A retail chain wants to understand why customers abandon their online shopping carts. They have historical transaction logs (internal data) and industry benchmarks (external data). They need to collect direct feedback from customers who abandoned carts in the last week. Which data collection method should they use?

Conduct a survey of customers who abandoned carts in the last week

Compare industry benchmarks to identify common abandonment causes

Use a web analytics tool to track clickstream data

Analyze the historical transaction logs to identify patterns

An analyst is integrating sales data from two regions. In the North region, `revenue` is stored in USD, while in the South region, it is stored in EUR. After merging, the total revenue is incorrect. What is the best way to address this data conflict?

Use the average of the two currencies as a compromise

Convert all revenue values to a common currency before merging

Drop the revenue column and use only order counts

Merge the data and then convert the combined column to USD

A startup needs to store user-generated content (posts, comments, likes) for a social media app. The data is semi-structured, with varying fields per post, and the workload is read-heavy with high write throughput. The team expects rapid growth and needs horizontal scalability. Which storage solution is most appropriate?

Data warehouse (e.g., Snowflake)

Relational database (e.g., PostgreSQL)

NoSQL document database (e.g., MongoDB)

An analyst is merging customer data from two systems. In the CRM, customer IDs are integers (e.g., 12345), but in the billing system, the same IDs are stored as strings with leading zeros (e.g., '012345'). After merging on the customer ID column, many customers appear as separate rows. What is the most likely cause?

Schema mismatch: the customer ID columns have different data types

Missing values: some customer IDs are null

Duplicate rows: the same customer appears multiple times in one system

Data conflict: the customer names are spelled differently

Python InstitutePCAD - Certified Associate in Data Analytics with Python

Domain 1Objective 1

Data Collection, Integration, and Storage PCAD-31 Practice Questions (Page 5)

Part of the Data Acquisition and Pre-Processing domain, which accounts for 29.2% of the PCAD-31 exam. Python Institute does not publish an official question count, but from its 60-minute exam (~25–40 total, ~7–7 in this domain), expect 2–2 from this objective — we provide 25 practice questions to prepare you well beyond it. (estimate)

25questions here

5free pages

6concepts

29.2%of the exam

Questions 21–25

21application · medium
A retail chain wants to understand why customers abandon their online shopping carts. They have historical transaction logs (internal data) and industry benchmarks (external data). They need to collect direct feedback from customers who abandoned carts in the last week. Which data collection method should they use?
Select an answer first
22application · medium
An analyst is integrating sales data from two regions. In the North region, `revenue` is stored in USD, while in the South region, it is stored in EUR. After merging, the total revenue is incorrect. What is the best way to address this data conflict?
Select an answer first
23application · medium
A startup needs to store user-generated content (posts, comments, likes) for a social media app. The data is semi-structured, with varying fields per post, and the workload is read-heavy with high write throughput. The team expects rapid growth and needs horizontal scalability. Which storage solution is most appropriate?
Select an answer first
24application · medium
An analyst is merging customer data from two systems. In the CRM, customer IDs are integers (e.g., 12345), but in the billing system, the same IDs are stored as strings with leading zeros (e.g., '012345'). After merging on the customer ID column, many customers appear as separate rows. What is the most likely cause?
Select an answer first
25foundation · easy
During data integration, an analyst notices that some records in the combined dataset have empty fields for 'age'. What challenge are they encountering?
Select an answer first

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Data Collection, Integration, and Storage PCAD-31 Practice Questions (Page 5)

Questions 21–25

An analyst is integrating sales data from two regions. In the North region, `revenue` is stored in USD, while in the South region, it is stored in EUR. After merging, the total revenue is incorrect. What is the best way to address this data conflict?

During data integration, an analyst notices that some records in the combined dataset have empty fields for 'age'. What challenge are they encountering?

Keep studying — Data Acquisition and Pre-Processing