DA0-002 Practice Test 31 — 15 Questions

Question 1

Which THREE of the following are common mistakes when creating data visualizations? (Choose 3.)

Accepted Answer

Using a 3D pie chart. Option B is correct because 3D pie charts distort the proportions of slices through perspective and depth, making values harder to compare accurately and adding visual clutter that misleads viewers. Option D is correct because bar charts encode value by bar length, so a non-zero baseline breaks that proportional encoding and visually exaggerates or shrinks differences between categories. Option E is correct because truncating the y-axis (especially on line or bar charts) compresses or magnifies the visible range, which can manufacture trends or differences that are not meaningful in the underlying data. Options A and C are not mistakes but best practices: choosing the correct chart type for the data ensures the visual encoding matches the data relationship, and labeling axes clearly gives viewers the units, scale, and context needed to interpret the chart correctly.

Answer

Choosing the correct chart type for the data

Answer

Labeling axes clearly

Question 2

An analyst is preparing data for a clustering algorithm that uses Euclidean distance. Which TWO data preprocessing techniques should be applied to ensure all features contribute equally?

Accepted Answer

Min-max normalization. Min-max normalization (A) is correct because it rescales each feature to a common range, typically [0, 1], via (x - min) / (max - min), so that no feature dominates the Euclidean distance calculation due to a larger scale. Z-score standardization (B) is also correct because it transforms each feature to mean 0 and standard deviation 1 using (x - μ) / σ, which equalizes the variance and ensures all features contribute equally to Euclidean distance. Log transformation (C) is not a scale-equalizing technique; it only compresses skewed distributions and does not guarantee equal feature contribution. Principal component analysis (D) is a dimensionality-reduction method, not a preprocessing step for equalizing feature scales. One-hot encoding (E) is for converting categorical variables into binary vectors and does not address differing numeric scales.

Answer

Log transformation

Answer

Principal component analysis

Answer

One-hot encoding

Question 3

Which TWO are common mistakes when creating data visualizations?

Accepted Answer

Using excessive 3D effects that obscure data. Option A is correct because excessive 3D effects distort proportions and depth cues, making values harder to compare accurately and often obscuring data points behind other elements. Option E is correct because starting the y-axis at a non-zero value on a bar chart exaggerates differences between bars, misleading viewers about the true magnitude of change. Option B is not a common mistake since alphabetical sorting is a legitimate, neutral ordering choice when no natural or quantitative order exists. Option C is not a mistake because color-blind friendly palettes improve accessibility and readability. Option D is not a mistake because a legend is a standard, helpful element for identifying chart elements.

Answer

Sorting categories alphabetically in a bar chart

Answer

Choosing a color-blind friendly palette

Answer

Including a legend to identify chart elements

Question 4

A data analyst is presenting a story to executives about a decline in sales. The analyst wants to show the key events that led to the decline, such as a product recall and a competitor's launch. Which storytelling technique should be used?

Accepted Answer

Annotating the line chart with event markers. Annotating a line chart with event markers ties specific business events (product recall, competitor launch) to the points in time where sales changed, making the causal narrative visually explicit. This is the standard storytelling technique for explaining a trend's drivers over time.

Answer

Using a pie chart to show current market share

Answer

Adding a waterfall chart to show incremental changes

Answer

Using a treemap to show hierarchical proportions

Question 5

An analyst is conducting an A/B test on a new website layout. Which TWO of the following must be defined before the test begins?

Accepted Answer

The significance threshold (alpha). Option D is correct because the significance threshold (alpha), typically set at 0.05, must be fixed in advance to determine the probability of a Type I error and to provide the criterion against which the resulting p-value will be judged. Option E is correct because the required sample size must be calculated beforehand, based on the desired statistical power (commonly 0.80), the baseline conversion rate, and the minimum detectable effect, to ensure the test can reliably detect a real difference. Options A, B, and C are not pre-test definitions: the final conversion rates and the actual p-value are outcomes observed only after the test concludes, and the confidence interval for the lift is likewise a post-hoc computed estimate rather than an input specified before the test begins.

Answer

The final conversion rates for each group

Answer

The actual p-value from the test

Answer

The confidence interval for the lift

Question 6

A data analyst is investigating a correlation between two continuous variables. Which THREE of the following are appropriate steps in this exploratory data analysis? (Select THREE.)

Accepted Answer

Calculate the Pearson correlation coefficient. Option A is correct because the Pearson correlation coefficient (r) is the standard statistic for quantifying the strength and direction of a linear relationship between two continuous variables, which is exactly the analyst's goal. Option B is correct because a scatter plot visually reveals the form, direction, and strength of the relationship between the two continuous variables and can expose non-linearity that a single correlation value would hide. Option D is correct because box plots (or their underlying IQR-based rules) identify outliers that can disproportionately distort the Pearson correlation coefficient, so checking for them is a necessary data-quality step before trusting r. Option C is not appropriate here because a t-test compares means between groups (or against a hypothesized mean), not the association between two continuous variables. Option E is not appropriate because a contingency table summarizes counts of categorical variables, whereas both variables in this scenario are continuous.

Answer

Perform a t-test

Answer

Create a contingency table

Question 7

An e-commerce company stores customer support emails in a text database, product images in a blob store, and sales transactions in a SQL table. Which data store holds only structured data?

