1. Question 1

Data Marts and Warehouses were traditionally relational, but what enabled them to support non-relational data?

• ❌ Data Lake

• ❌ SQL

• ✅ NoSQL

• ❌ ETL

Explanation:
The rise of NoSQL technologies enabled handling semi-structured and unstructured data in modern data warehouses.

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2. Question 2

What is one of the most significant advantages of an RDBMS?

• ❌ Requires source and destination tables to be identical

• ❌ Can store only structured data

• ✅ Is ACID-Compliant

• ❌ Enforces a limit on the length of data fields

Explanation:
A major benefit of RDBMS systems is ACID compliance, ensuring reliable, consistent transactions.

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3. Question 3

Which NoSQL database type uses a graphical model to analyze relationships?

• ✅ Graph-based

• ❌ Key value store

• ❌ Column-based

• ❌ Document-based

Explanation:
Graph databases (e.g., Neo4j) store nodes and relationships, ideal for network and relationship analysis.

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4. Question 4

Which repository stores large amounts of raw structured, semi-structured, and unstructured data?

• ❌ Relational Databases

• ✅ Data Lakes

• ❌ Data Marts

• ❌ Data Warehouses

Explanation:
Data Lakes store raw data in native formats without predefined schemas.

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5. Question 5

What does “Veracity” mean in Big Data?

• ❌ Diversity of type and sources

• ✅ Accuracy and conformity of data to facts

• ❌ The speed of data

• ❌ Scale of data

Explanation:
Veracity measures trustworthiness, quality, and accuracy of data.

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6. Question 6

One key use case of Apache Spark:

• ❌ Consolidate data across the organization

• ❌ Fast recovery from failures

• ✅ Perform complex analytics in real-time

• ❌ Scalable and reliable Big Data storage

Explanation:
Apache Spark is optimized for in-memory processing, enabling real-time and complex analytics at scale.

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🧾 Summary Table

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