DP-900 Describe core data concepts Practice Question
A company collects data from multiple sources: IoT sensor streams, social media feeds, and CSV files from legacy systems. They want to store all this data in its original format without any transformation, so that data scientists can later apply machine learning models or run ad-hoc queries. Which data storage pattern best describes this approach?
⚠ Common exam trap
A common mix-up: candidates confuse a data lake with a data warehouse, assuming both are for analytics, but the key differentiator is that a data lake stores raw, unprocessed data while a data warehouse requires transformation and schema-on-write.
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 vast amounts of raw data in its native format (structured, semi-structured, or unstructured) without requiring upfront schema or transformation. This aligns perfectly with the scenario of ingesting IoT streams, social media feeds, and CSV files as-is, enabling data scientists to later apply machine learning or run ad-hoc queries directly against the raw data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Data warehouse
Why it's wrong here
A data warehouse stores data that has been extracted, transformed, and loaded (ETL), organizing it into structured star schemas for business intelligence and reporting. This schema-on-write approach requires defining the schema before loading, making it impossible to preserve raw data in its original form; instead, warehouse data is curated and aggregated to answer known analytical questions.
When this WOULD be correct
A company needs to store structured, cleansed, and integrated data from multiple operational systems for business intelligence reporting and historical analysis, where data is transformed and optimized for query performance.
- ✓
Data lake
Why this is correct
A data lake is a centralized repository that stores raw data in its native format, from IoT sensor streams to structured files, without requiring a predefined schema. It employs schema-on-read, so data scientists can explore and run ad-hoc analytics before defining structure. This makes it ideal for diverse, high-volume streaming data where format and meaning may evolve over time.
- ✗
Relational database
Why it's wrong here
A relational database enforces a rigid schema and ACID-compliant transactions, which are essential for OLTP applications like order processing but ill-suited for ingesting raw IoT streams. Storing unstructured or semi-structured sensor data would force a transformation into tables, losing fidelity and creating scalability bottlenecks for high-velocity, heterogeneous data.
- ✗
Data mart
Why it's wrong here
A data mart is a logically separated subset of a data warehouse, tailored to a single business unit or process, such as sales or finance. It typically contains aggregated and pre-transformed data, so it inherits the warehouse's schema-on-write constraints and cannot accommodate raw, unmodified IoT streams; its scope is too narrow and its data too curated for exploratory big data analytics.
When this WOULD be correct
A question that asks for a storage pattern optimized for a specific department's reporting needs, such as 'A sales team needs fast access to aggregated sales data from a data warehouse for quarterly reports.'
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The DP-900 exam frequently reuses these exact scenarios with slightly different constraints.
✓Data lakeCorrect answer▾
Why this is correct
A data lake is a centralized repository that stores raw data in its native format, from IoT sensor streams to structured files, without requiring a predefined schema. It employs schema-on-read, so data scientists can explore and run ad-hoc analytics before defining structure. This makes it ideal for diverse, high-volume streaming data where format and meaning may evolve over time.
✗Data warehouseWrong answer — click to see why▾
Why this is wrong here
A data warehouse requires schema-on-write and data transformation before loading, which contradicts the requirement to store data in its original format without transformation.
★ When this WOULD be the correct answer
A company needs to store structured, cleansed, and integrated data from multiple operational systems for business intelligence reporting and historical analysis, where data is transformed and optimized for query performance.
Why candidates choose this
Candidates may associate 'multiple data sources' with a data warehouse, which is commonly used for integrating data from various sources, but overlook the key requirement of storing data in its original format without transformation.
✗Data martWrong answer — click to see why▾
Why this is wrong here
A data mart is a subset of a data warehouse focused on a specific business function, not designed to store raw, untransformed data from diverse sources like IoT streams and social media feeds.
★ When this WOULD be the correct answer
A question that asks for a storage pattern optimized for a specific department's reporting needs, such as 'A sales team needs fast access to aggregated sales data from a data warehouse for quarterly reports.'
Why candidates choose this
Candidates may confuse 'data mart' with 'data lake' due to similar-sounding names, or think a data mart can handle raw data because it's a storage repository.
Analysis generated from the official DP-900blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data lake
A data lake is a centralized storage repository that holds vast amounts of raw data in its native format until it is needed for analysis.
Key term
Schema
A schema is a blueprint or logical structure that defines how data is organized, stored, and accessed in a database or information system.
About these practice questions
This DP-900 question is part of Courseiva's 820-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-900 exam.