DOWNLOAD the newest Getcertkey Data-Engineer-Associate PDF dumps from Cloud Storage for free: https://drive.google.com/open?id=1JyF5o2jc8fs-Zzrqgcj8Xi29jOo-joqd
With Data-Engineer-Associate study tool, you are not like the students who use other materials. As long as the syllabus has changed, they need to repurchase learning materials. This not only wastes a lot of money, but also wastes a lot of time. Our industry experts are constantly adding new content to Data-Engineer-Associate exam torrent based on constantly changing syllabus and industry development breakthroughs. We also hire dedicated staff to continuously update our question bank daily, so no matter when you buy Data-Engineer-Associate Guide Torrent, what you learn is the most advanced. Even if you fail to pass the exam, as long as you are willing to continue to use our Data-Engineer-Associate study tool, we will still provide you with the benefits of free updates within a year.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Operations and Support | 22% | - Ensure reliability and scalability - Automate operational tasks - Monitor and troubleshoot data pipelines
|
| Topic 2: Data Security and Governance | 18% | - Enforce compliance and data governance
- Implement access control and authentication
|
| Topic 3: Data Ingestion and Transformation | 34% | - Transform and enrich data
- Ingest data from various sources
|
| Topic 4: Data Store Management | 26% | - Design and implement data storage solutions
- Optimize storage performance and cost |
>> Exam Data-Engineer-Associate Fees <<
Getcertkey actual Data-Engineer-Associate exam questions in PDF format are ideal for individuals who prefer to study on their tablets, laptops, and smartphones. Since these Data-Engineer-Associate exam questions can be studied from any place at any time, making this format a perfect alternative for candidates who are frequently on the move and want to prepare for the exam in a short time. Questions in the Amazon Data-Engineer-Associate Pdf Format are printable, allowing you to prepare for the Data-Engineer-Associate test via hard copy. Our Amazon Data-Engineer-Associate PDF version is regularly updated to improve the Data-Engineer-Associate exam questions based on the Data-Engineer-Associate real certification test’s content.
NEW QUESTION # 88
A company runs concurrent analytical queries on Amazon Redshift tables multiple times each day. The queries require consistent data views three times each day. The company runs extract, transform, and load (ETL) operations that update dimension tables while the queries run. The company has noticed that the queries cause table-level locks during the ETL operations. The company ' s current solution experiences query timeouts and deadlocks during peak processing hours, which affects analytical reporting and on-demand analysis.
Which solution will fix this issue?
Answer: A
Explanation:
Option D is correct because the problem is lock contention between ETL writes and analytical reads on the same Redshift tables. AWS documents that table locks can block both reads and writes, and that Redshift data sharing lets you share live data across Redshift clusters and workgroups without manually moving or copying the data. Because the shared data is live, consumer users see the most up-to-date information as soon as it is updated. Separating ETL and analytics onto different Redshift clusters while using data sharing is therefore the cleanest way to isolate workloads and still provide consistent data views.
Option A reduces contention only by changing schedules and does not fully solve concurrent peak-hour conflicts. Option B is not correct because Redshift federated queries are read-only against external sources and do not provide a Redshift "read replica" design for this case. Option C does not address the locking problem on the dimension tables that ETL is updating. The official Redshift guidance and service capabilities point to workload isolation plus data sharing as the best fix. This also matches the exam guide's emphasis on choosing architectures that maintain performance and consistency without unnecessary copying.
NEW QUESTION # 89
A data engineer needs to build a data pipeline to process medical records from 50 hospitals. The pipeline must ingest 5 GB of data from each hospital and remove personally identifiable information (PII). The pipeline must then transform the data and save the data in a central store. The pipeline must automatically retry after transient failures without manual intervention.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: D
Explanation:
The correct answer is A because the pipeline requires scalable ingestion, PII removal, ETL transformation, centralized storage, and automatic retry handling. Amazon S3 is the correct landing and central storage layer for large hospital data files. AWS Glue ETL is appropriate for managed data transformation at this scale, and AWS Glue DataBrew is the best fit among the options for low-code data preparation and PII handling. Step Functions is the correct orchestration service because it supports retry policies for task states, parallel states, and map states without manual intervention. EC2 custom scripts and AWS Batch add more operational work. Lambda is not suitable for 5 GB per hospital with heavier transformation steps. Therefore, S3, Glue, DataBrew, and Step Functions is the least-operational-overhead design.
