AWS DATA ENGINEERING EXAM
2024/2025 WITH 100% ACCURATE
SOLUTIONS
A data scientist writes a program that applies rule-based logic to
customer profile data to determine which customers are likely to respond
to an advertisement. How would you categorize this type of analysis?
Machine teaming (ML)
Artificial intelligence (Al)
Traditional analytics
Preventive analytics - Precise Answer ✔✔Traditional analytics
(Data analytics relies on programming logic and tools to predictions
from data)
Which statement describes a key factor to design an effective decision-
making infrastructure?
The designer should focus on collecting data and building a pipeline that
can be used for all of the analytics in the organization.
The design should prevent data from being transformed as it moves
through the pipeline.
,The designer should start with the business problem to be solved and
then build the pipeline that suits that use case.
Every data pipeline should follow the same pattern of tasks and move
directly
from ingestion to storage to processing and then to analysis and
visualization, sequentially. - Precise Answer ✔✔The designer should
start with the business problem to be solved and then build the pipeline
that suits that use case.
(The key to designing an effective decision-making
infrastructure is to start with the business problem to be
solved.)
A customer wants to create a website that highlights cars only. Because
there are many different cars, the customer plans to train a model by
showing it numerous pictures that are labeled as cars and letting it learn
to identify unlabeled pictures as cars. Which data science approach
could accomplish this task?
Traditional analytics
Natural language processing
Historical analysis
Artificial intelligence and machine learning (AI/ML) - Precise Answer
✔✔Artificial intelligence and machine learning (AI/ML)
(AI/ML can leam to make predictions from examples in data.
, This approach is good for unstructured data and where the
variables are complex.)
Which statement accurately reflects how an organization should think
about using its data to make decisions?
An organization should always store as much data as possible to
maximize value.
A solution should never sacrifice accuracy for speed.
Data becomes more valuable for decision-making over time.
Preventive and predictive analytics promise the most value when
compared to other types of analytics. - Precise Answer ✔✔Preventive
and predictive analytics promise the most value when compared to other
types of analytics.
(Being able to predict something and take action before it
occurs provides the most potential value compared to other
types of analytics.)
Which statement best describes the data scientist role in processing data
through a
pipeline?
A data scientist works with data in the pipeline.
A data scientist focuses on the infrastructure that data passes through.
2024/2025 WITH 100% ACCURATE
SOLUTIONS
A data scientist writes a program that applies rule-based logic to
customer profile data to determine which customers are likely to respond
to an advertisement. How would you categorize this type of analysis?
Machine teaming (ML)
Artificial intelligence (Al)
Traditional analytics
Preventive analytics - Precise Answer ✔✔Traditional analytics
(Data analytics relies on programming logic and tools to predictions
from data)
Which statement describes a key factor to design an effective decision-
making infrastructure?
The designer should focus on collecting data and building a pipeline that
can be used for all of the analytics in the organization.
The design should prevent data from being transformed as it moves
through the pipeline.
,The designer should start with the business problem to be solved and
then build the pipeline that suits that use case.
Every data pipeline should follow the same pattern of tasks and move
directly
from ingestion to storage to processing and then to analysis and
visualization, sequentially. - Precise Answer ✔✔The designer should
start with the business problem to be solved and then build the pipeline
that suits that use case.
(The key to designing an effective decision-making
infrastructure is to start with the business problem to be
solved.)
A customer wants to create a website that highlights cars only. Because
there are many different cars, the customer plans to train a model by
showing it numerous pictures that are labeled as cars and letting it learn
to identify unlabeled pictures as cars. Which data science approach
could accomplish this task?
Traditional analytics
Natural language processing
Historical analysis
Artificial intelligence and machine learning (AI/ML) - Precise Answer
✔✔Artificial intelligence and machine learning (AI/ML)
(AI/ML can leam to make predictions from examples in data.
, This approach is good for unstructured data and where the
variables are complex.)
Which statement accurately reflects how an organization should think
about using its data to make decisions?
An organization should always store as much data as possible to
maximize value.
A solution should never sacrifice accuracy for speed.
Data becomes more valuable for decision-making over time.
Preventive and predictive analytics promise the most value when
compared to other types of analytics. - Precise Answer ✔✔Preventive
and predictive analytics promise the most value when compared to other
types of analytics.
(Being able to predict something and take action before it
occurs provides the most potential value compared to other
types of analytics.)
Which statement best describes the data scientist role in processing data
through a
pipeline?
A data scientist works with data in the pipeline.
A data scientist focuses on the infrastructure that data passes through.
