DA0-002 Practice Exam 65 — 20 Questions

Question 1

A logistics company stores shipment records in a relational database. The ShipmentID column uniquely identifies every shipment, and the CarrierName column stores the name of the carrier that moved each shipment, such as "Northwind Freight" or "Acme Logistics". Analysts frequently group shipments by carrier to compare on-time performance. Which statement correctly describes the relationship between these two columns in this table?

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

Accepted Answer

ShipmentID is the primary key of the table, and CarrierName is a non-key descriptive attribute. Because ShipmentID uniquely identifies each shipment row, it serves as the primary key, while CarrierName simply describes an attribute of the shipment that can repeat and supports grouping. A foreign key must point to a unique parent key in another table, a candidate key must be unique, and a composite key is unnecessary when a single column already guarantees uniqueness. The described schema therefore fits the primary key plus descriptive attribute model.

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CarrierName is a candidate key because analysts group by it frequently

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ShipmentID and CarrierName together form a composite primary key

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ShipmentID is a foreign key that references CarrierName as its parent key

Question 2

A financial services firm stores customer account records in a relational database. An analyst must assign a classification label to a new table containing Social Security numbers, account balances, and transaction histories. The firm's data governance policy defines four tiers: Public, Internal, Confidential, and Restricted. Which classification tier is most appropriate for this table?

Accepted Answer

Restricted. Social Security numbers combined with account balances and transaction histories represent the most sensitive category of data the firm handles. The highest classification tier exists precisely for regulated identifiers and financial records whose disclosure triggers legal penalties and identity theft risk. Assigning Restricted ensures the table receives maximum access controls, encryption, and audit monitoring consistent with the governance policy.

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Confidential

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Internal

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Public

Question 3

A data analyst is examining a dataset of customer transactions and notices that the distribution of transaction amounts is highly skewed to the right. The analyst wants to apply a transformation to make the distribution more symmetric for use in a linear regression model. Which of the following transformations is most appropriate?

Accepted Answer

Logarithmic transformation. For highly right-skewed positive data like transaction amounts, the logarithmic transformation is the standard choice to reduce skewness and make the distribution more symmetric. It compresses the upper tail and can linearize relationships, which benefits linear regression. Other transformations like square root are weaker, while reciprocal and squaring are either too strong or counterproductive.

Answer

Box-Cox transformation with lambda = 2

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Square root transformation

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Reciprocal transformation

Question 4

A data analyst is validating a regression model that predicts monthly churn probability for 50,000 subscribers. The analyst wants to detect whether the model is overfitting before deploying it. (Choose two.)

Accepted Answer

Compare the model's error on the training set with its error on a held-out validation set. Overfitting is detected by measuring how well a model performs on data it did not train on. Holding out a validation set and comparing its error with training error reveals the generalization gap, while k-fold cross-validation repeats that comparison across multiple partitions to produce a stable estimate. Together they show whether the churn model has learned signal versus memorized noise, which is exactly what must be established before deployment.

Answer

Remove all records with missing values from the validation set only

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Increase the number of predictor variables until training accuracy reaches 100 percent

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Apply a log transformation to the target churn probability before evaluation

Question 5

A multinational corporation is implementing a data governance framework. The legal team requires that data stored in the European Union not be transferred to the United States without adequate safeguards. The data engineering team uses a cloud-based data warehouse that replicates data across regions for performance. Which mechanism should the governance team prioritize to ensure compliance with cross-border data transfer requirements?

Accepted Answer

Implementing data residency controls that restrict storage and processing of EU personal data to EU regions only.. Data residency controls are the most direct and preventive mechanism because they restrict EU personal data to EU regions, eliminating unauthorized cross-border transfers at the architectural level. This aligns with the legal requirement and avoids reliance on complex legal safeguards that may not fully address automatic replication in a cloud data warehouse.

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Using standard contractual clauses (SCCs) for all data transfers, including intra-company transfers to the US.

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Relying on the EU-US Privacy Framework certification of the cloud provider to cover all transfers.

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Encrypting all data with customer-managed keys so that US-based staff cannot decrypt EU data.