NEW QUESTION # 90
A company is planning to upgrade its Amazon Elastic Block Store (Amazon EBS) General Purpose SSD storage from gp2 to gp3. The company wants to prevent any interruptions in its Amazon EC2 instances that will cause data loss during the migration to the upgraded storage.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: C
Explanation:
Changing the volume type of the existing gp2 volumes to gp3 is the easiest and fastest way to migrate to the new storage type without any downtime or data loss. You can use the AWS Management Console, the AWS CLI, or the Amazon EC2 API to modify the volume type, size, IOPS, and throughput of your gp2 volumes.
The modification takes effect immediately, and you can monitor the progress of the modification using CloudWatch. The other options are either more complex or require additional steps, such as creating snapshots, transferring data, or attaching new volumes, which can increase the operational overhead and the risk of errors. References:
Migrating Amazon EBS volumes from gp2 to gp3 and save up to 20% on costs (Section: How to migrate from gp2 to gp3) Switching from gp2 Volumes to gp3 Volumes to Lower AWS EBS Costs (Section: How to Switch from GP2 Volumes to GP3 Volumes) Modifying the volume type, IOPS, or size of an EBS volume - Amazon Elastic Compute Cloud (Section: Modifying the volume type)
NEW QUESTION # 91
A company created an extract, transform, and load (ETL) data pipeline in AWS Glue. A data engineer must crawl a table that is in Microsoft SQL Server. The data engineer needs to extract, transform, and load the output of the crawl to an Amazon S3 bucket. The data engineer also must orchestrate the data pipeline.
Which AWS service or feature will meet these requirements MOST cost-effectively?
Answer: A
Explanation:
AWS Glue workflows are a cost-effective way to orchestrate complex ETL jobs that involve multiple crawlers, jobs, and triggers. AWS Glue workflows allow you to visually monitor the progress and dependencies of your ETL tasks, and automatically handle errors and retries. AWS Glue workflows also integrate with other AWS services, such as Amazon S3, Amazon Redshift, and AWS Lambda, among others, enabling you to leverage these services for your data processing workflows. AWS Glue workflows are serverless, meaning you only pay for the resources you use, and you don't have to manage any infrastructure.
AWS Step Functions, AWS Glue Studio, and Amazon MWAA are also possible options for orchestrating ETL pipelines, but they have some drawbacks compared to AWS Glue workflows. AWS Step Functions is a serverless function orchestrator that can handle different types of data processing, such as real-time, batch, and stream processing. However, AWS Step Functions requires you to write code to define your state machines, which can be complex and error-prone. AWS Step Functions also charges you for every state transition, which can add up quickly for large-scale ETL pipelines.
AWS Glue Studio is a graphical interface that allows you to create and run AWS Glue ETL jobs without writing code. AWS Glue Studio simplifies the process of building, debugging, and monitoring your ETL jobs, and provides a range of pre-built transformations and connectors. However, AWS Glue Studio does not support workflows, meaning you cannot orchestrate multiple ETL jobs or crawlers with dependencies and triggers. AWS Glue Studio also does not support streaming data sources or targets, which limits its use cases for real-time data processing.
Amazon MWAA is a fully managed service that makes it easy to run open-source versions of Apache Airflow on AWS and build workflows to run your ETL jobs and data pipelines. Amazon MWAA provides a familiar and flexible environment for data engineers who are familiar with Apache Airflow, and integrates with a range of AWS services such as Amazon EMR, AWS Glue, and AWS Step Functions. However, Amazon MWAA is not serverless, meaning you have to provision and pay for the resources you need, regardless of your usage. Amazon MWAA also requires you to write code to define your DAGs, which can be challenging and time-consuming for complex ETL pipelines. References:
* AWS Glue Workflows
* AWS Step Functions
* AWS Glue Studio
* Amazon MWAA
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide
NEW QUESTION # 92
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.)
Answer: A,B
Explanation:
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
NEW QUESTION # 93
......
Our Data-Engineer-Associate learning guide allows you to study anytime, anywhere. If you are concerned that your study time cannot be guaranteed, then our Data-Engineer-Associate learning guide is your best choice because it allows you to learn from time to time and make full use of all the time available for learning. Our Data-Engineer-Associate learning guide is for the world and users are very extensive. In order to give users a better experience, we have been constantly improving. The high quality and efficiency of Data-Engineer-Associate Test Guide has been recognized by users. The high passing rate of Data-Engineer-Associate exam training is its biggest feature. As long as you use Data-Engineer-Associate test guide, you can certainly harvest what you want thing.
Data-Engineer-Associate Sample Exam: https://www.getcertkey.com/Data-Engineer-Associate_braindumps.html
BTW, DOWNLOAD part of Getcertkey Data-Engineer-Associate dumps from Cloud Storage: https://drive.google.com/open?id=1JyF5o2jc8fs-Zzrqgcj8Xi29jOo-joqd