DA0-001 Mining and Acquiring Data Practice Test 5 — 15 Questions

Question 1

A financial analyst is integrating data from multiple stock exchanges. One exchange provides trade timestamps in UTC, another in Eastern Time. The analyst needs accurate time synchronization for time-series analysis. What is the best approach?

Accepted Answer

Convert all timestamps to a single timezone (e.g., UTC) during ETL. Option D (convert to UTC) is the standard. Option A (keep original with offset) adds complexity. Option B (local time) is inconsistent. Option C (ignore) leads to errors.

Answer

Keep original timezones and add a timezone offset column

Answer

Use the local time of the analyst's location

Answer

Ignore timezone differences if analysis is intraday

Question 2

An e-commerce company is merging customer data from three legacy systems. Two systems use email as unique identifier, but one system allows multiple customers per email. The third uses phone number. To create a unified customer view, the analyst should first:

Accepted Answer

Build a customer matching rule that uses multiple attributes (email, phone, name) with a confidence score. Option B is correct because merging data from systems with different identifier schemas requires a probabilistic matching approach. Using multiple attributes (email, phone, name) with a confidence score allows the analyst to resolve conflicts where email is not unique and phone numbers may be missing or formatted differently, creating a unified customer view without forcing a single key.

Answer

Request the IT team to modify the legacy system

Answer

Use email as primary key and ignore conflicts

Answer

Assign new unique IDs and discard existing identifiers

Question 3

A data engineer is tasked with acquiring data from a third-party vendor that provides daily file drops via SFTP. The files are large (10 GB each). The pipeline must load data into a data warehouse. Which approach optimizes for speed and reliability?

Accepted Answer

Stream the file directly from SFTP into warehouse using a data pipeline tool. Option B is correct because streaming the file directly from SFTP into the warehouse using a data pipeline tool (e.g., Apache NiFi, Airbyte, or Fivetran) eliminates the intermediate staging step, reducing disk I/O and latency. This approach leverages incremental processing and parallel streams to handle large 10 GB files efficiently, while built-in retry and checkpoint mechanisms ensure reliability against network interruptions.

Answer

Download the file to a staging server, then bulk insert into warehouse

Answer

Have the vendor push data via API instead of SFTP

Answer

Split the file into smaller chunks and load concurrently

Question 4

A data analyst is validating a dataset acquired from an external source. Which TWO actions are appropriate for data quality assessment?

Accepted Answer

Check for missing values in critical fields. Checking for missing values in critical fields is a fundamental data quality assessment step because missing data can indicate incomplete records, data corruption, or extraction errors. Identifying these gaps early allows the analyst to decide on appropriate handling strategies, such as imputation or rejection, before further processing. This aligns with data profiling best practices in the mining and acquisition phase.

Answer

Delete any rows with null values without review

Answer

Immediately load all data into production

Answer

Transform data to match target system without verification

Question 5

A company is acquiring social media data via a public API. Which TWO considerations are important for ensuring ethical and legal compliance?

Accepted Answer

Anonymize personal identifiable information (PII) before storage. Option C is correct because anonymizing PII before storage is a fundamental data privacy requirement under regulations like GDPR and CCPA. When acquiring data via a public API, the company must ensure that personal identifiers (e.g., names, email addresses, IP addresses) are removed or obfuscated to prevent re-identification, reducing legal liability and ethical risk.

Answer

Share raw data with third parties for additional insights

Answer

Use the data for any internal analysis without restrictions

Answer

Cache data indefinitely to avoid repeated API calls

Question 6

A data scientist is merging retail transaction data from online and in-store sources. Which THREE steps are required to ensure data consistency?

Accepted Answer

Ensure product IDs are standardized across sources. Options A (standardize product IDs), C (convert currency), and D (synchronize timestamps) are essential. Option B (use only store location) is insufficient. Option E (remove transactions with missing customer ID) may discard useful data.

Answer

Remove all transactions with missing customer ID

Answer

Merge data using only store location

Question 7

A data analyst receives the above JSON snippet from a web API. The analyst needs to extract the email addresses for all customers. Which JSONPath expression should be used?