Question 6

A data architect is designing a system for a subscription streaming service. The service must record every play, pause, and skip event from millions of concurrent viewers with very low write latency, and it must later support analytical queries over months of event history. The architect wants a single storage layer that handles both needs without a separate transformation pipeline. Which data architecture should the architect choose?

Accepted Answer

A lakehouse that combines open table formats with ACID transactions and query engines over the same storage. A lakehouse unifies streaming ingestion and analytical querying on one storage layer by adding ACID transactions and schema management to open table formats on object storage. This satisfies the requirement for low-latency event writes plus months of queryable history without a separate transformation pipeline.

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A message queue that retains events for a fixed retention period and serves analytical queries directly

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A traditional data warehouse that ingests events only through nightly ETL batches

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A data lake that stores raw event files and requires a separate batch job to load them into a warehouse

Question 7

A data analyst is designing a dashboard to monitor real-time website traffic. The dashboard will be used by the operations team to quickly identify anomalies and take immediate action. Which two design elements are most critical to include? (Choose two.)

Accepted Answer

Clear visual alerts (e.g., color-coded thresholds) for metrics exceeding normal ranges.. The two most critical elements are automatic refresh with a timestamp and clear visual alerts for anomalies. Real-time monitoring demands that data is current and that deviations from normal are immediately visible. A timestamp builds trust in data freshness, while color-coded thresholds enable split-second recognition of issues. Together, they empower the operations team to act quickly and confidently.

Answer

A detailed data table showing all raw traffic data for the current day.

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A historical trend line showing traffic over the past year for context.

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Drill-down capabilities to explore individual user sessions.

Question 8

A data analyst at a subscription streaming service is designing a dashboard for the customer success team. The team needs to monitor, side by side, the current month's churn rate against the same month last year and against a target churn rate of 4.5%. The analyst wants viewers to instantly see whether the current rate is above or below target. Which design approach best supports this?

Accepted Answer

A KPI card showing the current churn rate, the prior-year value, and the target, with a conditional indicator that changes when the target is exceeded. A KPI card with the current churn rate, the prior-year comparison, and the target, plus a conditional indicator, packages exactly the three values the team needs and converts the target comparison into an immediate visual cue. Gauges, tables, and stacked area charts either hide the target relationship or require manual interpretation, slowing the team's ability to act when churn drifts above 4.5%.

Answer

A detailed table listing monthly churn rates for the last 24 months with conditional formatting on the target column

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A gauge chart showing the current churn rate with a needle and colored zones for acceptable and unacceptable ranges

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A stacked area chart showing churn rate components over the last 12 months

Question 9

A national retailer is consolidating data from 40 regional stores into a central analytics platform. Each region uses different codes for the same product categories, and store managers report sales in local currencies. Before loading the data, the integration team must resolve these inconsistencies. Which two activities are appropriate steps to standardize the data? (Choose two.)

Accepted Answer

Convert all monetary values to a single reporting currency using a defined exchange rate table.. Standardizing inconsistent data requires resolving both the category code mismatch and the currency unit mismatch. A crosswalk mapping table unifies product categories under one enterprise code set, while conversion using a governed exchange rate table unifies monetary values into one reporting currency. Deleting records, isolating databases, or deferring translation to report time all leave the inconsistencies unresolved or shift the burden downstream.

Answer

Delete records from regions whose currency differs from the headquarters currency.

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Store each region's data in a separate database and report from each database independently.

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Allow each region to keep its own category codes and currencies, and resolve differences during reporting.

Question 10

A data analyst is preparing a dashboard that will be embedded in a public-facing web page and refreshed nightly. The source system contains customer names and account numbers, but the dashboard only needs aggregated counts by region and product line. Which two practices should the analyst apply to reduce disclosure risk while keeping the dashboard functional? (Choose two.)

Accepted Answer

Suppress or combine aggregate cells whose counts fall below a minimum group size threshold.. Minimizing the dataset to only the fields the dashboard consumes removes direct identifiers at the source, and enforcing a minimum group size on aggregate cells blocks the inference route where a tiny count can single out an individual. Together they let regional and product-line counts be published on a public page while removing the two most common re-identification paths.