Accepted Answer

SQL table. Structured data conforms to a predefined schema with rows and columns, enforcing data types and relationships. A SQL table is the canonical example of a structured data store because it organizes data into tables with fixed schemas, supports ACID transactions, and enables relational queries via SQL. In contrast, blob stores and text databases store unstructured or semi-structured data without a rigid schema.

Answer

Blob store

Answer

Text database

Answer

None

Question 8

A data analyst is designing a dashboard for executives. Which best practice should be followed regarding the placement of key performance indicators (KPIs)?

Accepted Answer

Place the most important KPIs in the top-left corner. Placing the most important KPIs in the top-left corner follows natural reading patterns (left-to-right, top-to-bottom), ensuring executives see critical metrics first. Option A is wrong because including too many charts on a single screen reduces readability and can overwhelm users. Option B is wrong because hiding KPIs behind filters defeats the purpose of having them visible at a glance. Option C is wrong because using distinct colors for all KPIs equally does not prioritize information; it may actually create visual clutter and reduce clarity.

Answer

Include as many charts as possible on a single screen to avoid scrolling

Answer

Hide KPIs behind filters to reduce initial load time

Answer

Use distinct colors to highlight all KPIs equally

Question 9

A data analyst is building a report that includes customer names and addresses. To comply with GDPR, what must the analyst do before publishing the report?

Accepted Answer

Anonymize the PII data. GDPR requires that personally identifiable information (PII) be anonymized to prevent individual identification in reports.

Answer

Add a data dictionary

Answer

Increase data freshness

Answer

Apply row-level security

Question 10

A financial analyst is preparing a report that must comply with the Sarbanes-Oxley (SOX) Act. What is the most critical requirement for this report?

Accepted Answer

Audit trail. SOX requires audit trails to ensure the integrity and traceability of financial data for compliance.

Answer

Row-level security

Answer

Data anonymization

Answer

Data dictionary

Question 11

Which TWO chart types are best suited for visualizing the distribution of a single continuous variable? (Select two.)

Accepted Answer

Box plot. A box plot (B) is correct because it summarizes the distribution of a single continuous variable using the median, quartiles, and potential outliers, making spread and skewness directly visible. A histogram (D) is correct because it bins a single continuous variable into intervals and displays frequencies, revealing the shape, center, and spread of the distribution. A scatter plot (A) is not appropriate here because it requires two continuous variables to show their relationship. A line chart (C) is used to show trends over an ordered sequence, typically time, not the distribution of one variable. A pie chart (E) displays proportions of a whole for categorical data, not the distribution of a continuous variable.

Answer

Scatter plot

Answer

Line chart

Answer

Pie chart

Question 12

A data analyst is communicating insights about a sales forecast to stakeholders. Which three of the following should the analyst include to build trust and clarity? (Select THREE.)

Accepted Answer

The confidence intervals around the forecast.. Option C is correct because confidence intervals quantify the range within which the true forecast value is likely to fall, giving stakeholders an honest measure of the forecast's precision rather than a single misleading point estimate. Option D is correct because stating the assumptions made in the forecast model (e.g., growth rates, seasonality, market conditions) lets stakeholders judge whether those premises match reality and understand how the results were derived. Option E is correct because discussing potential risks and uncertainties prepares stakeholders for scenarios where the forecast may not hold, which builds credibility and supports better contingency planning. Option A does not belong because presenting only the most optimistic scenario hides downside risk and biases decisions, undermining trust. Option B does not belong because dumping raw data on stakeholders adds noise without interpretation; the analyst should present summarized, relevant evidence instead of the full raw dataset.

Answer

Only the most optimistic scenario.

Answer

The raw data used for the forecast.

Question 13

In a time series analysis, a retail analyst observes consistent peaks in sales every December and troughs every February. This pattern repeats annually. Which component of time series does this represent?

Accepted Answer

Seasonality. Seasonality refers to regular patterns that repeat over fixed periods, such as months or quarters.

Answer

Irregular

Answer

Trend

Answer

Cyclical

Question 14

A data analyst is cleaning text data in a SQL database. Which THREE string functions are commonly used to standardize and clean text? (Choose three.)

Accepted Answer

REPLACE. REPLACE is correct because it substitutes specific substrings (e.g., removing stray characters or fixing inconsistent tokens) within a string, which is a core standardization step. UPPER is correct because it converts all characters to uppercase, enforcing consistent casing so values like 'usa' and 'USA' match during cleaning and comparison. TRIM is correct because it removes leading and trailing spaces (or specified characters), eliminating whitespace artifacts that break joins, grouping, and equality checks. LENGTH does not belong because it only returns the number of characters in a string and does not modify or standardize the data. CONCAT does not belong because it merely joins strings together, which is a transformation for combining values rather than cleaning or standardizing text.

Answer

LENGTH

Answer

CONCAT

Question 15

An analyst is performing a linear regression and obtains an R-squared value of 0.85. Which of the following is the best interpretation?

Accepted Answer

The model explains 85% of the variability in the dependent variable.. R-squared (R²) is the coefficient of determination, representing the proportion of variance in the dependent variable that is predictable from the independent variable(s). An R² of 0.85 means that 85% of the variability in the dependent variable is explained by the regression model, indicating a strong fit. This is the standard statistical interpretation.

Answer

85% of the residuals are zero.

Answer

85% of the data points lie on the regression line.

Answer

There is an 85% chance that the relationship is causal.