DA0-002 Data Concepts and Environments Practice Question
A business needs to store large volumes of raw data in its native format for future analytics. Which storage architecture is most appropriate?
⚠ Common exam trap
Many candidates confuse a data warehouse with a data lake, assuming both are for analytics, but the key differentiator is that a data warehouse requires schema-on-write and processed data, while a data lake stores raw data in native format.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Data lake
A data lake is designed to store large volumes of raw data in its native format (structured, semi-structured, or unstructured) without requiring a predefined schema. This makes it ideal for future analytics where the data schema may not yet be known, as it supports schema-on-read rather than schema-on-write.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Relational database
Why it's wrong here
Relational databases require a schema and are not designed for raw, unstructured data.
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Data lake
Why this is correct
Data lakes store raw data in its native format without transformation.
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Operational data store
Why it's wrong here
An operational data store is for current operational data, not large volumes of raw data.
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Data warehouse
Why it's wrong here
Data warehouses store structured, transformed data optimized for querying, not raw data.
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