DA0-002 Data Acquisition and Preparation Practice Test 5 — 15 Questions

Question 1

A healthcare organization acquires data from multiple hospitals with different patient record systems. The data includes patient IDs but no common identifier across systems. Which technique should be used to link records?

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

Accepted Answer

Probabilistic record linkage using name, DOB, and ZIP. (probabilistic linkage) is designed for such situations. Option A (merge without deduplication) creates duplicates and loses connections. Option B (random unique IDs) loses connections because there is no common identifier across systems. Option C (manual matching) is not scalable.

Answer

Merge all records without deduplication

Answer

Generate random unique IDs for each system

Answer

Manually match records for all patients

Question 2

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. (convert to UTC) is the standard. Option A (keep original with offset) adds complexity. Option B (local time) is inconsistent. Option D (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 3

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. 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 4

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. 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 5

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 6

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. 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 7

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), B (convert monetary amounts to a common currency), and D (synchronize timestamps to a single time zone) are essential for data consistency when merging online and in-store transaction data. Option C (remove all transactions with missing customer ID) is not required and may discard useful data; missing customer IDs can be handled in other ways. Option E (merge using only store location) is insufficient as it ignores other identifiers and may cause mismatches.

Answer

Remove all transactions with missing customer ID

Answer

Merge data using only store location

Question 8

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

$.customers[*].email. The JSONPath expression `$.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 9

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 10

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. 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 11

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. Web scraping from public social media APIs allows direct access to public posts for sentiment analysis, which is exactly what the marketing team needs. Option A is wrong because internal databases typically do not contain social media data. Option B is wrong because physical sensors are unrelated to social media sentiment. Option D is wrong because survey questionnaires are not real-time and do not capture existing social media posts.

Answer

Internal database query

Answer

Physical sensor data

Answer

Survey questionnaire

Question 12

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). 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 (Data federation) is wrong because it provides virtual integration without transforming data into a consistent schema. Option C (Data replication) is wrong because it copies data without transformation. Option D (Data virtualization) is wrong because it provides real-time access to disparate sources without physically storing the transformed data.

Answer

Data federation

Answer

Data replication

Answer

Data virtualization

Question 13

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. Data profiling is the first step because it examines the data to understand its structure, quality, and issues (like inconsistent delimiters and missing values) before any further processing. Option A (Data integration) is wrong because integration combines data from multiple sources and should follow profiling. Option C (Data transformation) is wrong because transforming data requires first understanding its current state through profiling. Option D (Data cleansing) is wrong because cleansing is performed after profiling identifies the issues.

Answer

Data integration

Answer

Data transformation

Answer

Data cleansing

Question 14

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. Python pandas. Python pandas is ideal for initial data exploration of CSV files because it provides Series and DataFrames for tabular data, automatic type inference, and functions like head(), info(), describe() to quickly understand the data. Option A (Hadoop) is overkill for a simple CSV file exploration. Option B (Tableau) is primarily for visualization and requires data to be already structured or imported. Option C (SQL database) is not the best tool for immediate exploration since it requires database setup and data import. Therefore, Python pandas is the most appropriate tool for initial exploration of CSV data.

Answer

Hadoop

Answer

Tableau

Answer

SQL database

Question 15

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