When is ELT better than ETL?

• With cloud data warehouses

• With on-premise databases

• When transforming before loading

• When no transformation is needed

What is a common issue when handling large-scale distributed data?

• High network latency

• Lack of storage space

• Excessive manual data entry

• Too many relational tables

What is a primary goal of data normalization?

• Increase storage usage

• Reduce redundancy

• Speed up queries

• Remove all primary keys

Which data processing model is best for handling large-scale batch data?

• Event-driven

• Lambda

• OLAP

• OLTP

Which tool is commonly used for building ETL pipelines?

• Apache Kafka

• Apache Airflow

• Elasticsearch

• Apache NIFI

What is the main drawback of data denormalization?

• Increased redundancy

• Slower queries

• More complex joins

• Loss of integrity

Which SQL technique improves query performance on large tables?

• Joins

• Indexing

• Normalization

• CTEs

What is a key benefit of a data catalog?

• Improves query speed

• Stores raw data

• Tracks metadata and lineage

• Automates ETL jobs

Which architecture best supports decentralized data ownership?

• OLAP

• Data Lake

• Data Mesh

• Data Warehouse

What is the main trade-off when using materialized views?

• Faster reads, but higher storage cost

• Slower reads, but less storage usage

• Requires primary keys

• Reduces data redundanc