DA0-002 Practice Exam 61 — 20 Questions

Question 1

A data team must implement a data retention policy to reduce storage costs while meeting legal requirements. Which TWO actions best achieve this?

Accepted Answer

Set data retention limits with automated deletion. Archiving old data to cheaper storage reduces primary storage costs, and setting retention limits ensures data is deleted when no longer needed, balancing cost and compliance.

Answer

Use data compression

Answer

Increase primary storage capacity

Answer

Implement data deduplication

Question 2

An organization has multiple systems that store customer information inconsistently. To create a single authoritative view of customer data, they implement a process that identifies and merges duplicate records. This is an example of which data management discipline?

Accepted Answer

Master Data Management (MDM). Master Data Management (MDM) is the discipline that creates a single authoritative view of customer data by identifying and merging duplicate records across systems. Option A is incorrect because Data governance focuses on policies and standards, not directly on merging records. Option B is incorrect because Data warehousing consolidates data for reporting and analysis, not for creating a golden record of master data. Option C is incorrect because Data quality ensures accuracy and consistency but is a component of MDM, not the specific discipline for managing master data.

Answer

Data governance

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Data warehousing

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Data quality

Question 3

An analyst creates a pie chart showing market share of four companies: A (45%), B (30%), C (15%), D (10%). A stakeholder complains that it is difficult to compare C and D. Which alternative chart should the analyst recommend?

Accepted Answer

Horizontal bar chart. A horizontal bar chart allows viewers to compare individual values by length, making it easy to see the difference between 15% and 10%. Pie charts rely on angles, which are difficult to compare for small slices. A line chart is for trends over time, a stacked bar chart shows parts of a whole but not individual comparisons as clearly, and a scatter plot shows relationships between variables. Thus, a horizontal bar chart is the best alternative for comparing C and D.

Answer

Line chart

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Stacked bar chart

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Scatter plot

Question 4

A data analyst creates a dashboard showing average order value by region. The chart indicates that one region has an unusually high average. Investigation reveals that the region has very few orders, but one large purchase inflates the average. Which data transformation should the analyst apply to improve the visualization?

Accepted Answer

Use median instead of mean for aggregation. Using the median instead of the mean reduces the influence of extreme values. The median is a robust measure of central tendency that is not skewed by a single large order, thus providing a more accurate representation of typical order values in that region. Option A (logarithmic scaling) could help with visualization of wide ranges but does not change the aggregation; option C (pie chart) is not suitable for comparing average values across regions; option D (removing all outliers) is too drastic and may discard valid data points.

Answer

Apply logarithmic scaling to the y-axis

Answer

Change the chart type to a pie chart

Answer

Remove all outliers from the dataset

Question 5

A company wants to show the number of products sold across different categories: Electronics, Clothing, Home Goods, and Books. Which chart type is most appropriate?

Accepted Answer

Bar chart. Bar chart is ideal for comparing categorical data across distinct groups.

Answer

Scatter plot

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Line chart

Answer

Pie chart

Question 6

Which TWO of the following are best practices for designing an accessible data visualization? (Choose 2.)

Accepted Answer

Add text labels or patterns to differentiate elements. Using colorblind-friendly palettes and adding text labels/patterns make charts accessible. Relying solely on color or using 3D effects reduces accessibility. Adding animation distracts.

Answer

Rely solely on color to convey information

Answer

Use 3D effects to make charts visually appealing

Answer

Include animated transitions between views

Question 7

Which TWO chart types are best suited to show the proportion of total sales contributed by each product category? (Select exactly two.)

Accepted Answer

Stacked bar chart. Options C and D are correct. Pie charts and stacked bar charts effectively show parts of a whole. Line charts show trends; scatter plots show relationships; histograms show distributions.

Answer

Histogram

Answer

Scatter plot

Answer

Line chart

Question 8

An analyst creates a dashboard with multiple visualizations. Which feature allows users to change the data displayed across all charts simultaneously?

Accepted Answer

Filter or slicer. A filter or slicer can be applied to multiple visualizations on a dashboard, allowing users to change the data displayed across all charts simultaneously. Option A (Linked chart) is not a standard feature for simultaneous filtering. Option B (Drill-down) enables exploring hierarchical data but does not affect multiple charts at once. Option D (Data segmentation) typically refers to dividing data into groups, not a cross-chart filtering mechanism.

