BTW, DOWNLOAD part of DumpsQuestion Data-Engineer-Associate dumps from Cloud Storage: https://drive.google.com/open?id=1vypJnXuBSUYxFGRmj-rdcdwrCQs3ABbX
APP test engine of Amazon Data-Engineer-Associate exam is popular with at least 60% candidates since all most certification candidates are fashion and easy to adapt to this new studying method. Someone thinks that APP test engine of Data-Engineer-Associate exam is convenient to use any time anywhere. Also part of candidates thinks that this version can simulate the real scene with the real test. If you can open the browser you can learn. Also if you want to learn offline, you should not clear the cache after downloading and installing the APP test engine of Data-Engineer-Associate Exam.
| Section | Weight | Objectives |
|---|---|---|
| Data Operations and Support | 22% | - Troubleshoot data workflow issues - Monitor and maintain data pipelines |
| Data Security and Governance | 18% | - Apply governance and compliance best practices - Implement data security controls |
| Data Store Management | 26% | - Select appropriate data storage solutions - Optimize storage performance and cost |
| Data Ingestion and Transformation | 34% | - Ingest and transform data using AWS services - Build and manage data pipelines |
>> Latest Data-Engineer-Associate Demo <<
Free renewal of our Data-Engineer-Associate study prep in this respect is undoubtedly a large shining point. Apart from the advantage of free renewal in one year, our Data-Engineer-Associate exam engine offers you constant discounts so that you can save a large amount of money concerning buying our Data-Engineer-Associate Training Materials. And we give these discount from time to time, so you should come and buy Data-Engineer-Associate learning guide more and you will get more rewards accordingly.
NEW QUESTION # 144
A telecommunications company collects network usage data throughout each day at a rate of several thousand data points each second. The company runs an application to process the usage data in real time. The company aggregates and stores the data in an Amazon Aurora DB instance.
Sudden drops in network usage usually indicate a network outage. The company must be able to identify sudden drops in network usage so the company can take immediate remedial actions.
Which solution will meet this requirement with the LEAST latency?
Answer: A
Explanation:
The telecommunications company needs a low-latency solution to detect sudden drops in network usage from real-time data collected throughout the day.
Option B: Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (Amazon Kinesis Data Analytics) application to detect drops in network usage.
Using Amazon Kinesis with Managed Service for Apache Flink (formerly Kinesis Data Analytics) is ideal for real-time stream processing with minimal latency. Flink can analyze the incoming data stream in real-time and detect anomalies, such as sudden drops in usage, which makes it the best fit for this scenario.
Other options (A, C, and D) either introduce unnecessary delays (e.g., querying databases) or do not provide the same real-time, low-latency processing that is critical for this use case.
Reference:
Amazon Kinesis Data Analytics for Apache Flink
Amazon Kinesis Documentation
NEW QUESTION # 145
A data engineer must manage the ingestion of real-time streaming data into AWS. The data engineer wants to perform real-time analytics on the incoming streaming data by using time-based aggregations over a window of up to 30 minutes. The data engineer needs a solution that is highly fault tolerant.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: D
Explanation:
This solution meets the requirements of managing the ingestion of real-time streaming data into AWS and performing real-time analytics on the incoming streaming data with the least operational overhead. Amazon Managed Service for Apache Flink is a fully managed service that allows you to run Apache Flink applications without having to manage any infrastructure or clusters. Apache Flink is a framework for stateful stream processing that supports various types of aggregations, such as tumbling, sliding, and session windows, over streaming data. By using Amazon Managed Service for Apache Flink, you can easily connect to Amazon Kinesis Data Streams as the source and sink of your streaming data, and perform time-based analytics over a window of up to 30 minutes. This solution is also highly fault tolerant, as Amazon Managed Service for Apache Flink automatically scales, monitors, and restarts your Flink applications in case of failures. References:
* Amazon Managed Service for Apache Flink
* Apache Flink
* Window Aggregations in Flink
NEW QUESTION # 146
A company maintains multiple extract, transform, and load (ETL) workflows that ingest data from the company's operational databases into an Amazon S3 based data lake. The ETL workflows use AWS Glue and Amazon EMR to process data.
The company wants to improve the existing architecture to provide automated orchestration and to require minimal manual effort.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: A
Explanation:
AWS Glue workflows are a feature of AWS Glue that enable you to create and visualize complex ETL pipelines using AWS Glue components, such as crawlers, jobs, triggers, and development endpoints. AWS Glue workflows provide automated orchestration and require minimal manual effort, as they handle dependency resolution, error handling, state management, and resource allocation for your ETL workflows.
You can use AWS Glue workflows to ingest data from your operational databases into your Amazon S3 based data lake, and then use AWS Glue and Amazon EMR to process the data in the data lake. This solution will meet the requirements with the least operational overhead, as it leverages the serverless and fully managed nature of AWS Glue, and the scalability and flexibility of Amazon EMR12.
The other options are not optimal for the following reasons:
* B. AWS Step Functions tasks. AWS Step Functions is a service that lets you coordinate multiple AWS services into serverless workflows. You can use AWS Step Functions tasks to invoke AWS Glue and Amazon EMR jobs as part of your ETL workflows, and use AWS Step Functions state machines to define the logic and flow of your workflows. However, this option would require more manual effort than AWS Glue workflows, as you would need to write JSON code to define your state machines, handle errors and retries, and monitor the execution history and status of your workflows3.
