Eladio Rocha
Quiz by , created 18 days ago

This quiz covers the core concepts of data lakes and their implementation in big data systems, with a focus on AWS tools like S3, Glue, Athena, and Redshift Spectrum. It explores how to structure, query, and optimize data in distributed file storage systems, emphasizing practical design considerations and performance optimization strategies.

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Eladio Rocha
Created by Eladio Rocha 18 days ago
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Data Lakes and Big Data Systems

Data Lakes and Big Data Systems

Question 1 of 9

1

What is a "data lake"?

Select one of the following:

  • A formal database for structured data.

  • A distributed file storage system containing raw, unstructured data.

  • A highly redundant server-based database system.

  • A collection of relational database schemas.

Explanation

Question 2 of 9

1

Which cloud service is commonly used to implement a data lake?

Select one of the following:

  • Amazon RDS

  • Amazon S3

  • Amazon DynamoDB

  • Amazon EC2

Explanation

Question 3 of 9

1

What is the primary purpose of AWS Glue in the context of a data lake?

Select one of the following:

  • To store data redundantly across regions.

  • To provide a SQL interface for querying raw data.

  • To crawl unstructured data and define schemas.

  • To optimize database queries for performance.

Explanation

Question 4 of 9

1

What tool allows SQL queries directly on data stored in Amazon S3?

Select one of the following:

  • Amazon DynamoDB

  • Amazon Athena

  • Amazon ElasticSearch

  • Amazon Lambda

Explanation

Question 5 of 9

1

How does Redshift Spectrum enhance the capabilities of Amazon Redshift?

Select one of the following:

  • By integrating with Amazon Glue to create schemas.

  • By querying data stored directly in Amazon S3.

  • By offering serverless SQL querying capabilities.

  • By storing all data in highly redundant clusters.

Explanation

Question 6 of 9

1

Why is partitioning data important in a data lake?

Select one of the following:

  • To replicate data across regions for redundancy.

  • To organize raw files into predefined schemas.

  • To improve query performance by narrowing data access.

  • To ensure compatibility with Amazon Glue.

Explanation

Question 7 of 9

1

What is a typical partitioning strategy for storing log data?

Select one of the following:

  • Partitioning by file size.

  • Partitioning by data source.

  • Partitioning by date.

  • Partitioning by user ID.

Explanation

Question 8 of 9

1

How should you approach data lake architecture from a system design perspective?

Select one of the following:

  • Design the data lake structure based on how end-users will query the data.

  • Store all data in a single bucket without structure to maximize flexibility.

  • Focus exclusively on schema design before considering query patterns.

  • Prioritize database migration over partitioning strategies.

Explanation

Question 9 of 9

1

What is one advantage of using off-the-shelf tools like AWS Glue and Amazon Athena?

Select one of the following:

  • They allow complete control over low-level data management.

  • They eliminate the need to think about data structure.

  • They enable scalable and reliable big data solutions with minimal custom design.

  • They prevent redundancy in cloud storage systems.

Explanation

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