Answer

Linked chart

Answer

Drill-down

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Data segmentation

Question 9

A data visualization specialist needs to display the relationship between advertising spend and revenue for 50 product categories over 12 months. The data has many overlapping points. Which chart type best reveals the correlation and density?

Accepted Answer

Scatter plot with alpha blending. A scatter plot with transparency (alpha blending) reveals both correlation and point density by showing overlapping points as darker areas. A bubble chart adds a third variable. A heatmap on a grid loses resolution. A line chart is not for correlation.

Answer

Heatmap with revenue binned

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Line chart for each category

Answer

Bubble chart

Question 10

Which THREE are best practices for designing a dashboard for executive consumption?

Accepted Answer

Ensure the dashboard is responsive for mobile devices. Options B, D, and E are correct. For executive dashboards, mobile responsiveness (B) ensures accessibility on any device, interactive filters (D) allow executives to drill down into time periods and regions, and displaying critical KPIs at the top (E) highlights key insights. Option A is incorrect because executives need summarized, not raw, data. Option C is incorrect because separate charts for each metric can create clutter; instead, use combined or summary visualizations.

Answer

Include detailed raw data tables for transparency

Answer

Use a separate chart for each metric to avoid clutter

Question 11

A financial analytics firm needs to acquire historical stock market tick data (millions of records per day) from a data vendor. The vendor provides data via FTP in binary format. The firm's existing infrastructure uses on-premise servers with limited storage and processing power. They need to stream the data into a cloud data lake for analysis. However, the binary format is proprietary and requires a licensed decoder. The budget is constrained. Which approach best meets the data acquisition requirements?

Accepted Answer

Purchase a license for the decoder and set up an ETL job to convert and upload. Purchasing the decoder license and setting up an ETL job to convert and upload to the cloud directly addresses the format issue and enables streaming to the data lake. Requesting CSV via email is impractical for millions of records. Negotiating for a JSON API is a good idea but may not be available or cost more than the decoder. Using a third-party service adds recurring costs and may introduce dependency.

Answer

Negotiate with the vendor to provide an API that outputs JSON

Answer

Request the vendor to send data in CSV format via email

Answer

Use a third-party cloud service that already decodes and normalizes the data for a subscription fee

Question 12

A retail company is acquiring sales data from 150 stores worldwide. Each store sends daily CSV files via email to a central email address. The data acquisition process is manual: an intern downloads each attachment and copies it into a shared folder. The shared folder is then accessed by an ETL tool that loads data into a data warehouse. Recently, the data warehouse has been missing records for several stores. The intern reports that some emails are not being received or are delayed. The company needs to improve the reliability and timeliness of data acquisition. Which course of action should be taken first?

Accepted Answer

Require stores to upload CSV files directly to a cloud-based storage bucket.. Requiring stores to upload CSV files directly to a cloud-based storage bucket eliminates dependency on email and manual intervention, addressing the root cause of missing records due to email delays or non-receipt. This approach improves reliability and timeliness. Option A is wrong because it still relies on email and increases manual effort. Option B, while potentially effective, is more complex to implement as a first step compared to switching to cloud uploads. Option C is wrong because automating email parsing still depends on email reliability, which is the underlying problem.

Answer

Train the intern to check email more frequently and manually verify all attachments.

Answer

Replace the email method with a web-based API that stores push data in real-time.

Answer

Implement an automated email parser that downloads attachments and moves them to the shared folder.

Question 13

Refer to the exhibit. An analyst runs this query before acquiring data from a PostgreSQL database. What is the primary purpose of this query?

Accepted Answer

To check for data freshness. The query shown in the exhibit retrieves the `last_analyzed` column from PostgreSQL's system catalog, which records when table statistics were last updated. Analyzing this timestamp helps the analyst determine if the table's data is fresh enough for the intended analysis, thus checking data freshness before acquisition.

Answer

To verify data types

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To find primary keys

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To identify duplicate tables

Question 14

Match each data analysis technique to its primary purpose.

Accepted Answer

Regression: Predicting a continuous outcome variable based on one or more predictor variables. The correct matches are: Regression with predicting continuous outcomes, Clustering with grouping similar data, Classification with assigning categories, and PCA with reducing dimensionality. Common confusions include swapping regression and clustering definitions.

