Data-Engineer-Associate Trainingsunterlagen, Data-Engineer-Associate Probesfragen

Außerdem sind jetzt einige Teile dieser PrüfungFrage Data-Engineer-Associate Prüfungsfragen kostenlos erhältlich: https://drive.google.com/open?id=1Ip0P5XEjw2Y436hsA07n6bgWfiGp6lEm

Mit der Ankunft der Informationsepoche im 21. Jahrhunderts wird das Amazon Data-Engineer-Associate Zertifikat auch unerlässlich in der IT-Branche. Ob Sie ein Anfänger oder ein Pendler sind, können Sie Ihre erwünschte Ergebnisse nur mit Häflte der Bemühungen von anderen erzeilen, denn es gibt bei PrüfungFrage für Sie maßgeschneidete Fragenkataloge zur Amazon Data-Engineer-Associate Zertifizierungsprüfung. PrüfungFrage wird Ihnen begleiten, für den Traum zu kämpfen. Worauf warten Sie noch?

Amazon Data-Engineer-Associate Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Security and Governance18%- Implement access control and authentication
  • 1. IAM, Lake Formation, resource policies
- Encrypt data at rest and in transit
- Protect sensitive data
- Enforce compliance and data governance
  • 1. Data lineage, audit logging, regulatory requirements
Topic 2: Data Store Management26%- Design and implement data storage solutions
  • 1. Data lakes, data warehouses, databases
  • 2. S3, Redshift, DynamoDB, RDS, Lake Formation
- Optimize storage performance and cost
- Manage data lifecycle and storage tiers
Topic 3: Data Operations and Support22%- Automate operational tasks
- Backup, restore, and disaster recovery
- Ensure reliability and scalability
- Monitor and troubleshoot data pipelines
  • 1. CloudWatch, X-Ray, logging and metrics
Topic 4: Data Ingestion and Transformation34%- Ingest data from various sources
  • 1. Batch and streaming data ingestion
  • 2. Use services like Kinesis, DMS, Glue, S3
- Implement data quality and validation
- Transform and enrich data
  • 1. Use Spark, EMR, Step Functions
  • 2. Apply data processing logic
  • 3. Orchestrate data pipelines

>> Data-Engineer-Associate Trainingsunterlagen <<

Data-Engineer-Associate aktueller Test, Test VCE-Dumps für AWS Certified Data Engineer - Associate (DEA-C01)

Egal wie anziehend die Werbung ist, ist nicht so überzeugend wie Ihre eigene Erfahrung. Auf unserer Webseite können Sie die Demo der Amazon Data-Engineer-Associate Prüfungssoftware kostenlos herunterladen. Wir glauben, solange Sie diese Software, die vielen Leuten bei der Amazon Data-Engineer-Associate geholfen hat, probiert haben, werden Sie diese Software sofort mögen. Benutzen Sie unsere Produkte! Sie können auch ein IT-Spezialist mit Amazon Data-Engineer-Associate Prüfungszeugnis werden!

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate Prüfungsfragen mit Lösungen (Q145-Q150):

145. Frage
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:

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

Antwort: D

Begründung:
The NEST TO MAP transformation allows you to combine multiple columns into a single column that contains a JSON object with key-value pairs. This is the easiest way to achieve the desired format for the physical address data, as you can simply select the columns to nest and specify the keys for each column. The NEST TO ARRAY transformation creates a single column that contains an array of values, which is not the same as the JSON object format. The PIVOT transformation reshapes the data by creating new columns from unique values in a selected column, which is not applicable for this use case. Writing a Lambda function in Python requires more coding effort than using AWS Glue DataBrew, which provides a visual and interactive interface for data transformations. References:
7 most common data preparation transformations in AWS Glue DataBrew (Section: Nesting and unnesting columns) NEST TO MAP - AWS Glue DataBrew (Section: Syntax)


146. Frage
A data engineer must use AWS services to ingest a dataset into an Amazon S3 data lake. The data engineer profiles the dataset and discovers that the dataset contains personally identifiable information (PII). The data engineer must implement a solution to profile the dataset and obfuscate the PII.
Which solution will meet this requirement with the LEAST operational effort?

