Data Engineering Program Quiz 7

Data Engineering Quiz 7

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1. What is the primary role of a data engineer when integrating data with BI tools like Tableau and Power BI?

Writing machine learning models for predictive analysis

Creating optimized data pipelines for efficient querying

Replacing traditional databases with NoSQL solutions

Designing dashboards for business users

2. Which data storage solution is best suited for enabling real-time analytics with streaming data?

PostgreSQL

Amazon S3

Apache Kafka

Google BigQuery

3. When working with scalable data architectures, what is the main advantage of using a data lake?

It stores both structured and unstructured data efficiently

It speeds up all SQL query executions

It eliminates the need for schema definition

It ensures data is always structured and pre-processed

4. In a real-time data pipeline, what is the function of Apache Flink?

Real-time stream processing

Storing transactional data in relational databases

Automating ETL workflows

Data ingestion for batch processing

5. What is the key benefit of using a columnar storage format like Parquet in a BI workflow?

Faster reads for analytical queries

Improved performance for transactional workloads

Lower storage costs due to text compression

Real-time data synchronization

6. What is an effective way to scale a data pipeline for high-volume real-time analytics?

Running SQL queries directly on raw streaming data

Storing all data in a single on-premises server

Increasing the number of relational database indexes

Using a distributed message broker like Apache Kafka

7. Which BI tool allows direct connection to streaming data sources for real-time visualization?

Tableau

Apache Superset

Google Looker

Power BI

8. When architecting a scalable data system, what role does partitioning play?

Distributes data across multiple storage locations for parallel processing

Slows down data ingestion to avoid overload

Ensures that only structured data is stored

Reduces query performance in distributed systems

9. How does a change data capture (CDC) mechanism help in real-time data integration?

Creates full backups of the entire database

Converts unstructured data into structured formats

Tracks and propagates only changes in source data

Aggregates data before inserting it into a warehouse

10. What is a common challenge in scaling a data architecture for large-scale analytics?

Storing only structured data in the system

Managing high availability and consistency

Avoiding all forms of schema evolution

Ensuring all queries execute sequentially

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Data Engineering Program Quiz 7

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