Browse DBS Questions
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Total: 100 questionsPage: 3 of 10
Question 21 of 100
ABCD has developed a sensor intended to be placed inside of people's shoes, monitoring the number of steps taken every day. ABCD is expecting thousands of sensors reporting in every minute and hopes to scale to millions by the end of the year. A requirement for the project is it needs to be able to accept the data, run it through ETL to store in warehouse and archive it on Amazon Glacier, with room for a real-time dashboard for the sensor data to be added at a later date. What is the best method for architecting this application given the requirements? Choose the correct answer:
AUse Amazon Cognito to accept the data when the user pairs the sensor to the phone, and then have Cognito send the data to Dynamodb. Use Data Pipeline to create a job that takes the DynamoDB tablee and sends it to an EMR cluster for ETL, then outputs to Redshift and S3 while, using S3 lifecycle policies to archive on Glacier.
BWrite the sensor data directly to a scaleable DynamoDB; create a data pipeline that starts an EMR cluster using data from DynamoDB and sends the data to S3 and Redshift.
CWrite the sensor data to Amazon S3 with a lifecycle policy for Glacier, create an EMR cluster that uses the bucket data and runs it through ETL. It then outputs that data into Redshift data warehouse.
DWrite the sensor data directly to Amazon Kinesis and output the data into Amazon S3 creating a lifecycle policy for Glacier archiving. Also, have a parallel processing application that runs the data through EMR and sends to a Redshift data warehouse.
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Question 22 of 100
You need to visualize data from Spark and Hive running on an EMR cluster. Which of the options is best for an interactive and collaborative notebook for data exploration?
AHive
BD3.js
CKinesis Analytics
DZeppelin
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Question 23 of 100
Your company needs to design a data warehouse for a client in the retail industry. The data warehouse will store historic purchases in Amazon Redshift. To comply with PCI:DSS requirements and meet data protection standards, the data must be encrypted at rest and have keys managed by a corporate on-premises HSM. How can you meet these requirements in a cost-effective manner?
AUse AWS Import/Export to import a company HSM device into AWS alongside the Amazon Redshift cluster, and configure Redshift to use the imported HSM.
BCreate a VPN connection between a VPC you create in AWS and an on-premises network. Then launch the Redshift cluster in the VPC, and configure it to use your corporate HSM.
CUse the AWS CloudHSM service to establish a trust relationship between the CloudHSM and the corporate HSM over a Direct Connect connection. Configure Amazon Redshift to use the CloudHSM device.
DConfigure the AWS Key Management Service to point to the corporate HSM device, and then launch the Amazon Redshift cluster with the KMS managing the encryption keys.
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Question 24 of 100
A company wants to use Redshift cluster for petabyte-scale data warehousing. Data for processing would be stored on Amazon S3. As a security requirement, the company wants the data to be encrypted at rest. As a solution architect how would you implement the solution?
AStore the data in S3 with Server Side Encryption and copy the data over to Redshift cluster
BStore the data in S3. Launch an encrypted Redshift cluster, copy the data to the Redshift cluster and store back in S3 in encrypted format
CStore the data in S3 with Server Side Encryption. Launch an encrypted Redshift cluster and copy the data to the cluster.
DStore the data in S3 with Server Side Encryption. Launch a Redshift cluster, copy the data to cluster and enable encryption on the cluster.
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Question 25 of 100
An organization needs a data store to handle the following data types and access patterns: Key-value access pattern Complex SQL queries and transactions Consistent reads Fixed schema Which data store should the organization choose?
AAmazon S3
BAmazon Kinesis
CAmazon DynamoDB
DAmazon RDS
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Question 26 of 100Multiple Choice
A video-sharing mobile application uploads files greater than 10 GB to an Amazon S3 bucket. However, when using the application in locations far away from the S3 bucket region, uploads take extended periods of time, and sometimes fail to complete. Which combination of methods would improve the performance of uploading to the application? (Select TWO.)
AConfigure an S3 bucket in each region to receive the uploads, and use cross-region replication to copy the files to the distribution bucket.
BModify the application to add random prefixes to the files before uploading.
CSet up Amazon Route 53 with latency-based routing to route the uploads to the nearest S3 bucket region.
DEnable S3 Transfer Acceleration on the S3 bucket, and configure the application to use the Transfer Acceleration endpoint for uploads.
EConfigure the application to break the video files into chunks and use a multipart upload to transfer files to Amazon S3.
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Question 27 of 100
A company is collected real time senstive data using Amazon Kinesis. As a security requirement, the Amazon Kinesis stream needs to be encrypted. Which approach should be used to accomplish this task?
APerform a client-side encryption of the data before it enters the Amazon Kinesis stream on the producer.
BUse a partition key to segment the data by MD5 hash function, which makes it undecipherable while in transit.
CPerform a client-side encryption of the data before it enters the Amazon Kinesis stream on the consumer.
DUse a shard to segment the data, which has built-in functionality to make it indecipherable while in transit.
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Question 28 of 100
A customer has a machine learning workflow that consists of multiple quick cycles of reads-writes-reads on Amazon S3. The customer needs to run the workflow on EMR but is concerned that the reads in subsequent cycles will miss new data critical to the machine learning from the prior cycles. How should the customer accomplish this?
AUse AWS Data Pipeline to orchestrate the data processing cycles.
BTurn on EMRFS consistent view when configuring the EMR cluster.
CSet hadoop.data.consistency=true in the core-site.xml file.
DSet hadoop.s3.consistency=true in the core-site.xml file.
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Question 29 of 100
Managers in a company need access to the human resources database that runs on Amazon Redshift, to run reports about their employees. Managers must only see information about their direct reports. Which technique should be used to address this requirement with Amazon Redshift?
ADefine an IAM group for each manager with each employee as an IAM user in that group, and use that to limit the access.
BUse Amazon Redshift snapshot to create one cluster per manager. Allow the manager to access only their designated clusters.
CDefine a key for each manager in AWS KMS and encrypt the data for their employees with their private keys.
DDefine a view that uses the employee’s manager name to filter the records based on current user names.
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Question 30 of 100
A company with a support organization needs support engineers to be able to search historic cases to provide fast responses on new issues raised. The company has forwarded all support messages into an Amazon Kinesis Stream. This meets a company objective of using only managed services to reduce operational overhead. The company needs an appropriate architecture that allows support engineers to search on historic cases and find similar issues and their associated responses. Which AWS Lambda action is most appropriate?
AIngest and index the content into an Amazon Elasticsearch domain.
BStem and tokenize the input and store the results into Amazon ElastiCache.
CWrite data as JSON into Amazon DynamoDB with primary and secondary indexes.
DAggregate feedback in Amazon S3 using a columnar format with partitioning.
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