Data Engineering Program Quiz 3

Data Engineering Quiz 3

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1. What is the primary function of an ETL pipeline?

To visualize data in real time

To extract, transform, and load data into a target system

To store raw data in its original format

To replace the need for data warehouses

2. In ETL processes, what is the main purpose of data transformation?

To replicate the data across multiple databases for redundancy

To improve data quality, enforce consistency, and format data for analysis

To extract relevant insights directly from the data

To move data between systems without modifying it

3. Which of the following is a common challenge when extracting data from various sources?

Differences in data formats and schemas across systems

Inability to perform data transformations

Lack of cloud storage integration

Incompatibility with relational databases

4. What is the main advantage of using an ELT (Extract, Load, Transform) pipeline over ETL?

Transformation occurs before loading, making processing faster

It avoids the need for a data warehouse

It ensures better data consistency across sources

It allows for better scalability and parallel processing in modern cloud-based warehouses

5. Which technique is commonly used for data cleansing in ETL pipelines?

Removing duplicate records and handling missing values

Encrypting sensitive information to improve security

Adding random noise to datasets to improve variance

Compressing large datasets for storage efficiency

6. Which of the following is a key characteristic of a data warehouse?

Optimized for transactional processing (OLTP)

Uses a schema-less data model for flexible storage

Designed for real-time data updates and modifications

Optimized for analytical queries and reporting (OLAP)

7. How does database sharding improve system performance?

By replicating the entire database across multiple nodes

By centralizing all data processing in a single high-performance node

By splitting a large database into smaller, distributed partitions

By converting relational data into NoSQL formats

8. In a star schema data warehouse model, what is the role of dimension tables?

To store large amounts of raw data in an unstructured format

To handle high-speed data ingestion from multiple sources

To contain descriptive attributes that provide context to fact tables

To act as a primary source of real-time transactional data

9. Which of the following is a major drawback of database sharding?

Reduced storage efficiency due to data normalization

The inability to scale horizontally

The complexity of managing distributed data and ensuring consistency

Increased query performance for large datasets

10. Which data warehouse architecture uses independent storage and compute resources for better scalability?

Shared-disk architecture

Traditional on-premises data warehouses

Centralized monolithic databases

Cloud-based modern data warehouses with a decoupled architecture

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Data Engineering Program Quiz 3

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