Answer

Regression: Grouping similar data points together

Answer

Clustering: Predicting a continuous outcome variable

Question 15

Drag and drop the steps to perform a data backup using the 3-2-1 rule in the correct order.

Accepted Answer

Create at least three copies of your data, then store the copies on at least two different types of media, then ensure at least one copy is stored offsite, then regularly test your backups.. The 3-2-1 rule involves multiple copies, different media, offsite storage, and regular testing.

Answer

Store the copies on at least two different types of media, then ensure at least one copy is stored offsite, then create at least three copies of your data, then regularly test your backups.

Answer

Create at least three copies of your data, then ensure at least one copy is stored offsite, then store the copies on at least two different types of media, then regularly test your backups.

Answer

Regularly test your backups, then create at least three copies of your data, then store the copies on at least two different types of media, then ensure at least one copy is stored offsite.

Question 16

A telecommunications company is experiencing issues with its customer satisfaction survey data. The data is collected from multiple channels: phone, email, and web forms. Each channel uses a different scale for ratings: phone uses 1-10, email uses 1-5, and web uses 1-7. Additionally, some survey responses contain missing values for demographic fields. The data analyst needs to calculate an overall satisfaction score that is comparable across all channels. The company's leadership wants a single metric that minimizes distortion from the different scales. Which approach should the analyst use to standardize the ratings?

Accepted Answer

Normalize each rating to a 0-100 scale using min-max normalization.. Min-max normalization rescales each rating to a common 0-100 range using the formula (x - min) / (max - min) * 100. This preserves the relative distribution of responses within each channel while eliminating the effect of different scale lengths, making the scores directly comparable. It minimizes distortion better than simple multiplication or binary conversion, as it accounts for the full range of each original scale.

Answer

Calculate the average rating separately for each channel and then compare the averages.

Answer

Convert all ratings to a binary metric of satisfied (above midpoint) or unsatisfied.

Answer

Convert all ratings to a 1-10 scale by multiplying email ratings by 2 and web by 1.43.

Question 17

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

Accepted Answer

Box plot. A box plot (B) is appropriate for visualizing the distribution of a continuous variable because it displays the median, quartiles, and potential outliers, providing a five-number summary of the data. A histogram (D) is also appropriate as it groups continuous data into bins and shows the frequency distribution, revealing the shape, central tendency, and spread of the variable.

Answer

Bar chart

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Line chart

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Pie chart

Question 18

Refer to the exhibit. A data pipeline is failing to parse this log entry. What is the most likely cause of the error?

Accepted Answer

Unquoted string for country. The log entry uses space as a delimiter. The country field 'United States' contains a space but is not enclosed in quotes. When parsing, the space within the value is misinterpreted as a delimiter, causing the parser to split the field incorrectly. This results in a parsing failure. The unquoted string containing a space is the most direct cause of the error.

Answer

Missing comma between fields

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Incorrect data type for age

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Extra whitespace

Question 19

Which THREE of the following are common steps in data cleaning?

Accepted Answer

Imputing missing values. Imputing missing values is a common data cleaning step because real-world datasets often have gaps due to data collection errors or system failures. Techniques like mean/median imputation, regression imputation, or using algorithms like k-NN help preserve sample size and avoid bias that would result from simply dropping rows. This ensures the dataset remains usable for analysis without introducing significant distortion.

Answer

Removing outliers without justification

Answer

Increasing sample size

Question 20

A company is designing a data lake to store raw sensor data from IoT devices. The data arrives as JSON objects with varying schemas. Which storage approach is most appropriate?

Accepted Answer

Store raw JSON files in a distributed file system and apply schema-on-read. A data lake is designed to store raw data in its native format, and IoT sensor data with varying schemas is best handled by storing raw JSON files in a distributed file system (e.g., HDFS or Amazon S3). This approach leverages schema-on-read, where the schema is applied at query time rather than at write time, allowing flexibility for heterogeneous JSON objects without data loss or transformation overhead.

Answer

Ingest into a relational database with a predefined schema

Answer

Store each JSON object as a separate file in a compressed columnar format

Answer

Convert all JSON to Avro with a fixed schema before storing