Greg Green Greg Green's Profile Page

Greg Green Greg Green

0 Course Enrolled • 0 Course Completed

Biography

Data-Engineer-Associate Pass4sure Dumps Pdf - Data-Engineer-Associate Exam Discount

Choosing our Data-Engineer-Associate exam quiz will be a wise decision that you make, because this decision may have a great impact in your future development. Having the certificate may be something you have always dreamed of, because it can prove that you have certain strength. Our Data-Engineer-Associate exam questions can provide you with services with pretty quality and help you obtain a certificate. Our Data-Engineer-Associate Learning Materials are made after many years of practical efforts and their quality can withstand the test of practice. And you will obtain the Data-Engineer-Associate certification just for our Data-Engineer-Associate study guide.

Keeping in view, the time constraints of professionals, our experts have devised Data-Engineer-Associate dumps PDF that suits your timetable and meets your exam requirements adequately. It is immensely helpful in enhancing your professional skills and expanding your exposure within a few-day times. This AWS Certified Data Engineer brain dumps exam testing tool introduces you not only with the actual exam paper formation but also allows you to master various significant segments of the Data-Engineer-Associate syllabus.

>> Data-Engineer-Associate Pass4sure Dumps Pdf <<

Download BraindumpStudy Data-Engineer-Associate Exam Real Questions and Start Preparation Today

Have you thought of how to easily pass Amazon Data-Engineer-Associate test? Have you found the trick? If you don't know what to do, I'll help you. In actual, there are many methods to sail through Data-Engineer-Associate exam. One is to learn exam related knowledge Data-Engineer-Associate certification test demands. Are you doing like this？However the above method is the worst time-waster and you cannot get the desired effect. Busying at work, you might have not too much time on preparing for Data-Engineer-Associate Certification test. Try BraindumpStudy Amazon Data-Engineer-Associate exam dumps. BraindumpStudy dumps can absolutely let you get an unexpected effect.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q62-Q67):

NEW QUESTION # 62
A data engineer uses Amazon Redshift to run resource-intensive analytics processes once every month. Every month, the data engineer creates a new Redshift provisioned cluster. The data engineer deletes the Redshift provisioned cluster after the analytics processes are complete every month. Before the data engineer deletes the cluster each month, the data engineer unloads backup data from the cluster to an Amazon S3 bucket.
The data engineer needs a solution to run the monthly analytics processes that does not require the data engineer to manage the infrastructure manually.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use AWS CloudFormation templates to automatically process the analytics workload.
B. Use Amazon Step Functions to pause the Redshift cluster when the analytics processes are complete and to resume the cluster to run new processes every month.
C. Use Amazon Redshift Serverless to automatically process the analytics workload.
D. Use the AWS CLI to automatically process the analytics workload.

Answer: C

Explanation:
Amazon Redshift Serverless is a new feature of Amazon Redshift that enables you to run SQL queries on data in Amazon S3 without provisioning or managing any clusters. You can use Amazon Redshift Serverless to automatically process the analytics workload, as it scales up and down the compute resources based on the query demand, and charges you only for the resources consumed. This solution will meet the requirements with the least operational overhead, as it does not require the data engineer to create, delete, pause, or resume any Redshift clusters, or to manage any infrastructure manually. You can use the Amazon Redshift Data API to run queries from the AWS CLI, AWS SDK, or AWS Lambda functions12.
The other options are not optimal for the following reasons:
* A. Use Amazon Step Functions to pause the Redshift cluster when the analytics processes are complete and to resume the cluster to run new processes every month. This option is not recommended, as it would still require the data engineer to create and delete a new Redshift provisioned cluster every month, which can incur additional costs and time. Moreover, this option would require the data engineer to use Amazon Step Functions to orchestrate the workflow of pausing and resuming the cluster, which can add complexity and overhead.
* C. Use the AWS CLI to automatically process the analytics workload. This option is vague and does not specify how the AWS CLI is used to process the analytics workload. The AWS CLI can be used to run queries on data in Amazon S3 using Amazon Redshift Serverless, Amazon Athena, or Amazon EMR, but each of these services has different features and benefits. Moreover, this option does not address the requirement of not managing the infrastructure manually, as the data engineer may still need to provision and configure some resources, such as Amazon EMR clusters or Amazon Athena workgroups.
* D. Use AWS CloudFormation templates to automatically process the analytics workload. This option is also vague and does not specify how AWS CloudFormation templates are used to process the analytics workload. AWS CloudFormation is a service that lets you model and provision AWS resources using templates. You can use AWS CloudFormation templates to create and delete a Redshift provisioned cluster every month, or to create and configure other AWS resources, such as Amazon EMR, Amazon Athena, or Amazon Redshift Serverless. However, this option does not address the requirement of not managing the infrastructure manually, as the data engineer may still need to write and maintain the AWS CloudFormation templates, and to monitor the status and performance of the resources.
:
1: Amazon Redshift Serverless
2: Amazon Redshift Data API
3: Amazon Step Functions
4: AWS CLI
5: AWS CloudFormation

