DA0-002 Practice Test 22 — 15 Questions

Question 1

A data engineer is choosing a storage approach for a new analytics platform. The workload consists of wide, denormalized event tables with dozens of attributes, queries that scan a few columns across billions of rows, and heavy aggregation rather than single-row lookups. Which storage structure is best suited to this workload?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

A columnar storage format that stores values of each column contiguously and supports compression. The described workload reads a small number of columns from very wide tables and performs large aggregations, which is exactly what columnar storage optimizes: reading only the needed column segments and compressing similar values. Row-oriented tables with B-tree indexes favor point lookups, key-value stores favor document retrieval by key, and heavily normalized schemas add join overhead. Columnar layout therefore fits the analytical scan pattern best.

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A normalized schema with many small tables joined at query time

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A row-oriented relational table with a B-tree index on the primary key

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A key-value store that maps each event ID to a serialized JSON document

Question 2

An analyst runs an A/B test with 1000 users per group and observes a conversion rate of 5% in the control and 6% in the treatment. The p-value is 0.12. What should the analyst conclude?

Accepted Answer

The difference is not statistically significant at the 0.05 level.. A p-value of 0.12 is greater than the conventional significance level of 0.05, so the null hypothesis of no difference cannot be rejected. The observed difference between 5% and 6% conversion rates is not statistically significant at the 0.05 level. The analyst should conclude that there is insufficient evidence to claim the treatment outperforms control.

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The sample size is too small to detect an effect.

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The treatment significantly outperforms control.

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There is a 12% chance the treatment is better.

Question 3

An organization is implementing a centralized reporting layer to replace multiple departmental spreadsheets. Which governance principle does this support?

Accepted Answer

Single version of truth. A single version of truth ensures that all users access the same consistent data, eliminating discrepancies from siloed spreadsheets.

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Data dictionary

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Data lineage

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Row-level security

Question 4

A data analyst is evaluating a classification model that predicts whether a customer will churn. The model's confusion matrix shows 80 true positives, 20 false negatives, 30 false positives, and 120 true negatives. Which TWO of the following metrics can be directly calculated from this confusion matrix? (Choose two.)

Accepted Answer

Accuracy. Accuracy and precision are both classification metrics that can be computed directly from the counts in a confusion matrix. Accuracy gives the overall correct prediction rate, while precision focuses on the reliability of positive predictions. R-squared, RMSE, and adjusted R-squared are regression metrics and cannot be calculated from a confusion matrix, so they are not applicable.

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R-squared

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Root Mean Square Error (RMSE)

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Adjusted R-squared

Question 5

A data analyst is working with a dataset containing a categorical variable 'Education Level' with categories: High School, Bachelor's, Master's, PhD. The analyst wants to include this variable in a regression model. Which encoding technique should the analyst use?

Accepted Answer

One-hot encoding. One-hot encoding is the preferred method for nominal categorical variables in regression because it avoids imposing an artificial order or equal spacing. It creates separate binary indicators, allowing the model to estimate distinct effects for each education level. Label, binary, and ordinal encoding all introduce numerical relationships that may misrepresent the categorical nature of the data.

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Binary encoding

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Label encoding

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Ordinal encoding

Question 6

A retail analytics team is building a data catalog and must document the metadata for a new sales fact table. The team needs to record structural metadata that describes how the data is organized. Which two items qualify as structural metadata for this table? (Choose two.)

Accepted Answer

The primary key constraint that enforces uniqueness on the sales transaction identifier. Structural metadata describes how data is organized: the columns and their data types, plus constraints such as primary keys that define row identity. Ownership, refresh timestamps, and business definitions describe accountability, operational state, and semantics respectively, which fall under administrative, operational, or descriptive categories. Documenting the column list with types and the primary key constraint therefore satisfies the structural requirement for the catalog.

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The name of the business owner accountable for the sales data

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The timestamp recording when the table was last refreshed from the source system

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A free-text business definition explaining what a completed sale means to the merchandising team

Question 7

A financial report must be retained for seven years to comply with regulatory requirements. This is an example of which data governance principle?

Accepted Answer

Data retention. Data retention policies specify how long data must be kept to meet legal or regulatory obligations.

