Browse DBS Questions
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Total: 100 questionsPage: 1 of 10
Question 1 of 100
A data engineer is about to perform a major upgrade to the DDL contained within an Amazon Redshift cluster to support a new data warehouse application. The upgrade scripts will include user permission updates, view and table structure changes as well as additional loading and data manipulation tasks. The data engineer must be able to restore the database to its existing state in the event of issues. Which action should be taken prior to performing this upgrade task?
ARun an UNLOAD command for all data in the warehouse and save it to S3.
BCreate a manual snapshot of the Amazon Redshift cluster.
CMake a copy of the automated snapshot on the Amazon Redshift cluster.
DCall the waitForSnapshotAvailable command from either the AWS CLI or an AWS SDK.
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Question 2 of 100
The department of transportation for a major metropolitan area has placed sensors on roads at key locations around the city. The goal is to analyze the flow of traffic and notifications from emergency services to identify potential issues and to help planners correct trouble spots. A data engineer needs a scalable and fault-tolerant solution that allows planners to respond to issues within 30 seconds of their occurrence. Which solution should the data engineer choose?
ACollect the sensor data with Amazon Kinesis Firehose and store it in Amazon Redshift for analysis. Collect emergency services events with Amazon SQS and store in Amazon DynamoDB for analysis.
BCollect the sensor data with Amazon SQS and store in Amazon DynamoDB for analysis. Collect emergency services events with Amazon Kinesis Firehose and store in Amazon Redshift for analysis.
CCollect both sensor data and emergency services events with Amazon Kinesis Streams and use DynamoDB for analysis.
DCollect both sensor data and emergency services events with Amazon Kinesis Firehose and use Amazon Redshift for analysis.
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Question 3 of 100Multiple Choice
An Amazon Redshift Database is encrypted using KMS. A data engineer needs to use the AWS CLI to create a KMS encrypted snapshot of the database in another AWS region. Which three steps should the data engineer take to accomplish this task? (Choose three.)
ACreate a new KMS key in the destination region.
BCopy the existing KMS key to the destination region.
CUse CreateSnapshotCopyGrant to allow Amazon Redshift to use the KMS key from the destination region.
DUse CreateSnapshotCopyGrant to allow Amazon Redshift to use the KMS key from the source region.
EIn the source region, enable cross-region replication and specify the name of the copy grant created.
FIn the destination region, enable cross-region replication and specify the name of the copy grant created.
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Question 4 of 100
You have two different groups using Redshift to analyze data of a petabyte-scale data warehouse. Each query issued by the first group takes approximately 1-2 hours to analyze the data while the second group's queries only take between 5-10 minutes to analyze data. You don't want the second group's queries to wait until the first group's queries are finished. You need to design a solution so that this does not happen. Which of the following would be the best and cheapest solution to deploy to solve this dilemma?
ACreate a read replica of Redshift and run the second team's queries on the read replica.
BCreate two separate workload management groups and assign them to the respective groups.
CPause the long queries when necessary and resume them when there are no queries happening.
DStart another Redshift cluster from a snapshot for the second team if the current Redshift cluster is busy processing long queries.
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Question 5 of 100
A telecommunications company needs to predict customer churn (i.e., customers who decide to switch to a competitor). The company has historic records of each customer, including monthly consumption patterns, calls to customer service, and whether the customer ultimately quit the service. All of this data is stored in Amazon S3. The company needs to know which customers are likely going to churn soon so that they can win back their loyalty. What is the optimal approach to meet these requirements?
AUse the Amazon Machine Learning service to build the binary classification model based on the dataset stored in Amazon S3. The model will be used regularly to predict churn attribute for existing customers.
BUse AWS QuickSight to connect it to data stored in Amazon S3 to obtain the necessary business insight. Plot the churn trend graph to extrapolate churn likelihood for existing customers.
CUse EMR to run the Hive queries to build a profile of a churning customer. Apply a profile to existing customers to determine the likelihood of churn.
DUse a Redshift cluster to COPY the data from Amazon S3. Create a User Defined Function in Redshift that computes the likelihood of churn.
