DA0-002 Practice Test 34 — 15 Questions

Question 1

A data analyst receives a dataset with inconsistent date formats (e.g., "01/02/2023", "2023-01-02", "Jan 2, 2023"). Which data quality dimension is most directly affected?

Accepted Answer

Consistency. Consistency refers to the uniformity of data representation. Inconsistent date formats violate consistency, not accuracy, completeness, or timeliness.

Answer

Accuracy

Answer

Completeness

Answer

Timeliness

Question 2

A retail company processes daily transactions. The current system transforms data before loading it into the data warehouse. The volume is growing rapidly, and they want to load raw data first to reduce processing time. Which approach should they adopt?

Accepted Answer

ELT (Extract, Load, Transform). (ELT) because the company wants to load raw data first and then transform it later, reducing initial processing time. ELT leverages the power of modern data warehouses to perform transformations after loading, which is ideal for rapidly growing volumes of raw transaction data.

Answer

Change data capture (CDC)

Answer

ETL (Extract, Transform, Load)

Answer

Data replication

Question 3

A data governance team is establishing policies. Which three activities are part of data governance? (Select THREE.)

Accepted Answer

Data quality management. Data quality management is a core activity of data governance because it ensures that data meets defined standards for accuracy, completeness, consistency, and timeliness. Governance policies mandate monitoring and remediation processes to maintain data quality across the organization.

Answer

Data indexing

Answer

Data normalization

Question 4

A large e-commerce company has a data warehouse that stores daily sales transactions. The data analytics team creates a weekly report for the executive team that includes total revenue, number of orders, and average order value. Recently, the report showed a sudden 20% drop in total revenue compared to the previous week. Upon investigation, the data analyst discovers that a major promotional event ended the previous week, and the current week's data includes a new product launch with lower prices. The analyst needs to present this data to the executives in a way that accurately reflects the business situation. The analyst must also provide recommendations for actions. Which of the following is the best course of action?

Accepted Answer

Present the data with annotations explaining the promotion end and new product launch, and recommend analyzing customer retention and cross-selling opportunities.. It adheres to the principle of transparent data communication: the analyst must present the full dataset with contextual annotations (promotion end, new product launch) to avoid misleading executives. This approach enables informed decision-making, and the recommendation to analyze customer retention and cross-selling opportunities directly addresses the underlying business dynamics—understanding whether the revenue drop is temporary or signals a shift in customer behavior. In a data warehouse context, this ensures that the weekly report reflects the true state of the business rather than a manipulated or incomplete view.

Answer

Remove the new product launch data from the report to show a clearer comparison.

Answer

Present only the data from the new product launch to show growth potential.

Answer

Present the drop as-is and recommend cutting costs to compensate for the revenue decline.

Question 5

Which SQL function can be used to extract the year from a date column 'order_date'?

Accepted Answer

YEAR(order_date). The YEAR function extracts the year portion from a date.

Answer

DATEDIFF(year, order_date)

Answer

DATEADD(year, order_date)

Answer

FORMAT(order_date, 'yyyy')

Question 6

A data analyst needs to collect customer sentiment data from social media platforms. Which data acquisition method is most appropriate?

Accepted Answer

Use web scraping. Web scraping is the most appropriate method because it allows the data analyst to programmatically extract unstructured customer sentiment data (e.g., posts, comments, reviews) directly from social media platforms using HTTP requests and HTML parsing. Unlike surveys or focus groups, scraping can collect large volumes of real-time, publicly available data without relying on self-reported or curated responses.

Answer

Conduct a survey

Answer

Organize focus groups

Answer

Query the internal CRM

Question 7

A healthcare database stores patient records. Each patient has a unique patient_id, and the database includes a table 'visits' with visit_id, patient_id, visit_date, and diagnosis_code. To ensure data integrity, which constraint should be applied to the patient_id column in the 'visits' table?

Accepted Answer

Foreign key. A foreign key constraint ensures that patient_id in visits references a valid patient_id in the patient table. Option A is wrong because a unique constraint prevents duplicate values but allows one NULL, and does not enforce referential integrity. Option C is wrong because a primary key ensures uniqueness and serves as the table's identifier, but it does not enforce relationships between tables. Option D is wrong because a check constraint validates values based on a condition, not referential integrity.

Answer

Unique constraint

Answer

Primary key

Answer

Check constraint

Question 8

A data analyst creates a bar chart to compare average customer satisfaction scores across five departments. The chart shows very tall bars for three departments and very short bars for two departments, making differences hard to assess. What is the most likely cause and the best fix?

Accepted Answer

The y-axis does not start at zero; reset it to zero. A bar chart's y-axis should start at zero to accurately represent proportions; a truncated y-axis can exaggerate differences between bars. Option A is wrong because grouping by region does not address the axis scaling issue. Option C is wrong because a line chart is not suitable for comparing discrete categories. Option D is wrong because 3D charts can introduce visual distortion and are not recommended.

