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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.)
A company uses Amazon S3 to store semi-structured data in a transactional data lake. Some of the data files are small, but other data files are tens of terabytes. A data engineer must perform a change data capture (CDC) operation to identify changed data from the data source. The data source sends a full snapshot as a JSON file every day and ingests the changed data into the data lake. Which solution will capture the changed data MOST cost-effectively?
A data engineer needs to schedule a workflow that runs a set of AWS Glue jobs every day. The data engineer does not require the Glue jobs to run or finish at a specific time. Which solution will run the Glue jobs in the MOST cost-effective way?
A company currently stores all of its data in Amazon S3 by using the S3 Standard storage class. A data engineer examined data access patterns to identify trends. During the first 6 months, most data files are accessed several times each day. Between 6 months and 2 years, most data files are accessed once or twice each month. After 2 years, data files are accessed only once or twice each year. The data engineer needs to use an S3 Lifecycle policy to develop new data storage rules. The new storage solution must continue to provide high availability. Which solution will meet these requirements in the MOST cost-effective way?
A company receives a daily file that contains customer data in .xls format. The company stores the file in Amazon S3. The daily file is approximately 2 GB in size. A data engineer concatenates the column in the file that contains customer first names and the column that contains customer last names. The data engineer needs to determine the number of distinct customers in the file. Which solution will meet this requirement with the LEAST operational effort?
A company maintains a data warehouse in an on-premises Oracle database. The company wants to build a data lake on AWS. The company wants to load data warehouse tables into Amazon S3 and synchronize the tables with incremental data that arrives from the data warehouse every day. Each table has a column that contains monotonically increasing values. The size of each table is less than 50 GB. The data warehouse tables are refreshed every night between 1 AM and 2 AM. A business intelligence team queries the tables between 10 AM and 8 PM every day. Which solution will meet these requirements in the MOST operationally efficient way?
A healthcare company uses Amazon Kinesis Data Streams to stream real-time health data from wearable devices, hospital equipment, and patient records. A data engineer needs to find a solution to process the streaming data. The data engineer needs to store the data in an Amazon Redshift Serverless warehouse. The solution must support near real-time analytics of the streaming data and the previous day's data. Which solution will meet these requirements with the LEAST operational overhead?
A company needs to set up a data catalog and metadata management for data sources that run in the AWS Cloud. The company will use the data catalog to maintain the metadata of all the objects that are in a set of data stores. The data stores include structured sources such as Amazon RDS and Amazon Redshift. The data stores also include semistructured sources such as JSON files and .xml files that are stored in Amazon S3. The company needs a solution that will update the data catalog on a regular basis. The solution also must detect changes to the source metadata. Which solution will meet these requirements with the LEAST operational overhead?
A company has three subsidiaries. Each subsidiary uses a different data warehousing solution. The first subsidiary hosts its data warehouse in Amazon Redshift. The second subsidiary uses Teradata Vantage on AWS. The third subsidiary uses Google BigQuery. The company wants to aggregate all the data into a central Amazon S3 data lake. The company wants to use Apache Iceberg as the table format. A data engineer needs to build a new pipeline to connect to all the data sources, run transformations by using each source engine, join the data, and write the data to Iceberg. Which solution will meet these requirements with the LEAST operational effort?
A company has used an Amazon Redshift table that is named Orders for 6 months. The company performs weekly updates and deletes on the table. The table has an interleaved sort key on a column that contains AWS Regions. The company wants to reclaim disk space so that the company will not run out of storage space. The company also wants to analyze the sort key column. Which Amazon Redshift command will meet these requirements?

Question 28 - DEA-C01 discussion

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A company uses an on-premises Microsoft SQL Server database to store financial transaction data. The company migrates the transaction data from the on-premises database to AWS at the end of each month. The company has noticed that the cost to migrate data from the on-premises database to an Amazon RDS for SQL Server database has increased recently.

The company requires a cost-effective solution to migrate the data to AWS. The solution must cause minimal downtown for the applications that access the database.

Which AWS service should the company use to meet these requirements?

A.

AWS Lambda

Answers
A.

AWS Lambda

B.

AWS Database Migration Service (AWS DMS)

Answers
B.

AWS Database Migration Service (AWS DMS)

C.

AWS Direct Connect

Answers
C.

AWS Direct Connect

D.

AWS DataSync

Answers
D.

AWS DataSync

Suggested answer: B

Explanation:

AWS Database Migration Service (AWS DMS) is a cloud service that makes it possible to migrate relational databases, data warehouses, NoSQL databases, and other types of data stores to AWS quickly, securely, and with minimal downtime and zero data loss1.AWS DMS supports migration between 20-plus database and analytics engines, such as Microsoft SQL Server to Amazon RDS for SQL Server2.AWS DMS takes over many of the difficult or tedious tasks involved in a migration project, such as capacity analysis, hardware and software procurement, installation and administration, testing and debugging, and ongoing replication and monitoring1.AWS DMS is a cost-effective solution, as you only pay for the compute resources and additional log storage used during the migration process2. AWS DMS is the best solution for the company to migrate the financial transaction data from the on-premises Microsoft SQL Server database to AWS, as it meets the requirements of minimal downtime, zero data loss, and low cost.

Option A is not the best solution, as AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers, but it does not provide any built-in features for database migration. You would have to write your own code to extract, transform, and load the data from the source to the target, which would increase the operational overhead and complexity.

Option C is not the best solution, as AWS Direct Connect is a service that establishes a dedicated network connection from your premises to AWS, but it does not provide any built-in features for database migration. You would still need to use another service or tool to perform the actual data transfer, which would increase the cost and complexity.

Option D is not the best solution, as AWS DataSync is a service that makes it easy to transfer data between on-premises storage systems and AWS storage services, such as Amazon S3, Amazon EFS, and Amazon FSx for Windows File Server, but it does not support Amazon RDS for SQL Server as a target. You would have to use another service or tool to migrate the data from Amazon S3 to Amazon RDS for SQL Server, which would increase the latency and complexity.Reference:

Database Migration - AWS Database Migration Service - AWS

What is AWS Database Migration Service?

AWS Database Migration Service Documentation

AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide

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asked 29/10/2024
David Brun
36 questions
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