Data and Analytics Big Data and Cloud Analytics 2 — Questions and Answers
Question 1: What is Google BigQuery's primary architectural advantage?
- On-premise storage for security
- Serverless, scalable analytics separating storage from compute (Correct answer)
- Native integration with Excel
- Built-in machine learning only
Correct answer: Serverless, scalable analytics separating storage from compute
BigQuery's serverless architecture separates storage from compute, allowing independent scaling and eliminating infrastructure management.
Question 2: What is Apache Kafka primarily used for?
- Batch processing historical data
- Real-time data streaming and event-driven pipelines (Correct answer)
- Relational data storage
- Data visualization
Correct answer: Real-time data streaming and event-driven pipelines
Apache Kafka is a distributed event streaming platform used for high-throughput, real-time data pipelines and stream processing.
Question 3: What is the purpose of a CDN (Content Delivery Network) in analytics applications?
- To store analytical models
- To reduce latency by caching content closer to users geographically (Correct answer)
- To process big data queries
- To encrypt data at rest
Correct answer: To reduce latency by caching content closer to users geographically
A CDN distributes cached content across geographically dispersed servers to reduce latency and improve load times for end users.
Question 4: What does 'schema-on-read' mean in the context of data lakes?
- Data schema is enforced when data is written
- Schema is applied when data is queried, not when it's stored (Correct answer)
- All data must follow a predefined schema
- Schema validation happens at the database layer
Correct answer: Schema is applied when data is queried, not when it's stored
Schema-on-read means raw data is stored without a fixed structure, and the schema is applied dynamically when the data is queried.
Question 5: What is Snowflake's multi-cluster, shared data architecture?
- Multiple databases sharing one compute cluster
- Separate storage and compute layers allowing multiple independent query engines (Correct answer)
- A peer-to-peer distributed computing model
- A single cluster serving all workloads
Correct answer: Separate storage and compute layers allowing multiple independent query engines
Snowflake separates storage from compute, allowing multiple virtual warehouses to independently access the same data without contention.
Question 6: What is the purpose of data partitioning in big data systems?
- To encrypt sensitive data
- To divide large datasets into smaller chunks for faster parallel processing (Correct answer)
- To replicate data across regions
- To compress data for storage efficiency
Correct answer: To divide large datasets into smaller chunks for faster parallel processing
Partitioning divides data into smaller, manageable chunks that can be processed in parallel across multiple nodes, improving query performance.
Data and Analytics Big Data and Cloud Analytics 2
What is Google BigQuery's primary architectural advantage?