NEW QUESTION # 63
A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.
Which actions will provide the FASTEST queries? (Choose two.)

A. Use a columnar storage file format.
B. Use file formats that are not
C. Partition the data based on the most common query predicates.
D. Split the data into files that are less than 10 KB.
E. Use gzip compression to compress individual files to sizes that are between 1 GB and 5 GB.

Answer: A,C

Explanation:
Amazon Redshift Spectrum is a feature that allows you to run SQL queries directly against data in Amazon S3, without loading or transforming the data. Redshift Spectrum can query various data formats, such as CSV, JSON, ORC, Avro, and Parquet. However, not all data formats are equally efficient for querying. Some data formats, such as CSV and JSON, are row-oriented, meaning that they store data as a sequence of records, each with the same fields. Row-oriented formats are suitable for loading and exporting data, but they are not optimal for analytical queries that often access only a subset of columns. Row-oriented formats also do not support compression or encoding techniques that can reduce the data size and improve the query performance.
On the other hand, some data formats, such as ORC and Parquet, are column-oriented, meaning that they store data as a collection of columns, each with a specific data type. Column-oriented formats are ideal for analytical queries that often filter, aggregate, or join data by columns. Column-oriented formats also support compression and encoding techniques that can reduce the data size and improve the query performance. For example, Parquet supports dictionary encoding, which replaces repeated values with numeric codes, and run-length encoding, which replaces consecutive identical values with a single value and a count. Parquet also supports various compression algorithms, such as Snappy, GZIP, and ZSTD, that can further reduce the data size and improve the query performance.
Therefore, using a columnar storage file format, such as Parquet, will provide faster queries, as it allows Redshift Spectrum to scan only the relevant columns and skip the rest, reducing the amount of data read from S3. Additionally, partitioning the data based on the most common query predicates, such as date, time, region, etc., will provide faster queries, as it allows Redshift Spectrum to prune the partitions that do not match the query criteria, reducing the amount of data scanned from S3. Partitioning also improves the performance of joins and aggregations, as it reduces data skew and shuffling.
The other options are not as effective as using a columnar storage file format and partitioning the data. Using gzip compression to compress individual files to sizes that are between 1 GB and 5 GB will reduce the data size, but it will not improve the query performance significantly, as gzip is not a splittable compression algorithm and requires decompression before reading. Splitting the data into files that are less than 10 KB will increase the number of files and the metadata overhead, which will degrade the query performance. Using file formats that are not supported by Redshift Spectrum, such as XML, will not work, as Redshift Spectrum will not be able to read or parse the data. Reference:
Amazon Redshift Spectrum
Choosing the Right Data Format
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 4: Data Lakes and Data Warehouses, Section 4.3: Amazon Redshift Spectrum

NEW QUESTION # 64
A financial company recently added more features to its mobile app. The new features required the company to create a new topic in an existing Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster.
A few days after the company added the new topic, Amazon CloudWatch raised an alarm on the RootDiskUsed metric for the MSK cluster.
How should the company address the CloudWatch alarm?

A. Expand the storage of the MSK broker. Configure the MSK cluster storage to expand automatically.
B. Update the MSK broker instance to a larger instance type. Restart the MSK cluster.
C. Specify the Target-Volume-in-GiB parameter for the existing topic.
D. Expand the storage of the Apache ZooKeeper nodes.