Accepted Answer

$.customers[*].email. Option C is correct because the JSONPath expression `$.customers[*].email` uses the wildcard `[*]` to select all elements in the `customers` array and then accesses the `email` property of each element. This matches the requirement to extract email addresses for all customers from the JSON snippet.

Answer

$.customers[0].email

Answer

$..email

Answer

$.customers.email

Question 8

An analyst is reviewing the above SQL query used to acquire data. What does this query retrieve?

Accepted Answer

Customers who placed more than 5 orders in 2023. The SQL query uses a HAVING clause with COUNT(*) > 5 to filter customers who placed more than 5 orders in 2023. The WHERE clause restricts records to the year 2023, and the GROUP BY customer_id aggregates orders per customer. The condition '> 5' explicitly excludes customers with exactly 5 or fewer orders, making option A correct.

Answer

All customers who placed at least 5 orders in 2023

Answer

The total number of orders per customer in 2023

Answer

Customers who placed exactly 5 orders in 2023

Question 9

A data pipeline log shows the above error. Which data transformation should be applied during acquisition?

Accepted Answer

Preprocess the string to remove non-numeric characters, then convert to DECIMAL. Option B is correct because the error indicates that the pipeline encountered a string with non-numeric characters (e.g., '$1,234.56') when trying to load it into a DECIMAL column. Preprocessing the string to remove non-numeric characters (like currency symbols, commas) before conversion ensures the data is clean and parseable, which is a standard data transformation during acquisition to handle dirty source data.

Answer

Skip rows that cause errors

Answer

Use CAST(transaction_amount AS DECIMAL(10,2)) in SQL

Answer

Change the target column type to VARCHAR

Question 10

A marketing team wants to analyze customer sentiment from social media posts. Which data acquisition method is most appropriate?

Accepted Answer

Web scraping from public social media APIs. Option D is correct because web scraping from public social media APIs allows direct access to public posts for sentiment analysis. Option A is wrong because internal databases do not contain social media data. Option B is wrong because surveys are not real-time from social media. Option C is wrong because physical sensors are unrelated.

Answer

Internal database query

Answer

Physical sensor data

Answer

Survey questionnaire

Question 11

A data analyst needs to combine sales data from multiple regional databases with different schemas. Which process is best?

Accepted Answer

ETL (Extract, Transform, Load). Option B is correct because ETL (Extract, Transform, Load) is designed to extract data from various sources, transform it to a common schema, and load it into a target system. Option A is wrong because data replication copies data without transformation. Option C is wrong because data virtualization provides real-time access without storing. Option D is wrong because data federation also provides virtual integration but is less suited for combining data into a single store.

Answer

Data federation

Answer

Data replication

Answer

Data virtualization

Question 12

An organization is acquiring data from an external vendor. The vendor provides a flat file with inconsistent delimiters and missing values. Which step should be performed first in data acquisition?

Accepted Answer

Data profiling. Option C is correct because data profiling examines the data to understand its structure, quality, and issues before any cleansing or transformation. Option A is wrong because data cleansing is performed after profiling. Option B is wrong because data integration combines data from multiple sources. Option D is wrong because data transformation occurs after profiling.

Answer

Data integration

Answer

Data transformation

Answer

Data cleansing

Question 13

A data analyst is tasked with gathering data from a legacy system that only exports CSV files. The files contain headers but no data types. Which tool would best facilitate initial data exploration?

Accepted Answer

Python pandas. Option A is correct because Python pandas provides powerful data structures and functions for exploring and manipulating CSV data, including detecting data types. Option B is wrong because SQL database requires importing data first. Option C is wrong because Hadoop is overkill for CSV exploration. Option D is wrong because Tableau is visualization-focused and not ideal for initial data exploration without pre-processing.

Answer

Hadoop

Answer

Tableau

Answer

SQL database

Question 14

A company wants to collect real-time clickstream data from its website. Which acquisition method is most suitable?

Accepted Answer

Streaming API. A streaming API is the most suitable method for collecting real-time clickstream data because it enables continuous, low-latency ingestion of events as they occur. Unlike batch or manual methods, a streaming API (e.g., using WebSockets or HTTP/2 Server-Sent Events) pushes each click event immediately to the data pipeline, satisfying the real-time requirement.

Answer

Web scraping

Answer

Batch processing nightly

Answer

Manual entry

Question 15

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