Module 2: ETL Pipeline and Database Foundations

Looking for ‘Data Analytics and Databases on AWS Module 2 Answers‘?

In this post, I provide accurate answers and detailed explanations for Module 2: ETL Pipeline and Database Foundations of Course 8: Data Analytics and Databases on AWS  Software Development – AWS Cloud Technology Consultant Professional Certificate

Whether you’re preparing for quizzes or brushing up on your knowledge, these insights will help you master the concepts effectively. Let’s dive into the correct answers and detailed explanations for each question.

Module 2 Quiz

Graded Assignment

1. The four characteristics of big data are volume, velocity, variety, and veracity. What does the term velocity refer to in the context of data analysis?

  • It describes the different
  • types of data sources.
  • It relates to the size of the dataset.
  • It defines the speed at which data is generated, collected, and processed. ✅
  • It means the level of accuracy and reliability of the data.

Explanation:
 In big data, velocity refers to the rapid pace at which data is created, transmitted, and analyzed. For example, streaming data from social media, IoT devices, or financial markets arrives quickly and must be handled in near real-time.

2. True or False:

NoSQL databases are the preferred choice for companies that handle highly structured datasets with fixed schemas.

  • True
  • False ✅

Explanation:
NoSQL databases are ideal for unstructured or semi-structured data and for situations where the schema is flexible or evolving. If the data is highly structured and schema is fixed, then relational (SQL) databases are the preferred choice.

3. A cloud consultant works for a company that uses a SQL database to store data. The consultant needs to retrieve specific information from the table. Which SQL command should the cloud consultant use to retrieve the data?

  • DROP
  • CREATE
  • SELECT ✅
  • INSERT

Explanation:
The SELECT command is used in SQL to retrieve data from a table. It allows querying specific columns and applying filters to get the exact information needed.

Related contents:

Module 1: Foundations of Data Analysis
Module 3: AWS Services for ETL

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