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Question 6 of 100
Your social media marketing application has a component written in Ruby running on AWS Elastic Beanstalk. This application component posts messages to social media sites in support of various marketing campaigns. Your management now requires you to record replies to these social media messages to analyze the effectiveness of the marketing campaign in comparison to past and future efforts. You’ve already developed a new application component to interface with the social media site APIs in order to read the replies. Which process should you use to record the social media replies in a durable data store that can be accessed at any time for analytics of historical data?
ADeploy the new application component in an Auto Scaling group of Amazon EC2 instances, read the data from the social media sites, store it with Amazon Elastic Block Store, and use AWS Data Pipeline to publish it to Amazon Kinesis for analytics.
BDeploy the new application component as an Elastic Beanstalk application, read the data from the social media sites, store it in DynamoDB, and use Apache Hive with Amazon Elastic MapReduce for analytics.
CDeploy the new application component in an Auto Scaling group of Amazon EC2 instances, read the data from the social media sites, store it in Amazon Glacier, and use AWS Data Pipeline to publish it to Amazon RedShift for analytics.
DDeploy the new application component as an Amazon Elastic Beanstalk application, read the data from the social media site, store it with Amazon Elastic Block store, and use Amazon Kinesis to stream the data to Amazon CloudWatch for analytics.
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Question 7 of 100
An organization needs to design and deploy a large-scale data storage solution that will be highly durable and highly flexible with respect to the type and structure of data being stored. The data to be stored will be sent or generated from a variety of sources and must be persistently available for access and processing by multiple applications. What is the most cost-effective technique to meet these requirements?
AUse Amazon Simple Storage Service (S3) as the actual data storage system, coupled with appropriate tools for ingestion/acquisition of data and for subsequent processing and querying.
BDeploy a long-running Amazon Elastic MapReduce (EMR) cluster with Amazon Elastic Block Store (EBS) volumes for persistent HDFS storage and appropriate Hadoop ecosystem tools for processing and querying.
CUse Amazon Redshift with data replication to Amazon Simple Storage Service (S3) for comprehensive durable data storage, processing, and querying.
DLaunch an Amazon Relational Database Service (RDS), and use the enterprise grade and capacity of the Amazon Aurora engine for storage, processing, and querying.
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Question 8 of 100
You have been asked to handle a large data migration from multiple Amazon RDS MySQL instances to a DynamoDB table. You have been given a short amount of time to complete the data migration. What will allow you to complete this complex data processing workflow?
ACreate an Amazon Kinesis data stream, pipe in all of the Amazon RDS data, and direct the data toward a DynamoDB table.
BWrite a script in your language of choice, install the script on an Amazon EC2 instance, and then use Auto Scaling groups to ensure that the latency of the migration pipelines never exceeds four seconds in any 15-minute period.
CWrite a bash script to run on your Amazon RDS instance that will export data into DynamoDB.
DCreate a data pipeline to export Amazon RDS data and import the data into DynamoDB.
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Question 9 of 100
A retailer exports data daily from its transactional databases into an S3 bucket in the Sydney region. The retailer's Data Warehousing team wants to import this data into an existing Amazon Redshift cluster in their VPC at Sydney. Corporate security policy mandates that data can only be transported within a VPC. What combination of the following steps will satisfy the security policy? Choose 2 answers
AEnable Amazon Redshift Enhanced VPC Routing.
BCreate a Cluster Security Group to allow the Amazon Redshift cluster to access Amazon S3.
CCreate a NAT gateway in a public subnet to allow the Amazon Redshift cluster to access Amazon S3.
DCreate and configure an Amazon S3 VPC endpoint.
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Question 10 of 100
You have an application that is currently in the development stage but is expected to write 2,400 items per minute to a DynamoDB table, each 2Kb in size or less and then fluctuate to 4,800 writes of items (of the same size) per minute on weekends. There may be other fluctuations within that range in the future as the application develops. It is important to the success of the application that the vast majority of user requests are met in a cost-effective way. How should this table be created?
AProvision a base WCU of 80 and then schedule regular increases to 160 WCUs when a higher load is expected.
BSet up an auto-scaling policy on the DynamoDB table that doesn't let the traffic dip below the usual load and allows it to scale to meet demand.
CEnabled DynamoDB streams have a Lambda function triggered to review the current capacity on each change to the table.
DProvision a base WCU of 160 and then schedule a job that adds 160 more WCUs when a higher load is expected.
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