Instant Access Amazon.DAS-C01.v2024-02-15.q109 Actual Practice Test Engine for Free (Page 13)

40%off

DAS-C01 Premium Dumps

Latest DAS-C01 Exam Premium Dumps provide by TrainingQuiz.com to help you Passing DAS-C01 Exam! TrainingQuiz.com offers the updated DAS-C01 exam dumps, the TrainingQuiz.com DAS-C01 exam questions has been updated to correct Answer. Get the latest TrainingQuiz.com DAS-C01 pdf dumps with Exam Engine here:

(209 Q&As Dumps, 40%OFF Special Discount: DumpsDB)

Question 56

A company uses the Amazon Kinesis SDK to write data to Kinesis Data Streams. Compliance requirements state that the data must be encrypted at rest using a key that can be rotated. The company wants to meet this encryption requirement with minimal coding effort.
How can these requirements be met?

A.Create a customer master key (CMK) in AWS KMS. Assign the CMK an alias. Use the AWS Encryption SDK, providing it with the key alias to encrypt and decrypt the data.
B.Create a customer master key (CMK) in AWS KMS. Assign the CMK an alias. Enable server-side encryption on the Kinesis data stream using the CMK alias as the KMS master key.
C.Create a customer master key (CMK) in AWS KMS. Create an AWS Lambda function to encrypt and decrypt the data. Set the KMS key ID in the function's environment variables.
D.Enable server-side encryption on the Kinesis data stream using the default KMS key for Kinesis Data

Question 57

A real estate company has a mission-critical application using Apache HBase in Amazon EMR. Amazon EMR is configured with a single master node. The company has over 5 TB of data stored on an Hadoop Distributed File System (HDFS). The company wants a cost-effective solution to make its HBase data highly available.
Which architectural pattern meets company's requirements?

A.Store the data on an EMR File System (EMRFS) instead of HDFS and enable EMRFS consistent view. Run two separate EMR clusters in two different Availability Zones. Point both clusters to the same HBase root directory in the same Amazon S3 bucket.
B.Store the data on an EMR File System (EMRFS) instead of HDFS. Enable EMRFS consistent view. Create an EMR HBase cluster with multiple master nodes. Point the HBase root directory to an Amazon S3 bucket.
C.Use Spot Instances for core and task nodes and a Reserved Instance for the EMR master node. Configure the EMR cluster with multiple master nodes. Schedule automated snapshots using Amazon EventBridge.
D.Store the data on an EMR File System (EMRFS) instead of HDFS and enable EMRFS consistent view. Create a primary EMR HBase cluster with multiple master nodes. Create a secondary EMR HBase read- replica cluster in a separate Availability Zone. Point both clusters to the same HBase root directory in the same Amazon S3 bucket.

Question 58

A retail company's data analytics team recently created multiple product sales analysis dashboards for the average selling price per product using Amazon QuickSight. The dashboards were created from .csv files uploaded to Amazon S3. The team is now planning to share the dashboards with the respective external product owners by creating individual users in Amazon QuickSight. For compliance and governance reasons, restricting access is a key requirement. The product owners should view only their respective product analysis in the dashboard reports.
Which approach should the data analytics team take to allow product owners to view only their products in the dashboard?

A.Separate the data by product and use S3 bucket policies for authorization.
B.Separate the data by product and use IAM policies for authorization.
C.Create a manifest file with row-level security.
D.Create dataset rules with row-level security.

Question 59

A company is building a data lake and needs to ingest data from a relational database that has time-series data.
The company wants to use managed services to accomplish this. The process needs to be scheduled daily and bring incremental data only from the source into Amazon S3.
What is the MOST cost-effective approach to meet these requirements?

A.Use AWS Glue to connect to the data source using JDBC Drivers. Ingest incremental records only using job bookmarks.
B.Use AWS Glue to connect to the data source using JDBC Drivers. Store the last updated key in an Amazon DynamoDB table and ingest the data using the updated key as a filter.
C.Use AWS Glue to connect to the data source using JDBC Drivers and ingest the entire dataset. Use appropriate Apache Spark libraries to compare the dataset, and find the delta.
D.Use AWS Glue to connect to the data source using JDBC Drivers and ingest the full data. Use AWS DataSync to ensure the delta only is written into Amazon S3.

Question 60

A technology company is creating a dashboard that will visualize and analyze time-sensitive data. The data will come in through Amazon Kinesis Data Firehose with the butter interval set to 60 seconds. The dashboard must support near-real-time data.
Which visualization solution will meet these requirements?

A.Select Amazon S3 as the endpoint for Kinesis Data Firehose. Read data into an Amazon SageMaker Jupyter notebook and carry out the desired analyses and visualizations.
B.Select Amazon S3 as the endpoint for Kinesis Data Firehose. Use AWS Glue to catalog the data and Amazon Athena to query it. Connect Amazon QuickSight with SPICE to Athena to create the desired analyses and visualizations.
C.Select Amazon Elasticsearch Service (Amazon ES) as the endpoint for Kinesis Data Firehose. Set up a Kibana dashboard using the data in Amazon ES with the desired analyses and visualizations.
D.Select Amazon Redshift as the endpoint for Kinesis Data Firehose. Connect Amazon QuickSight with SPICE to Amazon Redshift to create the desired analyses and visualizations.