DA0-001 · topic practice

Comparing and Contrasting Data Concepts practice questions

Practise CompTIA Data+ DA0-001 Comparing and Contrasting Data Concepts practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Reviewed byJohnson Ajibi· MSc IT Security
20 questionsDomain: Comparing and Contrasting Data Concepts

What the exam tests

What to know about Comparing and Contrasting Data Concepts

Comparing and Contrasting Data Concepts questions test whether you can apply the concept in context, not just recognise a definition.

How the topic appears in realistic exam-style scenarios.

Which detail in the question changes the correct answer.

How to eliminate plausible but wrong options.

How to connect the question back to the wider exam objective.

Watch out for

Common Comparing and Contrasting Data Concepts exam traps

  • Answering from memory before reading the full scenario.
  • Missing a constraint such as cost, availability, security, scope or command context.
  • Choosing a broad answer when the question asks for the most specific fix.
  • Ignoring why the wrong options are tempting.

Practice set

Comparing and Contrasting Data Concepts questions

20 questions · select your answer, then reveal the explanation

A retail company stores customer purchase history in a relational database. The database contains a table 'transactions' with columns: transaction_id, customer_id, product_id, quantity, price, and transaction_date. A data analyst needs to create a report that shows total revenue per customer for the last quarter. Which data concept describes the relationship between customer_id and total revenue?

Question 2easymultiple choice
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A healthcare database stores patient records. Each patient has a unique patient_id, and the database includes a table 'visits' with visit_id, patient_id, visit_date, and diagnosis_code. To ensure data integrity, which constraint should be applied to the patient_id column in the 'visits' table?

Question 3hardmultiple choice
Read the full NAT/PAT explanation →

A data engineer is designing a data warehouse for a multinational corporation. The company has sales data from different regions with varying currencies and date formats. To ensure consistency, which data concept should be applied to standardize the data before loading into the warehouse?

An e-commerce company uses a star schema for its data warehouse. The fact table 'sales_fact' contains foreign keys to dimension tables: customer_dim, product_dim, time_dim, and store_dim. A business user wants to know the total sales for each product category in the last month. Which join operation is required to retrieve this data?

A data analyst is working with a dataset containing customer information. The dataset includes a column 'full_name' which stores first and last names together. To perform analysis on first names separately, which data concept describes the process of splitting 'full_name' into 'first_name' and 'last_name'?

A data scientist is building a machine learning model to predict customer churn. The dataset includes both numerical features (age, income) and categorical features (gender, marital status). Which data concept describes the process of converting categorical features into numerical values that can be used by the algorithm?

A company's database has a table 'orders' with columns: order_id, customer_id, order_date, and total_amount. A data analyst needs to identify customers who have placed more than 5 orders in the past year. Which data concept should be used to group orders by customer and count them?

A data analyst receives a dataset with a column 'salary' that contains values like '45,000', '55,000', and '65,000'. The analyst notices that the values are stored as text. Which data concept should be applied to convert the salary column from text to numeric format for analysis?

Which TWO of the following are characteristics of structured data? (Choose TWO.)

Which THREE of the following are valid data quality dimensions? (Choose THREE.)

Which TWO of the following are examples of data transformation? (Choose TWO.)

A financial services company is migrating its customer data from a legacy on-premises relational database to a cloud-based data warehouse. The legacy database uses a denormalized schema with a single table 'customer_master' that contains all customer attributes, including repeated groups for multiple accounts per customer (account1_type, account1_balance, account2_type, account2_balance, etc.). The data warehouse team wants to implement a normalized star schema with separate dimension and fact tables. During the ETL process, the team encounters an error: 'Data truncation: string data right truncation' when loading account_type values into the dim_account table. The account_type column in dim_account is defined as VARCHAR(10), but the source data contains account types like 'SavingsPlus' (11 characters) and 'CheckingPremium' (15 characters). The team must resolve this issue without losing data. Which course of action should the team take?

Question 13mediummultiple choice
Read the full NAT/PAT explanation →

A healthcare organization maintains a database of patient records. The database has a table 'patients' with columns: patient_id (primary key), first_name, last_name, date_of_birth, gender, and last_visit_date. A data analyst is tasked with creating a report that lists all patients who have not visited in the last two years. The analyst writes a query: SELECT * FROM patients WHERE last_visit_date < DATEADD(year, -2, GETDATE()); However, the query returns zero rows, even though the analyst knows there are patients who have not visited for over two years. Upon inspection, the analyst discovers that the last_visit_date column contains NULL values for patients who have never visited. Which modification to the query should the analyst make to include patients with NULL last_visit_date?

A data analyst needs to ensure that a customer's address is stored in a consistent format across multiple databases. Which data quality dimension is the analyst primarily concerned with?

A data engineer is designing a data warehouse for a retail company. The fact table must record each sale transaction, including product ID, store ID, date, and quantity sold. The product details (name, category, price) are stored in a separate table. This design is an example of which data modeling concept?

A data analyst is troubleshooting a report that shows unusually high sales for a specific product. Upon investigation, the analyst finds that the product was returned by several customers, but the returns were recorded in a separate system and not reflected in the sales data. Which data integration concept was likely missing?

When the analyst runs the query, it fails. What is the most likely reason?

Network Topology
+Refer to the exhibit.FROM ProductsWHERE TotalValue > 2000

A data analyst is reviewing the error log from a nightly batch load. What is the most likely cause of the error?

Exhibit

Refer to the exhibit.

Error log from a data pipeline:

[2025-03-15 10:32:14] ERROR: Duplicate key value violates unique constraint 'order_pkey'
[2025-03-15 10:32:14] Detail: Key (order_id)=(12345) already exists.
[2025-03-15 10:32:15] WARNING: Batch load incomplete. 4999 of 5000 rows inserted.

A data analyst is creating a report for a marketing campaign. The campaign data includes customer names, email addresses, and purchase history. Which of the following best describes the 'customer name' data type?

Which TWO of the following are considered structured data?

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Frequently asked questions

What does the DA0-001 exam test about Comparing and Contrasting Data Concepts?
Comparing and Contrasting Data Concepts questions test whether you can apply the concept in context, not just recognise a definition.
How should I use these practice questions?
Select your answer before revealing the explanation. Then read why each option is right or wrong — this active recall approach builds retention far faster than re-reading notes.
Can I practise just Comparing and Contrasting Data Concepts questions in a focused session?
Yes — the session launcher on this page draws every question from the Comparing and Contrasting Data Concepts domain. Use a 10-question session first to gauge your baseline, then move to 20 or 30 once the weak spots are clear.
Where can I practise other DA0-001 topics?
Use the topic links above to move to related areas, or go back to the DA0-001 question bank to see all topics.
Are these real exam questions or dumps?
These are original practice questions written to test the same concepts the DA0-001 exam covers. They are not copied from any real exam or dump site.