DA0-002 Practice Test 34 — 15 Questions

Question 1

Which TWO of the following data quality dimensions are most directly affected by duplicate records?

Accepted Answer

Uniqueness. Duplicate records most directly undermine Uniqueness (C), because uniqueness is the data quality dimension that measures whether each real-world entity appears exactly once in a dataset; duplicates violate this one-record-per-entity rule by definition. They also directly affect Accuracy (D), since duplicated rows distort counts, aggregations, and the true representation of the entity, making the stored data an incorrect reflection of reality. Timeliness (A) concerns whether data is current and available when needed, which duplicates do not inherently affect. Consistency (B) refers to agreement of the same data across systems or formats, which is a separate issue from repeated rows. Completeness (E) measures whether required data is present, and duplicates add data rather than omit it, so it is not the dimension most directly impacted.

Answer

Timeliness

Answer

Consistency

Answer

Completeness

Question 2

A data analyst is preparing a report to present to a mixed audience of technical and non-technical stakeholders. Which THREE techniques should the analyst use to ensure effective communication? (Choose three.)

Accepted Answer

Tailor the narrative to address different concerns. Option A is correct because tailoring the narrative to address different concerns lets the analyst speak to both technical and non-technical stakeholders in terms they care about, keeping the presentation relevant and engaging for everyone. Option D is correct because providing high-level summaries gives non-technical audience members an accessible overview of the key findings without requiring them to parse technical details. Option E is correct because including detailed technical appendices satisfies the technical stakeholders who want deeper evidence and methodology, without cluttering the main presentation for others. Option B does not belong because using only one chart type for consistency can obscure data that is better represented by a different visualization, reducing clarity. Option C does not belong because using technical jargon to demonstrate expertise alienates non-technical stakeholders and undermines effective communication rather than supporting it.

Answer

Use only one chart type for consistency

Answer

Use technical jargon to demonstrate expertise

Question 3

Which THREE are considered best practices in dashboard design? (Select three.)

Accepted Answer

Using heat maps to visualize correlation. Option A is correct because heat maps encode values through color intensity across a matrix, making correlation and density patterns between two dimensions immediately visible without requiring users to read individual numbers. Option C is correct because maximizing the data-ink ratio, a principle from Edward Tufte, means removing non-data decoration so that most pixels convey actual information, which improves clarity and reduces cognitive load. Option D is correct because interactive filters let users drill into relevant subsets and explore the data themselves, turning a static report into an analytical tool that answers multiple questions. Option B is not a best practice because 3D charts distort proportions and depth perception, making values harder to compare accurately than their 2D equivalents. Option E is not a best practice because cramming every data point into a dashboard creates clutter and obscures the key signals, whereas dashboards should surface aggregated or prioritized metrics.

Answer

Using 3D charts to add depth

Answer

Including every data point in the dashboard

Question 4

A data analyst is using Tableau to build a dashboard. Which THREE features are available in Tableau for creating interactive dashboards?

Accepted Answer

Dashboard actions. Dashboard actions (A) are a Tableau feature that lets a dashboard respond to user interaction—such as filter, highlight, URL, or go-to-sheet actions—making the dashboard interactive. Calculated fields (B) are Tableau expressions (using functions like IF, SUM, and LOD expressions) that create new derived data, and they can be exposed as interactive controls through parameters or actions. Parameters (D) are Tableau's user-controlled input values (for example, a slider or dropdown) that can drive calculated fields, filters, and reference lines, directly enabling interactivity. DAX measures (C) belong to Microsoft Power BI, not Tableau, and Power Query (E) is a Power BI/Excel data-transformation tool, so neither is available in Tableau for building dashboards.

Answer

DAX measures

Answer

Power Query

Question 5

During data acquisition, an analyst notices that the data from an external vendor has inconsistent date formats. What is the first step the analyst should take?

Accepted Answer

Perform data profiling. Before transforming or rejecting data, the analyst must first understand its shape, quality, and anomalies — that is data profiling. Profiling reveals the extent and pattern of the inconsistent date formats, how many records are affected, and whether other issues exist, which then informs the correct remediation approach. Jumping straight to transformation without profiling risks applying the wrong parsing rules.

Answer

Contact the vendor to request corrected data

Answer

Immediately transform dates to a standard format

Answer

Reject the entire dataset

Question 6

A data analyst needs to retrieve current weather data from a third-party service. The service provides an endpoint that returns data in JSON format over HTTP. Which data source type is being used?

Accepted Answer

API. The data analyst is retrieving data from a third-party service via an HTTP endpoint that returns JSON. This is the classic definition of an API (Application Programming Interface) — specifically a RESTful web API — which allows programmatic access to structured data over HTTP using standard methods like GET. The JSON format confirms it is an API response, not a file or stream.

Answer

Streaming data

Answer

Flat file

Answer

Web scraping

Question 7

When creating a data story, what should be the FIRST step?

Accepted Answer

Identify the key message. The first step in creating a data story is to identify the key message because the entire narrative, data selection, and visualization choices must align with a central insight. Without a clear message, subsequent steps like gathering data or designing layouts risk being unfocused and failing to communicate actionable findings. This ensures the story is driven by the insight, not by the data or tools.

