Data Processing Data Processing MCQ 4 — Questions and Answers
Question 1: What is 'data enrichment' in the context of data processing?
- Compressing raw data to save storage space
- Enhancing existing data by appending additional relevant information from external sources (Correct answer)
- Removing null values from a dataset
- Encrypting data fields before storage
Correct answer: Enhancing existing data by appending additional relevant information from external sources
Data enrichment augments a dataset by adding context or supplementary data from external sources, increasing its analytical value.
Question 2: Which concept describes the ability of a data processing system to handle increasing workloads by adding more machines rather than upgrading existing ones?
- Vertical scaling
- Horizontal scaling (Correct answer)
- Load balancing
- Data sharding
Correct answer: Horizontal scaling
Horizontal scaling (scaling out) adds more nodes to a distributed system, while vertical scaling upgrades the capacity of existing machines.
Question 3: What is 'late-arriving data' a challenge in stream processing?
- Data that is encrypted and cannot be decoded in real time
- Events that arrive after the time window in which they should have been processed (Correct answer)
- Data records that exceed the maximum size limit
- Duplicate messages sent multiple times by producers
Correct answer: Events that arrive after the time window in which they should have been processed
Late-arriving data occurs when events reach the processing system after their event-time window has already closed, complicating aggregations.
Question 4: In columnar storage formats like Apache Parquet, what is the primary performance advantage over row-based storage?
- Columnar formats support more data types than row-based formats
- Columnar formats allow faster reads of specific columns without scanning entire rows (Correct answer)
- Columnar formats use stronger encryption algorithms
- Columnar formats require less processing power to write data
Correct answer: Columnar formats allow faster reads of specific columns without scanning entire rows
Columnar storage reads only the queried columns from disk, drastically reducing I/O for analytical queries that access a few columns from wide tables.
Question 5: What is the primary purpose of a 'data catalog' in an enterprise data environment?
- To automatically clean and validate incoming datasets
- To provide a searchable inventory of available data assets with metadata and lineage information (Correct answer)
- To enforce row-level security policies on databases
- To compress and archive historical data
Correct answer: To provide a searchable inventory of available data assets with metadata and lineage information
A data catalog acts as a centralized registry where users can discover, understand, and govern available data assets across the organization.
Question 6: Which technique splits a large database table into smaller segments stored across different servers to improve query performance?
- Indexing
- Replication
- Sharding (partitioning) (Correct answer)
- Caching
Correct answer: Sharding (partitioning)
Sharding distributes rows of a table across multiple servers based on a shard key, enabling parallel processing and reducing per-server load.
Question 7: What does 'idempotency' mean in the context of data processing pipelines?
- Processing data at the fastest possible speed
- Ensuring that applying the same operation multiple times produces the same result as applying it once (Correct answer)
- Encrypting data at rest and in transit simultaneously
- Synchronizing data between primary and replica databases
Correct answer: Ensuring that applying the same operation multiple times produces the same result as applying it once
An idempotent operation produces the same result regardless of how many times it is applied, preventing data duplication during retries.
Data Processing Data Processing MCQ 4
What is 'data enrichment' in the context of data processing?