Answer

Restrict the dashboard to authenticated internal users so the public page shows a login prompt instead of the report.

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Embed the full source table in the page and rely on the chart configuration to display only aggregated values.

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Obscure the identifiers by applying a simple substitution cipher to the name and account number columns before publishing.

Question 11

A data analyst is evaluating a classification model for predicting customer churn. The model's confusion matrix shows 100 true positives, 20 false positives, 30 false negatives, and 850 true negatives. The analyst wants to assess the model's ability to correctly identify actual churners. Which metric should the analyst use?

Accepted Answer

Recall. The analyst wants to assess the model's ability to correctly identify actual churners, which is the definition of recall (sensitivity). Recall is calculated as true positives divided by the sum of true positives and false negatives. In this scenario, recall is 100/(100+30) ≈ 0.769. Precision and specificity focus on different aspects, and accuracy can be misleading in imbalanced datasets.

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Precision

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Accuracy

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Specificity

Question 12

A data analyst is using a decision tree to predict customer churn. The tree is very deep, with many branches, and achieves 99% accuracy on the training data but only 70% on the test data. Which technique should the analyst use to address this issue?

Accepted Answer

Apply pruning to the decision tree. Pruning is a technique specifically designed to reduce overfitting in decision trees by removing unnecessary branches. The large discrepancy between training and test accuracy indicates the model is too complex and has memorized the training data. Pruning simplifies the tree, improving its ability to generalize. Other options either worsen overfitting or do not directly address the model complexity.

Answer

Use a larger training dataset

Answer

Decrease the size of the test set

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Increase the maximum depth of the tree

Question 13

A data team is ingesting JSON event data from a mobile application into a columnar warehouse. Each event has a nested array of product objects, and analysts frequently need to report on individual products within those events. The team wants to avoid repeated manual parsing in every query. Which approach best prepares the data for efficient product-level analysis?

Accepted Answer

Flatten the nested product array into a separate table with one row per product and a foreign key back to the event, during the load process.. The requirement is reusable, efficient product-level analysis from nested JSON. Shredding the array into a child table during load normalizes the structure, lets the columnar warehouse store each product as a row, and removes repeated parsing from reports. Storing raw JSON, querying nested arrays each time, or converting to positional text all defer or damage the preparation work.

Answer

Convert the entire event to a single delimited text field and split it into columns by position.

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Keep the nested array as-is and rely on the warehouse's native semi-structured query functions for every report.

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Store the raw JSON as a single string column and parse it at query time using string functions.

Question 14

A data analyst is profiling a dataset of customer records and discovers that 12% of the rows have missing values in the "postal_code" column, while the "customer_id" column is fully populated. The analyst needs to document this finding for a data quality report. Which data quality dimension does the missing postal code values primarily violate?

Accepted Answer

Completeness. Completeness assesses whether all required values are present. The postal_code column has 12% missing entries, meaning the dataset does not fully capture that attribute for all customers, which is the defining characteristic of a completeness violation. Accuracy, consistency, and uniqueness address correctness, agreement, and duplication respectively, none of which describe absent values.

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Uniqueness

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Accuracy

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Consistency

Question 15

A data analyst is building a decision tree to classify whether customers will churn. The analyst wants to prevent the tree from overfitting the training data. Which technique should the analyst use?

Accepted Answer

Pruning the tree after full growth. Pruning is a standard technique to reduce decision tree overfitting by removing branches that do not improve predictive accuracy on validation data. It simplifies the model and enhances generalization. Increasing depth, using all features, or allowing single-sample leaves all increase complexity and overfitting risk, making them incorrect choices for this scenario.

Answer

Increasing the maximum depth of the tree

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Setting the minimum samples per leaf to 1

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Using all available features without selection

Question 16

A data analyst is preparing a dataset for a machine learning model and notices that several numerical features have different scales (e.g., age ranges from 18-90, income from 20,000-200,000). The analyst decides to apply feature scaling. Which TWO of the following statements about scaling techniques are correct? (Choose two.)