Antwort: C

Begründung:
AWS Glue is a fully managed service that provides a serverless data integration platform for data preparation, data cataloging, and data loading. AWS Glue Studio is a graphical interface that allows you to easily author, run, and monitor AWS Glue ETL jobs. AWS Glue Data Quality is a feature that enables you to validate, cleanse, and enrich your data using predefined or custom rules. AWS Step Functions is a service that allows you to coordinate multiple AWS services into serverless workflows.
Using the Detect PII transform in AWS Glue Studio, you can automatically identify and label the PII in your dataset, such as names, addresses, phone numbers, email addresses, etc. You can then create a rule in AWS Glue Data Quality to obfuscate the PII, such as masking, hashing, or replacing the values with dummy data. You can also use other rules to validate and cleanse your data, such as checking for null values, duplicates, outliers, etc. You can then use an AWS Step Functions state machine to orchestrate a data pipeline to ingest the data into the S3 data lake. You can use AWS Glue DataBrew to visually explore and transform the data, AWS Glue crawlers to discover and catalog the data, and AWS Glue jobs to load the data into the S3 data lake.
This solution will meet the requirement with the least operational effort, as it leverages the serverless and managed capabilities of AWS Glue, AWS Glue Studio, AWS Glue Data Quality, and AWS Step Functions. You do not need to write any code to identify or obfuscate the PII, as you can use the built-in transforms and rules in AWS Glue Studio and AWS Glue Data Quality. You also do not need to provision or manage any servers or clusters, as AWS Glue and AWS Step Functions scale automatically based on the demand.
The other options are not as efficient as using the Detect PII transform in AWS Glue Studio, creating a rule in AWS Glue Data Quality, and using an AWS Step Functions state machine. Using an Amazon Kinesis Data Firehose delivery stream to process the dataset, creating an AWS Lambda transform function to identify the PII, using an AWS SDK to obfuscate the PII, and setting the S3 data lake as the target for the delivery stream will require more operational effort, as you will need to write and maintain code to identify and obfuscate the PII, as well as manage the Lambda function and its resources. Using the Detect PII transform in AWS Glue Studio to identify the PII, obfuscating the PII, and using an AWS Step Functions state machine to orchestrate a data pipeline to ingest the data into the S3 data lake will not be as effective as creating a rule in AWS Glue Data Quality to obfuscate the PII, as you will need to manually obfuscate the PII after identifying it, which can be error-prone and time-consuming. Ingesting the dataset into Amazon DynamoDB, creating an AWS Lambda function to identify and obfuscate the PII in the DynamoDB table and to transform the data, and using the same Lambda function to ingest the data into the S3 data lake will require more operational effort, as you will need to write and maintain code to identify and obfuscate the PII, as well as manage the Lambda function and its resources. You will also incur additional costs and complexity by using DynamoDB as an intermediate data store, which may not be necessary for your use case. Reference:
AWS Glue
AWS Glue Studio
AWS Glue Data Quality
[AWS Step Functions]
[AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide], Chapter 6: Data Integration and Transformation, Section 6.1: AWS Glue


147. Frage
A company stores customer data in an Amazon S3 bucket. The company must permanently delete all customer data that is older than 7 years.

Antwort: A

Begründung:
S3 Lifecycle policies automate data retention and deletion. By specifying an expiration rule for 7 years, objects older than that period are permanently deleted without manual intervention.
"To automatically delete aged data, configure an S3 Lifecycle rule with an expiration policy for objects older than the retention period."
- Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf


148. Frage
A data engineer must orchestrate a series of Amazon Athena queries that will run every day. Each query can run for more than 15 minutes.
Which combination of steps will meet these requirements MOST cost-effectively? (Choose two.)