* C. AWS Lambda functions. AWS Lambda is a service that lets you run code without provisioning or managing servers. You can use AWS Lambda functions to trigger AWS Glue and Amazon EMR jobs as part of your ETL workflows, and use AWS Lambda event sources and destinations to orchestrate the flow of your workflows. However, this option would also require more manual effort than AWS Glue workflows, as you would need to write code to implement your business logic, handle errors and retries, and monitor the invocation and execution of your Lambda functions. Moreover, AWS Lambda functions have limitations on the execution time, memory, and concurrency, which may affect the performance and scalability of your ETL workflows.
* D. Amazon Managed Workflows for Apache Airflow (Amazon MWAA) workflows. Amazon MWAA is a managed service that makes it easy to run open source Apache Airflow on AWS. Apache Airflow is a popular tool for creating and managing complex ETL pipelines using directed acyclic graphs (DAGs).
You can use Amazon MWAA workflows to orchestrate AWS Glue and Amazon EMR jobs as part of your ETL workflows, and use the Airflow web interface to visualize and monitor your workflows.
However, this option would have more operational overhead than AWS Glue workflows, as you would need to set up and configure your Amazon MWAA environment, write Python code to define your DAGs, and manage the dependencies and versions of your Airflow plugins and operators.
1: AWS Glue Workflows
2: AWS Glue and Amazon EMR
3: AWS Step Functions
4: AWS Lambda
5: Amazon Managed Workflows for Apache Airflow
NEW QUESTION # 147
The company stores a large volume of customer records in Amazon S3. To comply with regulations, the company must be able to access new customer records immediately for the first 30 days after the records are created. The company accesses records that are older than 30 days infrequently.
The company needs to cost-optimize its Amazon S3 storage.
Which solution will meet these requirements MOST cost-effectively?
Answer: D
Explanation:
The most cost-effective solution in this case is to apply a lifecycle policy to transition records to Amazon S3 Standard-IA storage after 30 days. Here's why:
* Amazon S3 Lifecycle Policies: Amazon S3 offers lifecycle policies that allow you to automatically transition objects between different storage classes to optimize costs. For data that is frequently accessed in the first 30 days and infrequently accessed after that, transitioning from the S3 Standard storage class to S3 Standard-Infrequent Access (S3 Standard-IA) after 30 days makes the most sense. S3 Standard-IA is designed for data that is accessed less frequently but still needs to be retained, offering lower storage costs than S3 Standard with a retrieval cost for access.
* Cost Optimization: S3 Standard-IA offers a lower price per GB than S3 Standard. Since the data will be accessed infrequently after 30 days, using S3 Standard-IA will lower storage costs while still allowing for immediate retrieval when necessary.
* Compliance with Regulations: Since the records need to be immediately accessible for the first 30 days, the use of S3 Standard for that period ensures compliance with regulatory requirements. After 30 days, transitioning to S3 Standard-IA continues to meet access requirements for infrequent access while reducing storage costs.
* Alternatives Considered:
* Option B (S3 Intelligent-Tiering): While S3 Intelligent-Tiering automatically moves data between access tiers based on access patterns, it incurs a small monthly monitoring and automation charge per object. It could be a viable option, but transitioning data to S3 Standard- IA directly would be more cost-effective since the pattern of access is well-known (frequent for
30 days, infrequent thereafter).
* Option C (S3 Glacier Deep Archive): Glacier Deep Archive is the lowest-cost storage class, but it is not suitable in this case because the data needs to be accessed immediately within 30 days and on an infrequent basis thereafter. Glacier Deep Archive requires hours for data retrieval, which is not acceptable for infrequent access needs.
* Option D (S3 Standard-IA for all records): Using S3 Standard-IA for all records would result in higher costs for the first 30 days, as the data is frequently accessed. S3 Standard-IA incurs retrieval charges, making it less suitable for frequently accessed data.
:
Amazon S3 Lifecycle Policies
S3 Storage Classes
Cost Management and Data Optimization Using Lifecycle Policies
AWS Data Engineering Documentation
NEW QUESTION # 148
A company uses Amazon S3 buckets, AWS Glue tables, and Amazon Athena as components of a data lake. Recently, the company expanded its sales range to multiple new states. The company wants to introduce state names as a new partition to the existing S3 bucket, which is currently partitioned by date.
The company needs to ensure that additional partitions will not disrupt daily synchronization between the AWS Glue Data Catalog and the S3 buckets.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: A
Explanation:
Scheduling an AWS Glue crawler to periodically update the Data Catalog automates the process of detecting new partitions and updating the catalog, which minimizes manual maintenance and operational overhead.
NEW QUESTION # 149
......
The Amazon Data-Engineer-Associate exam practice questions are being offered in three different formats. These formats are Amazon Data-Engineer-Associate web-based practice test software, desktop practice test software, and PDF dumps files. All these three Amazon Data-Engineer-Associate exam questions format are important and play a crucial role in your AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam preparation. With the Amazon Data-Engineer-Associate exam questions you will get updated and error-free AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam questions all the time. In this way, you cannot miss a single DumpsQuestion Amazon Data-Engineer-Associate exam question without an answer.
Sample Data-Engineer-Associate Questions: https://www.dumpsquestion.com/Data-Engineer-Associate-exam-dumps-collection.html
DOWNLOAD the newest DumpsQuestion Data-Engineer-Associate PDF dumps from Cloud Storage for free: https://drive.google.com/open?id=1vypJnXuBSUYxFGRmj-rdcdwrCQs3ABbX