Accepted Answer

Standardization (Z-score normalization) transforms features to have a mean of 0 and a standard deviation of 1, and is less affected by outliers than min-max scaling.. Min-max normalization scales to a fixed range but is sensitive to outliers, while standardization centers data with unit variance and is less affected by outliers. Both are common scaling techniques. The other statements misrepresent properties of scaling or incorrectly claim that distance-based algorithms are scale-invariant.

Answer

Feature scaling is unnecessary for distance-based algorithms like k-nearest neighbors (KNN) because they are scale-invariant.

Answer

Standardization scales features to a range of [0, 1] and is preferred when features have different units.

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Min-max normalization preserves the shape of the original distribution and is robust to outliers.

Question 17

A data analyst is building a dashboard for a regional sales director who needs to monitor daily performance across 12 territories. The director wants to instantly see which territories are below target, with the ability to click a territory to view its individual store details. The analyst decides to use a bullet chart for each territory. Which design choice best supports the director's need for immediate exception identification and drill-down?

Accepted Answer

Apply a conditional color rule that highlights bullet charts in red when actual sales fall below the target, and enable drill-through to a store-level detail page.. The director needs to instantly spot territories below target and then drill into store details. Conditional formatting on bullet charts uses color to preattentively flag exceptions, while drill-through provides the required detail. Together, these features meet both requirements without forcing the director to interpret each chart individually.

Answer

Use a stacked bar chart with actual and target values stacked on top of each other, and add a tooltip showing the variance.

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Replace the bullet charts with a single pie chart showing each territory's percentage of total sales.

Answer

Use a uniform color for all bullet charts and rely on the target marker position to indicate performance.

Question 18

A data governance council at an insurance company is reviewing an incident in which an analyst exported a customer dataset to a personal cloud drive. The council wants a control that detects and blocks sensitive data leaving the managed environment regardless of which application initiates the transfer. Which control type should the council implement?

Accepted Answer

Data loss prevention policies enforced on endpoints and network egress. Detecting and blocking sensitive data leaving the managed environment requires content-aware inspection at the points where data exits, which is the role of data loss prevention on endpoints, email, and network egress. Access control, encryption at rest, and retention schedules address different risks and cannot stop a user from exporting data during an active session.

Answer

Role-based access control applied to the data warehouse

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Column-level encryption of the customer dataset at rest

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A data retention schedule that deletes customer records after seven years

Question 19

A retail analytics team publishes a dashboard showing average order value by store. A regional manager notices that the store with the highest average order value is also the store with the fewest orders, and questions whether that store is genuinely the best performer. Which dashboard design change would BEST let the manager judge that store fairly?

Accepted Answer

Add order-count context to the measure, for example by displaying the number of orders alongside the average and sizing or annotating the mark accordingly.. The manager's objection is fundamentally about sample size: an average built on few orders is unstable and easy to top by chance. Pairing the average with the order count, or encoding volume in the mark itself, gives the reader the information needed to weigh the result appropriately while preserving the requested metric. Substituting a different metric, transforming the scale, or filtering out small stores all fail to expose reliability.

Answer

Switch the metric from average order value to total revenue by store and rebuild the ranking on that basis.

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Remove the lowest-volume stores from the dashboard so the ranking reflects only established locations.

Answer

Apply a logarithmic scale to the axis showing average order value so differences between stores appear smaller.

Question 20

An e-commerce company stores product descriptions that contain accented characters and emoji in customer reviews. The database currently fails to store these characters correctly, replacing them with question marks. Which action should the data engineer take to resolve this issue?

Accepted Answer

Set the column's character set to UTF-8 and ensure the connection uses UTF-8 encoding. The symptom of accented characters and emoji becoming question marks is a classic encoding problem. Unicode character sets such as UTF-8 can represent virtually all characters, while legacy encodings cannot. Aligning both the column character set and the client connection encoding to UTF-8 ensures end-to-end representation and storage of multibyte characters without corruption.

Answer

Increase the maximum length of the VARCHAR column

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Convert the column to a BLOB data type to store raw bytes

Answer

Change the column data type from VARCHAR to CHAR