Answer

Design the layout of the report

Answer

Gather all available data

Answer

Choose visualization tools

Question 8

Which THREE elements should be included in a data insight report to ensure it is actionable? (Choose three.)

Accepted Answer

The level of confidence or statistical significance.. An actionable data insight report must include the level of confidence or statistical significance to allow decision-makers to assess the reliability of the findings. Without this, stakeholders cannot determine whether the observed patterns are likely to be real or due to random chance, which is critical for making data-driven decisions.

Answer

The source code of the analysis scripts.

Answer

All raw data used in the analysis.

Question 9

Match each data security concept to its description.

Accepted Answer

Encryption: Process of converting data into a coded form to prevent unauthorized access.. The correct matches are: Encryption - encoding data, Authentication - verifying identity, Authorization - access control, Non-repudiation - denying actions. Common confusions arise from swapping Encryption and Authentication.

Answer

Encryption: Process of verifying identity.

Answer

Authentication: Process of converting data into code.

Question 10

While reviewing a dashboard, an analyst notices that the data in a trend line chart does not match the underlying data due to a filter setting. The dashboard is used for weekly executive meetings. What should the analyst do?

Accepted Answer

Document the issue and fix the filter before the next meeting.. The analyst has identified a data integrity issue caused by a filter setting that directly impacts the accuracy of the trend line chart. The dashboard is used for weekly executive meetings, so the analyst must document the discrepancy and correct the filter before the next meeting to ensure data-driven decisions are based on accurate visualizations. This aligns with best practices in data governance and the principle of maintaining trust in reporting tools.

Answer

Ignore the discrepancy if it is small.

Answer

Wait for someone to complain before acting.

Answer

Immediately remove the dashboard and send raw data.

Question 11

A data analyst needs to extract data from a transactional database and load it into a data warehouse for reporting. Which process typically transforms the data before loading it into the warehouse?

Accepted Answer

ETL. ETL (Extract, Transform, Load) transforms data in a staging area before loading it into the target warehouse, which matches the question's requirement that transformation happens before loading. This is the classic pattern for data warehouses where the target schema is fixed and data quality must be enforced upstream. ELT, by contrast, loads raw data first and transforms it inside the warehouse using its compute engine.

Answer

Data virtualization

Answer

ELT

Answer

Data replication

Question 12

A data analyst is creating a dashboard for executives to show monthly sales trends over the past year. Which chart type is most appropriate?

Accepted Answer

Line chart. A line chart is the most appropriate choice because it excels at showing continuous data trends over time, such as monthly sales over a year. The x-axis represents the time dimension (months), and the y-axis represents sales values, allowing executives to easily identify upward or downward trends, seasonality, and inflection points. This aligns with the goal of communicating data insights clearly and effectively.

Answer

Stacked bar chart

Answer

Scatter plot

Answer

Pie chart

Question 13

An organization is integrating data from multiple sources into a data warehouse. They need to handle differences in data granularity (e.g., daily vs. hourly sales data). Which technique is most appropriate?

Accepted Answer

Data aggregation. Data aggregation is the correct technique because it allows the organization to roll up hourly sales data to a daily granularity, ensuring consistency when integrating sources with different levels of detail. By applying aggregation functions (e.g., SUM, AVG) during the ETL process, the data warehouse can store all data at a common grain, which is essential for accurate reporting and analysis.

Answer

Data normalization

Answer

Data deduplication

Answer

Data profiling

Question 14

A data analyst is creating a weekly KPI email for executives. Which TWO attributes are most important for this type of report?

Accepted Answer

Providing an executive summary with key metrics. Scheduled reports for executives should be concise and automated, with clear headline metrics and context.

Answer

Allowing interactive drill-down

Answer

Including raw data tables

Answer

Including real-time data

Question 15

A data analyst is designing a dashboard for executives to monitor company performance. Which THREE practices should the analyst follow to ensure effective storytelling with data? (Select three.)

Accepted Answer

Annotate key events on time-series charts. Option A is correct because annotating key events (such as product launches, outages, or policy changes) directly on time-series charts gives executives immediate context for spikes and dips, turning raw trends into an explanatory story rather than an unexplained line. Option D is correct because selecting the chart type that matches the intended message — for example, line charts for trends over time, bar charts for comparisons across categories, and scatter plots for correlation — ensures the visual encoding reinforces the insight instead of obscuring it. Option E is correct because structuring the dashboard around a narrative arc (situation, complication, resolution) mirrors how executives reason about performance: it establishes the baseline, highlights the deviation or problem, and points to the recommended action. Option B is not appropriate because cramming in as much data as possible creates clutter and cognitive overload, which undermines clarity and focus on the key message. Option C is not appropriate because pie charts are generally poor for part-to-whole comparisons with many categories and are widely discouraged in favor of bar charts, so 'always' using them is not an effective storytelling practice.

Answer

Include as much data as possible to avoid missing details

Answer

Always use pie charts for part-to-whole comparisons