A data analyst has monthly sales data for January, February, and March, each with the same columns. They want to create a single dataset containing all rows. Which aggregation technique is most appropriate?

Merging the datasets on a common key

Joining the datasets on an index

Concatenating the datasets vertically

A company needs to store data for both real-time operational queries and long-term historical analysis. The operational data is structured and requires low-latency access, while the historical data is large and used for batch analytics. The budget is limited. Which storage architecture is most appropriate?

Use a data lake for both operational and historical data

Use a NoSQL database for both operational and historical data

Use a single data warehouse for both operational and historical data

Use a relational database for operational data and a data lake for historical data

A market research firm is studying consumer preferences for a new product. They have a limited budget and need results within two weeks. They have access to a large customer database from a previous study (secondary data) and can also conduct a new survey (primary data). Which approach is most appropriate?

Conduct both a survey and focus groups to maximize data quality

Use secondary data first, then supplement with a small survey if needed

Use the existing secondary data from the previous study

Conduct a new survey to collect fresh, specific data

Python InstitutePCAD - Certified Associate in Data Analytics with Python

Domain 1Objective 1

Data Collection, Integration, and Storage PCAD-31 Practice Questions (Page 4)

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 16–20

16foundation · easy
A data analyst has monthly sales data for January, February, and March, each with the same columns. They want to create a single dataset containing all rows. Which aggregation technique is most appropriate?
Select an answer first
17expert · hard
A company needs to store data for both real-time operational queries and long-term historical analysis. The operational data is structured and requires low-latency access, while the historical data is large and used for batch analytics. The budget is limited. Which storage architecture is most appropriate?
Select an answer first
18expert · hard
A market research firm is studying consumer preferences for a new product. They have a limited budget and need results within two weeks. They have access to a large customer database from a previous study (secondary data) and can also conduct a new survey (primary data). Which approach is most appropriate?
Select an answer first
19foundation · easy
An organization wants to store massive amounts of raw data in its native format for future analysis, without a predefined schema. Which storage solution is most appropriate?
Select an answer first
20foundation · easy
A retail company wants to analyze customer satisfaction by directly asking a sample of its customers to complete a survey. Which type of data collection method is being used?
Select an answer first

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Data Collection, Integration, and Storage PCAD-31 Practice Questions (Page 4)

Questions 16–20

A data analyst has monthly sales data for January, February, and March, each with the same columns. They want to create a single dataset containing all rows. Which aggregation technique is most appropriate?

An organization wants to store massive amounts of raw data in its native format for future analysis, without a predefined schema. Which storage solution is most appropriate?

A retail company wants to analyze customer satisfaction by directly asking a sample of its customers to complete a survey. Which type of data collection method is being used?

Keep studying — Data Acquisition and Pre-Processing