Data Engineering

What is the role of a data engineer?

• Uses stats and ML to generate predictions

• Creating mobile applications

• Building and optimizing systems for data scientists and analysts

• Deliver value and communicate results, helping make business decisions

Which skillset is essential for data engineering?

• SQL

• Software Development and UI/UX

• Machine Learning

• Programming Language

What is the purpose of data engineering?

• To make business decisions

• To make predictions based on data

• To generate insights on data

• To improve data quality and consistency

How does data engineering contribute to business success?

• By organizing company events

• By improving data quality and accessibility

• By easing dataflow

• By designing product

How does data engineering differ from data science?

• Data engineering focuses on building and optimizing data systems, while data science focuses on analyzing and interpreting data

• Data engineering involves creating visualizations, while data science involves data cleaning

• Data engineering is only concerned with structured data, while data science deals with unstructured data

• Data engineering is a subset of data science

Why is data engineering important in the era of big data?

• To increase the number of social media followers

• To ensure data security and privacy

• To handle the volume, velocity, and variety of data

• To create engaging content for marketing purposes

What is the primary focus of data engineering?

• Building and optimizing data systems

• Creating visualizations

• Analyzing and interpreting data

• Developing machine learning models

How does data engineering support data science?

• By generating insights on data

• By handling the volume, velocity, and variety of data

• By creating engaging content for marketing purposes

• By improving data quality and consistency

Which of the following Azure services is not used for Data Engineering?

• Azure Synapse Analytics

• Azure MLOps

• Azure Stream Analytics

• Azure Data Factory

Which of the following is a part of the Data Engineering process?

• Data Cleaning

• Deployment

• Data Transformation

• All of the Above