Antwort: C,D

Begründung:
Option A and B are the correct answers because they meet the requirements most cost-effectively. Using an AWS Lambda function and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically is a simple and scalable way to orchestrate the queries. Creating an AWS Step Functions workflow and adding two states to check the query status and invoke the next query is a reliable and efficient way to handle the long-running queries.
Option C is incorrect because using an AWS Glue Python shell job to invoke the Athena queries programmatically is more expensive than using a Lambda function, as it requires provisioning and running a Glue job for each query.
Option D is incorrect because using an AWS Glue Python shell script to run a sleep timer that checks every 5 minutes to determine whether the current Athena query has finished running successfully is not a cost- effective or reliable way to orchestrate the queries, as it wastes resources and time.
Option E is incorrect because using Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the Athena queries in AWS Batch is an overkill solution that introduces unnecessary complexity and cost, as it requires setting up and managing an Airflow environment and an AWS Batch compute environment.
:
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 5: Data Orchestration, Section 5.2: AWS Lambda, Section 5.3: AWS Step Functions, Pages 125-135 Building Batch Data Analytics Solutions on AWS, Module 5: Data Orchestration, Lesson 5.1: AWS Lambda, Lesson 5.2: AWS Step Functions, Pages 1-15 AWS Documentation Overview, AWS Lambda Developer Guide, Working with AWS Lambda Functions, Configuring Function Triggers, Using AWS Lambda with Amazon Athena, Pages 1-4 AWS Documentation Overview, AWS Step Functions Developer Guide, Getting Started, Tutorial: Create a Hello World Workflow, Pages 1-8


149. Frage
A company is migrating on-premises workloads to AWS. The company wants to reduce overall operational overhead. The company also wants to explore serverless options.
The company's current workloads use Apache Pig, Apache Oozie, Apache Spark, Apache Hbase, and Apache Flink. The on-premises workloads process petabytes of data in seconds. The company must maintain similar or better performance after the migration to AWS.
Which extract, transform, and load (ETL) service will meet these requirements?

Antwort: D

Begründung:
AWS Glue is a fully managed serverless ETL service that can handle petabytes of data in seconds. AWS Glue can run Apache Spark and Apache Flink jobs without requiring any infrastructure provisioning or management. AWS Glue can also integrate with Apache Pig, Apache Oozie, and Apache Hbase using AWS Glue Data Catalog and AWS Glue workflows. AWS Glue can reduce the overall operational overhead by automating the data discovery, data preparation, and data loading processes. AWS Glue can also optimize the cost and performance of ETL jobs by using AWS Glue Job Bookmarking, AWS Glue Crawlers, and AWS Glue Schema Registry. Reference:
AWS Glue
AWS Glue Data Catalog
AWS Glue Workflows
[AWS Glue Job Bookmarking]
[AWS Glue Crawlers]
[AWS Glue Schema Registry]
[AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide]


150. Frage
......

Wenn Sie die Schulungsunterlagen zur Amazon Data-Engineer-Associate Zertifizierungsprüfung haben, dann werden Sie sicherlich erfolgreich sein. Nachdem Sie unsere Lehrbücher gekauft haben,werden Sie einjährige Aktualisierung kostenlos genießen. Die Bestehensrate von Amazon Data-Engineer-Associate ist 100%. Wenn Sie die Zertifizierungsprüfung nicht bestehen oder die Schulungsunterlagen zur Amazon Data-Engineer-Associate Zertifizierungsprüfung irgend ein Problem haben, geben wir Ihnen eine bedingungslose volle Rückerstattung.

Data-Engineer-Associate Probesfragen: https://www.pruefungfrage.de/Data-Engineer-Associate-dumps-deutsch.html

Außerdem sind jetzt einige Teile dieser PrüfungFrage Data-Engineer-Associate Prüfungsfragen kostenlos erhältlich: https://drive.google.com/open?id=1Ip0P5XEjw2Y436hsA07n6bgWfiGp6lEm