Answer

The chart should group departments by region to reduce variance

Answer

The data should be visualized as a line chart instead

Answer

The bar chart should be replaced with a 3D version for better depth

Question 9

An executive dashboard must display high-level KPIs such as current revenue, profit margin, and customer count. Which visualization type is most appropriate for each KPI?

Accepted Answer

KPI card showing value and variance. KPI cards (or tiles) are designed to display a single key metric, such as revenue, profit margin, or customer count, along with its variance (e.g., change over time or vs. target), making them ideal for executive dashboards where quick comprehension of high-level KPIs is critical. Pie charts are poor for showing individual values and cannot display variance; sparklines show trends but not the current value prominently; gauge charts are less precise for exact numbers. Therefore, KPI cards are the most appropriate choice.

Answer

Pie chart

Answer

Sparkline for each KPI

Answer

Gauge chart

Question 10

Which THREE actions improve the accessibility of data visualizations for users with visual impairments? (Select exactly three.)

Accepted Answer

Provide text alternatives for charts (e.g., data tables).. Options A, C, and D are correct. Text alternatives (A) allow screen readers to convey chart data. Clear labels (C) improve readability for all users. Sufficient color contrast (D) helps users with low vision. Using only color (B) to convey information excludes colorblind users, and animated transitions (E) can be distracting and are not an accessibility improvement.

Answer

Use only color to convey information.

Answer

Add animated transitions between views.

Question 11

A hospital's analytics team has created a dashboard for tracking patient wait times across departments. The dashboard uses a stacked bar chart showing average wait time per department, with each bar segmented by severity level (Low, Medium, High). However, management complains that it is difficult to compare total wait times across departments or identify which department has the highest average wait time. The data itself is accurate and complete. The analyst needs to redesign the visualization to address these concerns. Which course of action should the analyst take?

Accepted Answer

Change the chart to a grouped bar chart, with each department having separate bars for each severity level placed side-by-side.. A grouped bar chart with each department showing separate bars for each severity level placed side-by-side enables direct comparison of total wait times across departments and easy identification of the department with the highest average wait time. Option A is incorrect because multiple line charts are designed for time-series data, not for comparing categorical totals across departments, and would clutter the view. Option B is incorrect because a heat map can show patterns but does not allow clear comparison of total wait times or identification of the highest average. Option D is incorrect because a pie chart only shows proportions of a single category (e.g., total wait time per department) and loses severity-level information, making it impossible to compare total wait times meaningfully.

Answer

Replace the stacked bar chart with multiple line charts, one per department.

Answer

Use a heat map with departments on one axis and severity levels on the other, with color intensity representing wait time.

Answer

Switch to a pie chart showing the proportion of total wait time each department contributes.

Question 12

A data analyst is presenting a story about declining sales. The narrative arc should include which three elements in order?

Accepted Answer

Situation → Complication → Resolution. A compelling data story about declining sales follows the classic narrative arc: Situation (establish context, e.g., 'Sales were steady in Q1'), Complication (introduce the conflict, e.g., 'Then a 20% drop occurred in Q2'), and Resolution (present the insight or action, e.g., 'We identified the cause and implemented a new pricing strategy'). This order mirrors the 'Situation-Complication-Resolution' framework used in data storytelling to guide the audience logically from context to problem to solution.

Answer

Resolution → Complication → Situation

Answer

Situation → Resolution → Complication

Answer

Complication → Situation → Resolution

Question 13

An IT operations team monitors 200 servers. Each server reports CPU utilization (0-100%) every five minutes for the past year. The team wants to visualize the data to identify servers that are consistently over 80% utilization and detect any unusual spikes. They have a large dataset with 100,000+ records per server. The current visualization is a single scatter plot with CPU utilization on the y-axis, time on the x-axis, and each server as a different colored point. The chart is extremely cluttered, with points overlapping and colors indistinguishable. What should the team do to improve the visualization?

Accepted Answer

Use a heatmap showing CPU utilization over time per server, or create small multiple charts (one per server). Heatmaps and small multiples (trellis charts) are effective for visualizing large, dense datasets with multiple categories. A heatmap can show CPU utilization intensity over time for all servers in a compact form, making it easy to identify consistently high utilization and spikes. Small multiples create separate charts per server, avoiding overlap and allowing comparison. Option B is wrong because a single line chart with 200 lines would be even more cluttered than the scatter plot, making it impossible to distinguish individual servers. Option C is wrong because trend lines remove the individual data points needed to detect unusual spikes, and they would not show the actual utilization values. Option D is wrong because increasing the size of data points would worsen the overlap and clutter, making the chart even less readable.

Answer

Switch to a line chart with each server as a separate line

Answer

Add a trend line to each server's data and remove the individual points

Answer

Increase the size of the data points to make them more visible

Question 14

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 15

Which THREE of the following are common characteristics of unstructured data?

Accepted Answer

Often stored in NoSQL databases or data lakes. Options B, C, and E are correct. Unstructured data lacks a predefined schema, can include various media types, and is often stored in NoSQL or data lakes. A is wrong because unstructured data is not stored in relational tables. D is wrong because SQL queries are not designed for unstructured data.

Answer

Easily queried using SQL

Answer

Stored in relational tables