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Data freshness

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Data lineage

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Data dictionary

Question 8

A data analyst is reviewing a dataset and notices that the 'ProductCategory' column contains inconsistent entries such as 'Electronics', 'electronics', and 'ELECTRONICS'. Which data cleaning technique should the analyst apply to standardize these values?

Accepted Answer

Case normalization. Case normalization is the appropriate technique to standardize text values that differ only by case. By converting all entries to a consistent case, the analyst ensures that 'Electronics', 'electronics', and 'ELECTRONICS' are treated as the same category. Other techniques like normalization, standardization, and one-hot encoding are not designed to fix case inconsistencies in text data.

Answer

Standardization

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Normalization

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One-hot encoding

Question 9

A data analyst is working with a dataset that contains a column 'income' with a highly skewed distribution. The analyst wants to apply a transformation to make the distribution more symmetric for use in a linear regression model. Which transformation is most appropriate?

Accepted Answer

Logarithmic transformation. A logarithmic transformation is effective for reducing right skewness in positive data like income. It compresses the upper tail, making the distribution more symmetric and improving linearity for regression. Standardization and min-max normalization only rescale without changing shape. Binning discards information and does not achieve symmetry. Therefore, the logarithmic transformation is the correct choice.

Answer

Min-max normalization

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Binning into equal-width intervals

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Standardization (z-score normalization)

Question 10

A data analyst is preparing a report on monthly website traffic for the marketing team. The team wants to see how the total number of visits has changed over the past 12 months. Which chart type is most appropriate for this purpose?

Accepted Answer

Line chart. A line chart is the best choice for visualizing trends over time because it connects data points to show continuity. For monthly website traffic, it clearly illustrates the direction and magnitude of changes across the 12-month period, enabling the marketing team to quickly grasp performance patterns and anomalies.

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Bar chart

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Pie chart

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Scatter plot

Question 11

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.

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Resolution → Complication → Situation

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Situation → Resolution → Complication

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Complication → Situation → Resolution

Question 12

A data analyst needs to perform stratified sampling on a customer database to ensure proportional representation across three regions: North (40%), South (30%), and West (30%). The total sample size required is 1,000. How many customers should be sampled from the North region?

Accepted Answer

400. Stratified sampling allocates sample size proportionally to each stratum's share of the population. North represents 40% of the population, so 40% of the 1,000-customer sample — 400 customers — should be drawn from North.

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333

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500

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300

Question 13

A data analyst is creating a dashboard to monitor website traffic. The dashboard will include metrics such as page views, unique visitors, and average session duration. The analyst wants to ensure the dashboard effectively communicates performance to the marketing team. Which TWO design elements should the analyst prioritize? (Choose two.)

Accepted Answer

Place the most important metrics in the top-left area of the dashboard.. Prioritizing a consistent color scheme for trends and placing key metrics in the top-left area enhances quick comprehension and guides the viewer's attention. These elements align with best practices for dashboard design, ensuring the marketing team can efficiently monitor website traffic performance.

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Use 3D charts to make the data more visually appealing.

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Include as many metrics as possible to provide a comprehensive view.

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Include a detailed data table beneath each chart for reference.

Question 14

A data analyst needs to design a report for two audiences: executives want a high-level trend, and operational managers need current inventory levels. Which approach best satisfies both?

Accepted Answer

Create two separate reports: an executive summary with trends and an operational dashboard with real-time inventory.. Providing a summary view for executives and a detailed view for operational managers addresses different needs.

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Include all details in one report so everyone sees the same information.

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Send only the operational dashboard and let executives derive trends.

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Ask the stakeholders to agree on a single view.

Question 15

A data analyst is tasked with creating a report that shows the proportion of total sales contributed by each product category. The analyst wants to use a chart that clearly displays the parts of a whole. Which chart type is most appropriate?

Accepted Answer

Pie chart. A pie chart is the most appropriate because it visually represents each product category's share of total sales as slices of a whole. This directly addresses the requirement to show proportions, making it easy for the audience to compare contributions at a glance.

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Histogram

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Scatter plot

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Line chart