DA0-002 Practice Test 23 — 15 Questions

Question 1

A data analyst is building a time series forecasting model for monthly sales data. The analyst observes that the data has a clear upward trend and a seasonal pattern that repeats every 12 months. After differencing the data once to remove the trend, the analyst notices that the seasonal pattern remains. Which of the following should the analyst do next to properly model the data?

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

Accepted Answer

Apply a seasonal difference with lag 12.. After removing the trend with non-seasonal differencing, the persistent seasonal pattern indicates the need for seasonal differencing. Taking a difference at lag 12 removes the yearly seasonal effect, making the series stationary in both trend and seasonality. This step is crucial before fitting a SARIMA model, which can then include seasonal autoregressive and moving average terms to capture the remaining structure.

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Include a moving average term of order 12.

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Fit a non-seasonal ARIMA model with only autoregressive terms.

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Apply a second round of non-seasonal differencing.

Question 2

Which data quality dimension is violated if a customer record has a missing phone number?

Accepted Answer

Completeness. Completeness refers to the extent to which data is not missing.

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Consistency

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Accuracy

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Validity

Question 3

A data analyst is creating a report that shows the percentage of total sales contributed by each product category. The categories are: Electronics (45%), Clothing (30%), Home Goods (15%), and Toys (10%). Which chart type is most effective for displaying this information?

Accepted Answer

Pie chart. A pie chart is the most effective for showing the percentage contribution of each product category to total sales because it visually represents parts of a whole. With only four categories, the slices are easy to compare, and the chart immediately conveys the relative proportions, making it suitable for this composition analysis.

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Histogram

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Line chart

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Scatter plot

Question 4

A data analyst is designing a dashboard for a hospital's emergency department. The dashboard must display real-time patient wait times, current bed occupancy, and the number of patients waiting to be seen. The primary users are charge nurses and physicians who need to make quick staffing decisions. Which two design principles are most critical to ensure the dashboard is effective for this scenario? (Choose two.)

Accepted Answer

Use a consistent color scheme with red indicating critical thresholds and green indicating normal status.. For a real-time operational dashboard used in a high-pressure environment, immediate interpretability and data freshness are paramount. A consistent color scheme for thresholds allows quick status assessment, and frequent automatic refreshes ensure the data reflects current conditions. Both features directly support rapid, informed staffing decisions.

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Include detailed patient demographic information to provide context for each waiting patient.

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Use a complex, multi-layered drill-down structure to allow users to explore data from multiple angles.

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Display all available historical data to provide full context for current conditions.

Question 5

A data analyst at a logistics company receives a shipment-tracking table in which the carrier identifier column contains values such as 'FEDX', 'FedEx', 'fed ex', and 'FX'. The analyst needs to consolidate these into a single carrier value before building a delivery-performance dashboard. Which data preparation step should the analyst perform?

Accepted Answer

Standardize and normalize the categorical values through data cleansing.. The carrier column suffers from inconsistent representation of the same entity, a classic data cleansing issue. Trimming whitespace, normalizing case, and mapping aliases to a canonical label collapses the variants into one category. Numeric rescaling, missing-value imputation, and one-hot encoding all address different problems and would leave the duplicated carrier categories intact in the delivery dashboard.

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One-hot encode the carrier column into binary indicator fields.

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Impute the missing carrier values using the column mean.

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Apply min-max normalization to rescale the carrier column.

Question 6

A data analyst is designing a report that will be viewed on a large monitor in a conference room. The report includes a heatmap of customer satisfaction scores across different regions and time periods. The analyst notices that the color scale uses a rainbow gradient, and some viewers have difficulty distinguishing between adjacent colors. Which change should the analyst make to improve the readability of the heatmap?

Accepted Answer

Switch to a sequential color palette with varying lightness.. Switching to a sequential color palette that varies in lightness improves the heatmap's readability by making value differences easier to perceive. Lightness is a more effective visual encoding than hue, especially for viewers with color vision deficiencies, and it aligns with best practices for visualizing continuous data like satisfaction scores.

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Use a diverging color palette with red and green at the extremes.

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Add data labels to every cell in the heatmap to show exact values.

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Increase the number of colors in the rainbow gradient to provide more detail.

Question 7

A data analyst at a healthcare provider is reconciling patient records from two source systems. System A stores dates in 'MM/DD/YYYY' format, while System B stores dates in 'DD/MM/YYYY' format. During integration, the analyst notices that some records from System B have been incorrectly parsed, resulting in invalid dates. Which data preparation technique should the analyst apply to ensure consistent date interpretation?

Accepted Answer

Apply a regular expression to extract the day, month, and year components, then reassemble them in a standard 'YYYY-MM-DD' format.. The core issue is ambiguous date formats across sources. Explicitly parsing and reconstructing dates based on known source formats eliminates ambiguity. This method ensures each component is correctly identified before standardization, preventing misinterpretation that occurs when relying on default settings or automated detection.

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Use a CAST function to convert the string dates to a DATE data type, relying on the database's default date format.

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Convert all dates to Unix timestamps using a built-in function that automatically detects the format.

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Sort the dates as strings and then manually correct any that appear out of order.

Question 8

A data analyst is building a dashboard that tracks daily active users. The source system records one event row per user session, and a user can have multiple sessions in a day. The analyst needs to display the count of unique users per day. Which approach produces the correct daily active user count?

Accepted Answer

Count distinct user identifiers grouped by date. Daily active users is defined as the number of distinct users who take an action on a given day. Because the source grain is one row per session, the analyst must deduplicate users within each date before counting. A distinct count of the user identifier grouped by date performs exactly that deduplication and yields the correct metric, whereas counting rows or averaging sessions measures activity volume instead of reach.

