DA0-001 Comparing and Contrasting Data Concepts Practice Question
This DA0-001 practice question tests your understanding of comparing and contrasting data concepts. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which TWO of the following are characteristics of a data lake?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Retains raw data in native format
A data lake retains raw data in its native format, meaning data is ingested without transformation or schema enforcement. This allows storage of structured, semi-structured, and unstructured data as-is, preserving fidelity for future analytics. Unlike a data warehouse, a data lake does not require upfront schema definition, enabling flexible exploration and machine learning workloads.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Retains raw data in native format
Why this is correct
Data lakes store data as-is without transformation.
Related concept
Read the scenario before looking for a memorised answer.
✗
Optimized for OLTP
Why it's wrong here
OLTP is typical of relational databases, not data lakes.
✗
Stores only structured data
Why it's wrong here
Data lakes store all types of data: structured, semi-structured, unstructured.
✗
Enforces ACID transactions
Why it's wrong here
ACID is enforced by relational databases, not data lakes.
✓
Uses schema-on-read
Why this is correct
Data lakes apply schema when reading data, preserving flexibility.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse data lakes with data warehouses, assuming all enterprise data stores enforce ACID and schema-on-write, when in fact data lakes prioritize raw storage and schema flexibility.
Detailed technical explanation
How to think about this question
Schema-on-read means the schema is applied at query time, not at write time, allowing raw data to be stored in formats like Parquet, Avro, or ORC. Under the hood, this enables late-binding transformations where tools like Apache Spark or Presto interpret the data structure dynamically. A real-world scenario is ingesting IoT sensor streams in JSON format and later querying them with different schemas for anomaly detection versus trend analysis without reprocessing.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Comparing and Contrasting Data Concepts — This question tests Comparing and Contrasting Data Concepts — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Retains raw data in native format — A data lake retains raw data in its native format, meaning data is ingested without transformation or schema enforcement. This allows storage of structured, semi-structured, and unstructured data as-is, preserving fidelity for future analytics. Unlike a data warehouse, a data lake does not require upfront schema definition, enabling flexible exploration and machine learning workloads.
What should I do if I get this DA0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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