Answer: A

Explanation:
The RootDiskUsed metric for the MSK cluster indicates that the storage on the broker is reaching its capacity. The best solution is to expand the storage of the MSK broker and enable automatic storage expansion to prevent future alarms.
* Expand MSK Broker Storage:
* AWS Managed Streaming for Apache Kafka (MSK) allows you to expand the broker storage to accommodate growing data volumes. Additionally, auto-expansion of storage can be configured to ensure that storage grows automatically as the data increases.

NEW QUESTION # 65
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?

A. AWS Glue workflows
B. AWS Glue Studio
C. Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
D. AWS Step Functions

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 # 66
A company stores logs in an Amazon S3 bucket. When a data engineer attempts to access several log files, the data engineer discovers that some files have been unintentionally deleted.
The data engineer needs a solution that will prevent unintentional file deletion in the future.
Which solution will meet this requirement with the LEAST operational overhead?

A. Manually back up the S3 bucket on a regular basis.
B. Configure replication for the S3 bucket.
C. Enable S3 Versioning for the S3 bucket.
D. Use an Amazon S3 Glacier storage class to archive the data that is in the S3 bucket.

Answer: C

Explanation:
To prevent unintentional file deletions and meet the requirement with minimal operational overhead, enabling S3 Versioning is the best solution.
* S3 Versioning:
* S3 Versioning allows multiple versions of an object to be stored in the same S3 bucket. When a file is deleted or overwritten, S3 preserves the previous versions, which means you can recover from accidental deletions or modifications.
* Enabling versioning requires minimal overhead, as it is a bucket-level setting and does not require additional backup processes or data replication.
* Users can recover specific versions of files that were unintentionally deleted, meeting the needs of the data engineer to avoid accidental data loss.

NEW QUESTION # 67
......

A bold attempt is half success. Stop hesitating again, just try and choose our Data-Engineer-Associate test braindump. Please trust me, if you pay attention on dumps content, even just remember the questions and answers you will clear your exam surely. Data-Engineer-Associate test braindump will be the right key to your exam success. As long as the road is right, success is near. Don't be over-anxious, wasting time is robbing oneself. Our Amazon Data-Engineer-Associate test braindump will be definitely useful for your test and 100% valid. Money Back Guaranteed!

Data-Engineer-Associate Exam Discount: https://www.braindumpstudy.com/Data-Engineer-Associate_braindumps.html

At the same time, the content of Data-Engineer-Associate exam torrent is safe and you can download and use it with complete confidence, Amazon Data-Engineer-Associate Pass4sure Dumps Pdf We can guarantee you pass exam, Amazon Data-Engineer-Associate Pass4sure Dumps Pdf Boring learning is out of style, If you still cannot decide, we strongly advise you to buy our Data-Engineer-Associate actual exam material, If you are workers in IT field, holding a Data-Engineer-Associate certification (with the help of Data-Engineer-Associate prep + test bundle) will be an outstanding advantages over others when you are facing promotion or better jobs opportunities especially for companies which have business with Amazon or sell Amazon products.

These devices scan for and remove content that is not wanted, Data-Engineer-Associate It is better to say that our successors speak more clearly through this method rather than facing our absence.

At the same time, the content of Data-Engineer-Associate Exam Torrent is safe and you can download and use it with complete confidence, We can guarantee you pass exam, Boring learning is out of style.

Data-Engineer-Associate Pass4sure Dumps Pdf | High Pass-Rate Data-Engineer-Associate Exam Discount: AWS Certified Data Engineer - Associate (DEA-C01)

If you still cannot decide, we strongly advise you to buy our Data-Engineer-Associate actual exam material, If you are workers in IT field, holding a Data-Engineer-Associate certification (with the help of Data-Engineer-Associate prep + testbundle) will be an outstanding advantages over others when you are Data-Engineer-Associate Exam Pass4sure facing promotion or better jobs opportunities especially for companies which have business with Amazon or sell Amazon products.

Greg Green Greg Green

Biography

Quick Links

Resources

Support