DA0-002 Data Acquisition and Preparation Practice Test 6 — 15 Questions

Question 1

A financial institution needs to acquire credit transaction data from multiple sources while ensuring compliance with data privacy regulations. What is the most critical step?

Accepted Answer

Data anonymization during extraction. Data anonymization during extraction is the most critical step because it ensures that personally identifiable information (PII) is irreversibly masked or removed before the data enters the processing pipeline, directly addressing compliance with regulations such as GDPR and PCI DSS. Without this step, even if other measures are applied later, the initial exposure of sensitive data violates privacy mandates and increases breach risk.

Answer

Data replication for redundancy

Answer

Data enrichment with external sources

Answer

Data compression for storage

Question 2

A data analyst is extracting data from a relational database using SQL. Which clause is essential for limiting the rows retrieved to only those needed?

Accepted Answer

WHERE. WHERE. The WHERE clause is used to filter rows from a table based on specified conditions, limiting the result set to only the rows that meet those conditions. Option A (GROUP BY) is incorrect because it groups rows with same values into summary rows, not for filtering. Option B (ORDER BY) is incorrect because it sorts the result set, not filters. Option D (HAVING) is incorrect because it filters groups after aggregation, not individual rows. Therefore, WHERE is essential for limiting rows retrieved.

Answer

GROUP BY

Answer

ORDER BY

Answer

HAVING

Question 3

An e-commerce company is acquiring product data from multiple supplier APIs. The APIs return JSON with inconsistent field naming conventions. Which data acquisition technique should be applied?

Accepted Answer

Data mapping and transformation. Data mapping and transformation is the correct technique because the JSON responses from different supplier APIs use inconsistent field naming conventions (e.g., 'product_id' vs. 'ProductID'). This technique defines a schema to map source fields to a standardized target format, ensuring data consistency before loading into the company's system. Without transformation, downstream processes like analytics or inventory management would fail due to mismatched field names.

Answer

Data compression

Answer

Data deduplication

Answer

Data aggregation

Question 4

A data team is using web scraping to collect competitor pricing data. The target website has anti-scraping measures like CAPTCHAs and rate limiting. Which approach is most effective?

Accepted Answer

Use rotating proxies and respectful delays. Using rotating proxies and respectful delays helps evade anti-scraping mechanisms like CAPTCHAs and rate limiting by distributing requests across multiple IPs and mimicking human browsing behavior. Option A is incorrect because using a single IP address makes it easy for the website to block all requests from that IP. Option B is incorrect because disregarding robots.txt may violate the website's terms of service and could lead to legal action or IP bans. Option D is incorrect because increasing request frequency would trigger rate limiting and increase the likelihood of being blocked.

Answer

Use a single IP address

Answer

Disregard robots.txt

Answer

Increase request frequency

Question 5

Which TWO are examples of internal data sources? (Select exactly 2)

Accepted Answer

Relational databases. Relational databases are internal data sources because they store structured data generated and controlled within an organization's own systems. They are typically managed by internal IT teams and accessed via SQL queries, making them a classic example of an internal data repository.

Answer

APIs

Answer

Sensor readings

Answer

Social media comments

Question 6

A data analyst is evaluating data quality issues during acquisition. Which TWO issues are most likely to arise from merging data from different sources? (Select exactly 2)

Accepted Answer

Duplicate records. Options B and E are correct because merging data from different sources often leads to duplicate records (the same entity represented differently across sources) and formatting inconsistencies (such as different date formats, units of measurement, or naming conventions). Option A is wrong: user access permissions are a security concern, not a direct data quality issue arising from merging. Option C is wrong: slow network speed is a performance or infrastructure issue, not a data quality issue. Option D is wrong: high storage cost is a cost consideration, not a data quality issue.

Answer

User access permissions

Answer

Slow network speed

Answer

High storage cost

Question 7

Which THREE are best practices for acquiring data via web scraping? (Select exactly 3)

Accepted Answer

Respect robots.txt. Options B, C, and E are correct because best practices for web scraping include respecting robots.txt (ethical and legal compliance), identifying yourself with a user-agent (transparency), and limiting request rate (avoid overloading servers). Option A is incorrect because using multiple IP addresses is often used to circumvent blocking, which can violate terms of service and is not a recommended best practice. Option D is incorrect because scraping all data without regard to terms is unethical and potentially illegal.