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Sum the maximum session count per user across all dates

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Average the number of session rows per user for each date

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Count all session rows grouped by date

Question 9

A data analyst at a hospital network is exploring the relationship between patient age and length of stay for 400 discharged patients. A scatterplot shows a roughly linear upward trend, but the analyst wants a single number summarizing both the strength and direction of the association before reporting to clinicians. Which measure should the analyst calculate?

Accepted Answer

The Pearson correlation coefficient between age and length of stay.. For two continuous variables with an approximately linear relationship, the Pearson correlation coefficient is the standard single-number summary: it is bounded between -1 and 1, carries direction through its sign, and reflects strength through its magnitude. Covariance is scale-dependent, while R-squared and chi-square discard direction or require arbitrary categorization, so none of them answers the clinician-facing question as directly.

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The coefficient of determination from a model predicting age from length of stay.

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The chi-square statistic from a contingency table of age and length of stay.

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The covariance between age and length of stay.

Question 10

A data analyst at an e-commerce company is profiling a transactions table with ten million rows. The 'order_total' column is stored as text and contains values like '$1,299.00', a few entries of 'N/A', and several negative amounts that represent refunds. The analyst must produce a numeric column suitable for summation in a revenue report. Which sequence of operations best prepares the column?

Accepted Answer

Strip the currency symbol and thousands separators, convert non-numeric entries to null or a flagged value, preserve negative signs for refunds, then cast to decimal.. The column mixes formatting characters, non-numeric placeholders, and meaningful negative values. A robust cleanup removes currency symbols and separators, explicitly maps invalid entries to nulls or a flagged value, retains the negative sign for refunds, and then casts to a decimal type. Direct casting and character-stripping shortcuts either lose rows silently or corrupt the sign and precision of the amounts.

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Cast the column directly to a decimal type, letting the database coerce invalid strings to nulls.

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Replace all non-numeric characters with zeros, then sum the column as text.

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Take the absolute value of every entry first, then remove the dollar signs and cast to integer.

Question 11

A data analyst publishes a quarterly financial report in which the same revenue figure is printed on a summary page, a regional breakdown page, and an appendix table. The three values currently come from three separately written queries. Which practice most directly reduces the risk of the pages disagreeing?

Accepted Answer

Define the revenue metric once in a governed semantic layer and have all three pages consume that shared definition.. When one metric appears in several places, the durable fix is to compute it once in a governed semantic layer and let every consumer reference that definition. Shared logic removes the class of error where independently authored queries drift in filters, joins, or aggregation. Consistency then becomes a property of the architecture rather than of individual author diligence.

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Increase the refresh frequency of all three queries so they run within the same hour.

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Add a footnote to each page stating the date the query was last executed.

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Instruct each report author to cross-check their number against the other two pages before publishing.

Question 12

A data analyst at a regional bank is examining monthly account balances for 5,000 customers. The distribution is strongly right-skewed because a small number of high-net-worth clients hold very large balances. The analyst must report a measure of central tendency that best represents the typical customer without being pulled upward by those few extreme accounts. Which measure should the analyst report?

Accepted Answer

The median of the monthly balances.. With a strong right skew driven by a few very large balances, the mean is pulled upward while the median stays anchored near the middle of the ordered data. Because the request is for a representative central value that resists outliers, the median is the appropriate choice. Standard deviation and the range describe dispersion, not central tendency, so they cannot answer the question.

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The arithmetic mean of the monthly balances.

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The standard deviation of the monthly balances.

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The range between the minimum and maximum monthly balances.

Question 13

A data analyst is creating a report to compare the total sales revenue for five different product categories over the last four quarters. The analyst wants to show both the overall total and how each category contributes to that total for each quarter. Which chart type is most appropriate?

Accepted Answer

A stacked bar chart with quarters on the x-axis and sales on the y-axis, with segments for each category.. A stacked bar chart is ideal for showing both total values per quarter and the contribution of each category to those totals. It allows viewers to compare overall quarterly sales and see how the product mix changes over time. The other chart types either omit the total, obscure the part-to-whole relationship, or lose the time dimension.

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A pie chart with one slice per category, using the total sales across all quarters.

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A line chart with quarters on the x-axis and sales on the y-axis, with one line per category.

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A grouped bar chart with quarters on the x-axis and sales on the y-axis, with one bar per category.

Question 14

A data analyst is creating a report that compares the performance of five different marketing campaigns over the past year. The analyst wants to show both the total revenue generated by each campaign and the proportion of total revenue that each campaign represents. Which combination of visualizations is most effective for this purpose?

Accepted Answer

A bar chart showing total revenue by campaign and a pie chart showing the percentage of total revenue for each campaign.. The most effective combination is a bar chart for total revenue and a pie chart for proportion. A bar chart enables accurate comparison of revenue totals across campaigns, while a pie chart clearly illustrates each campaign's share of the total when there are only five categories. This dual approach directly addresses both analytical goals without requiring viewers to perform mental calculations.

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A treemap showing revenue by campaign, with rectangle sizes proportional to revenue.

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A line chart showing revenue trends for each campaign over the year and a scatter plot showing revenue versus campaign cost.

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A stacked bar chart showing revenue by campaign, with each bar segmented by month.

Question 15

A data analyst at a healthcare clinic is preparing a patient records dataset for analysis. The analyst discovers that the 'date_of_birth' column contains values stored as text strings in the format 'MM/DD/YYYY', but the analytics tool requires a date data type for age calculations. Which data transformation technique should the analyst apply?

Accepted Answer

Data type conversion. The dataset stores dates as text, which prevents date arithmetic. Converting the column to a date data type is the correct transformation because it changes the underlying representation to one that supports date functions. This enables accurate age calculations and other temporal operations required by the analytics tool.

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Data aggregation

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Data imputation

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Data normalization