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Amazon Web Services Data-Engineer-Associate Dumps Questions Answers

Exam Code:
Data-Engineer-Associate
Last Update: Nov 15, 2024
130 Questions Answers with Explanation Detail
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Data-Engineer-Associate Q&A's Detail

Exam Code:
Data-Engineer-Associate
Total Questions:
130 Q&A's
Single Choice Questions:
106 Q&A's
Multiple Choice Questions:
24 Q&A's

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AWS Certified Data Engineer - Associate (DEA-C01) Questions and Answers

Questions 1

An airline company is collecting metrics about flight activities for analytics. The company is conducting a proof of concept (POC) test to show how analytics can provide insights that the company can use to increase on-time departures.

The POC test uses objects in Amazon S3 that contain the metrics in .csv format. The POC test uses Amazon Athena to query the data. The data is partitioned in the S3 bucket by date.

As the amount of data increases, the company wants to optimize the storage solution to improve query performance.

Which combination of solutions will meet these requirements? (Choose two.)

Options:

A.

Add a randomized string to the beginning of the keys in Amazon S3 to get more throughput across partitions.

B.

Use an S3 bucket that is in the same account that uses Athena to query the data.

C.

Use an S3 bucket that is in the same AWS Region where the company runs Athena queries.

D.

Preprocess the .csv data to JSON format by fetching only the document keys that the query requires.

E.

Preprocess the .csv data to Apache Parquet format by fetching only the data blocks that are needed for predicates.

Questions 2

A company receives .csv files that contain physical address data. The data is in columns that have the following names: Door_No, Street_Name, City, and Zip_Code. The company wants to create a single column to store these values in the following format:

Data-Engineer-Associate Question 2

Which solution will meet this requirement with the LEAST coding effort?

Options:

A.

Use AWS Glue DataBrew to read the files. Use the NEST TO ARRAY transformation to create the new column.

B.

Use AWS Glue DataBrew to read the files. Use the NEST TO MAP transformation to create the new column.

C.

Use AWS Glue DataBrew to read the files. Use the PIVOT transformation to create the new column.

D.

Write a Lambda function in Python to read the files. Use the Python data dictionary type to create the new column.

Questions 3

A company uses Amazon S3 as a data lake. The company sets up a data warehouse by using a multi-node Amazon Redshift cluster. The company organizes the data files in the data lake based on the data source of each data file.

The company loads all the data files into one table in the Redshift cluster by using a separate COPY command for each data file location. This approach takes a long time to load all the data files into the table. The company must increase the speed of the data ingestion. The company does not want to increase the cost of the process.

Which solution will meet these requirements?

Options:

A.

Use a provisioned Amazon EMR cluster to copy all the data files into one folder. Use a COPY command to load the data into Amazon Redshift.

B.

Load all the data files in parallel into Amazon Aurora. Run an AWS Glue job to load the data into Amazon Redshift.

C.

Use an AWS Glue job to copy all the data files into one folder. Use a COPY command to load the data into Amazon Redshift.

D.

Create a manifest file that contains the data file locations. Use a COPY command to load the data into Amazon Redshift.

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