Answer

Use multiple IP addresses

Answer

Scrape all data without regard to terms

Question 8

Refer to the exhibit. What is the most likely issue causing the unexpectedly low count?

Accepted Answer

The signup_date column is in a different date format. If the signup_date column is stored in a different date format (e.g., MM/DD/YYYY), the comparison with '2023-01-01' (YYYY-MM-DD) may not match many records, leading to an unexpectedly low count. Option A is incorrect because indexing affects performance, not the correctness of the count. Option B is incorrect because COUNT(*) aggregates all rows and does not require a GROUP BY clause. Option C is incorrect because a database refresh typically updates data but does not directly cause a mismatch in date comparisons.

Answer

The customers table is indexed incorrectly

Answer

The query is missing a GROUP BY clause

Answer

The database was not refreshed

Question 9

Refer to the exhibit. What is the most likely cause of the extraction failure?

Accepted Answer

The network firewall is blocking the port. Connection timeouts with consistent 30-second delays suggest the network firewall is blocking the port, causing the connection to hang until timeout. Option A is wrong because if the server were down, the error would be connection refused immediately. Option C is wrong because a complex query would cause a slow query, not a connection timeout. Option D is wrong because a locked table would cause a lock wait timeout, not a connection timeout.

Answer

The source table is locked

Answer

The extraction query is too complex

Answer

The database server is down

Question 10

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 11

A marketing analyst needs to combine customer data from a CRM database with social media engagement data from a third-party API. Which data acquisition method is most appropriate?

Accepted Answer

API integration. API integration is the most appropriate method because it allows the analyst to programmatically retrieve structured social media engagement data directly from the third-party service's RESTful or GraphQL API endpoints. This approach ensures real-time or near-real-time data synchronization, supports authentication (e.g., OAuth 2.0), and returns data in standardized formats like JSON or XML, which can be directly ingested into the CRM system without manual intervention.

Answer

Web scraping

Answer

Manual data entry

Answer

Batch file upload

Question 12

A data analyst is tasked with collecting data from multiple spreadsheets provided by different departments. Each spreadsheet has different column names and formats. What is the best first step?

Accepted Answer

Develop a data dictionary and standardize column names. Developing a data dictionary and standardizing column names ensures consistency across all data sources before loading, reducing errors and facilitating integration. Immediately loading data can cause inconsistencies. Discarding mismatched data loses potentially valuable information. Using a machine learning model is an unnecessary and complex first step.

Answer

Discard any mismatched data

Answer

Use a machine learning model to clean data

Answer

Immediately load all data into a database

Question 13

A data engineer is designing an ETL pipeline to extract sales data from a legacy on-premise database and load it into a cloud data warehouse. The database is slow and queries during business hours affect performance. Which extraction strategy minimizes impact?

Accepted Answer

Incremental extraction using Change Data Capture (CDC). Incremental extraction using Change Data Capture (CDC) minimizes impact on the legacy on-premise database by reading only the changed rows (inserts, updates, deletes) from transaction logs or change tables, rather than issuing heavy SELECT queries. This avoids full table scans or frequent queries during business hours, preserving database performance for operational workloads.

Answer

Query the database with SELECT * every hour

Answer

Full table extraction nightly

Answer

Use a database log shipping

Question 14

A research firm is acquiring data from public government databases via API. The API rate limits at 100 requests per minute. They need to download 10,000 records, but each request returns a maximum of 100 records. What is the most efficient approach to ensure complete acquisition without being blocked?

Accepted Answer

Use a retry logic with exponential backoff and pagination. Pagination with retry logic using exponential backoff allows the firm to send requests in a controlled manner, respecting the rate limit and handling potential failures. Sending all requests in parallel would likely exceed the rate limit and cause blocking. Downloading one record per second is too slow. Requesting a data dump via email is inefficient and may not be supported.

Answer

Request a data dump from the government via email

Answer

Download one record per second

Answer

Send all requests simultaneously in parallel

Question 15

Which TWO are valid data acquisition methods? (Select two.)

Accepted Answer

Web scraping. Web scraping and API calls are direct methods to acquire data from external sources. Data profiling and data normalization are data preparation techniques, not acquisition. Data encryption is a security measure.

Answer

Data normalization

Answer

Data encryption

Answer

Data profiling