The modern data ecosystem encompasses collecting, storing, processing, and analyzing large volumes of data from various sources. Data engineering plays a crucial role in this ecosystem by designing and maintaining the infrastructure required to handle big data, creating data pipelines for efficient data flow, and ensuring data quality and reliability. Data engineers also build and optimize databases, data warehouses, and data lakes to support the organization's data analytics and machine learning initiatives.
Question 1
A modern data ecosystem includes a network of continually
evolving entities. It includes:
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Options:
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A. Data
providers, databases, and programming languages
B. Data
sources, enterprise data repository, business stakeholders, and tools,
applications, and infrastructure to manage data
C. Data
sources, databases, and programming languages
D. Social
media sources, data repositories, and APIs
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Question 2
Data Engineers work within the data ecosystem to:
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Options:
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A. Provide
business intelligence solutions by monitoring data on different business
functions
B. Analyze
data for actionable insights
C. Develop
and maintain data architectures
D. Analyze
data for deriving insights
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Question 3
The goal of data engineering is to make quality data
available for fact-finding and decision-making. Which one of these statements
captures the process of data engineering?
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Options:
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A. Collecting,
processing, and storing data
B. Collecting,
processing, and making data available to users securely
C. Processing
data and making it available to users securely
D. Collecting,
processing, storing, and making data available to users securely
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Question 4
Data extracted from disparate sources can be stored in:
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Options:
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A. Databases,
data warehouses, data lakes, or any other type of data repository
B. Data
Warehouses only
C. Databases
only
D. Data
Lakes only
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Question 5
From the provided list, select the three emerging
technologies that are shaping today’s data ecosystem.
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Options:
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A. Machine
Language, Cloud Computing, and Internet of Things
B. Big
Data, Internet of Things, and Dashboarding
C. Cloud
Computing, Machine Learning, and Big Data
D. Cloud
Computing, Internet of Things, and Dashboarding
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