanned, improving performance.

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Minimal use of filters.

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Use of summary tables.

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Excessive use of live data connections.

Question 16

Which THREE of the following are valid data quality dimensions? (Choose THREE.)

Accepted Answer

Completeness. Completeness is a core data quality dimension that measures whether all required data is present. In the context of the DA0-001 exam, completeness ensures that no fields or records are missing, which is fundamental for reliable analysis and reporting.

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Encryption

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Redundancy

Question 17

A data engineer is tasked with acquiring data from a third-party vendor that provides daily file drops via SFTP. The files are large (10 GB each). The pipeline must load data into a data warehouse. Which approach optimizes for speed and reliability?

Accepted Answer

Stream the file directly from SFTP into warehouse using a data pipeline tool. Streaming the file directly from SFTP into the warehouse using a data pipeline tool (e.g., Apache NiFi, Airbyte, or Fivetran) eliminates the intermediate staging step, reducing disk I/O and latency. This approach leverages incremental processing and parallel streams to handle large 10 GB files efficiently, while built-in retry and checkpoint mechanisms ensure reliability against network interruptions.

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Download the file to a staging server, then bulk insert into warehouse

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Have the vendor push data via API instead of SFTP

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Split the file into smaller chunks and load concurrently

Question 18

Refer to the exhibit. A data analyst is reviewing a data quality report. Which of the following actions should the analyst take first?

Accepted Answer

Investigate the source system to understand why emails are missing.. The first step in data quality remediation is root cause analysis. Without understanding why 1200 records have null emails (e.g., a source system bug, a failed ETL join, or a missing required field), any corrective action like deletion or placeholder insertion risks introducing bias or masking a systemic issue. Investigating the source system aligns with the data governance principle of 'fix the source, not the symptom.'

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Delete the 1200 records with null emails.

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Fill null emails with a placeholder.

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Ignore the nulls as they are not critical.

Question 19

A data analyst is tasked with collecting data from multiple spreadsheets provided by different departments. Each spreadsheet has different column names and formats. What is the best first step?

Accepted Answer

Develop a data dictionary and standardize column names. Developing a data dictionary and standardizing column names ensures consistency across all data sources before loading, reducing errors and facilitating integration. Immediately loading data can cause inconsistencies. Discarding mismatched data loses potentially valuable information. Using a machine learning model is an unnecessary and complex first step.

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Discard any mismatched data

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Use a machine learning model to clean data

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Immediately load all data into a database

Question 20

A data analyst needs to visualize the distribution of a continuous variable across different categories. Which chart type is most suitable?

Accepted Answer

Box plot. A box plot (option D) is the most suitable chart for visualizing the distribution of a continuous variable across different categories because it displays the median, quartiles, and potential outliers for each group, enabling direct comparison of spread and central tendency. Unlike a histogram, which shows the distribution of a single continuous variable without categorical grouping, the box plot inherently supports categorical axes. This makes it ideal for exploratory data analysis when assessing how a metric like revenue varies by region or product category.

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Bar chart

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Histogram

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Scatter plot