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Question 1:

A company has deployed an e-commerce web application in a new AWS account. An Amazon RDS for MySQL Multi-AZ DB instance is part of this deployment with a database-1.xxxxxxxxxxxx.us-east1.rds.amazonaws.com endpoint listening on port 3306. The company\’s Database Specialist is able to log in to MySQL and run queries from the bastion host using these details.

When users try to utilize the application hosted in the AWS account, they are presented with a generic error message. The application servers are logging a “could not connect to server: Connection times out” error message to Amazon CloudWatch Logs.

What is the cause of this error?

A. The user name and password the application is using are incorrect.

B. The security group assigned to the application servers does not have the necessary rules to allow inbound connections from the DB instance.

C. The security group assigned to the DB instance does not have the necessary rules to allow inbound connections from the application servers.

D. The user name and password are correct, but the user is not authorized to use the DB instance.

Correct Answer: C

Reference: https://forums.aws.amazon.com/thread.jspa?threadID=129700


Question 2:

An AWS CloudFormation stack that included an Amazon RDS DB instance was accidentally deleted and recent data was lost. A Database Specialist needs to add RDS settings to the CloudFormation template to reduce the chance of accidental instance data loss in the future.

Which settings will meet this requirement? (Choose three.)

A. Set DeletionProtection to True

B. Set MultiAZ to True

C. Set TerminationProtection to True

D. Set DeleteAutomatedBackups to False

E. Set DeletionPolicy to Delete

F. Set DeletionPolicy to Retain

Correct Answer: ACF

Reference: https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attributedeletionpolicy.html https://aws.amazon.com/premiumsupport/knowledge-center/cloudformation-accidental-updates/


Question 3:

A Database Specialist is troubleshooting an application connection failure on an Amazon Aurora DB cluster with multiple Aurora Replicas that had been running with no issues for the past 2 months. The connection failure lasted for 5 minutes and corrected itself after that. The Database Specialist reviewed the Amazon RDS events and determined a failover event occurred at that time. The failover process took around 15 seconds to complete.

What is the MOST likely cause of the 5-minute connection outage?

A. After a database crash, Aurora needed to replay the redo log from the last database checkpoint

B. The client-side application is caching the DNS data and its TTL is set too high

C. After failover, the Aurora DB cluster needs time to warm up before accepting client connections

D. There were no active Aurora Replicas in the Aurora DB cluster

Correct Answer: C


Question 4:

A company is deploying a solution in Amazon Aurora by migrating from an on-premises system. The IT department has established an AWS Direct Connect link from the company\’s data center. The company\’s Database Specialist has selected the option to require SSL/TLS for connectivity to prevent plaintext data from being set over the network. The migration appears to be working successfully, and the data can be queried from a desktop machine.

Two Data Analysts have been asked to query and validate the data in the new Aurora DB cluster. Both Analysts are unable to connect to Aurora. Their user names and passwords have been verified as valid and the Database Specialist can connect to the DB cluster using their accounts. The Database Specialist also verified that the security group configuration allows network from all corporate IP addresses.

What should the Database Specialist do to correct the Data Analysts’ inability to connect?

A. Restart the DB cluster to apply the SSL change.

B. Instruct the Data Analysts to download the root certificate and use the SSL certificate on the connection string to connect.

C. Add explicit mappings between the Data Analysts’ IP addresses and the instance in the security group assigned to the DB cluster.

D. Modify the Data Analysts’ local client firewall to allow network traffic to AWS.

Correct Answer: D


Question 5:

A company is concerned about the cost of a large-scale, transactional application using Amazon DynamoDB that only needs to store data for 2 days before it is deleted. In looking at the tables, a Database Specialist notices that much of the data is months old, and goes back to when the application was first deployed.

What can the Database Specialist do to reduce the overall cost?

A. Create a new attribute in each table to track the expiration time and create an AWS Glue transformation to delete entries more than 2 days old.

B. Create a new attribute in each table to track the expiration time and enable DynamoDB Streams on each table.

C. Create a new attribute in each table to track the expiration time and enable time to live (TTL) on each table.

D. Create an Amazon CloudWatch Events event to export the data to Amazon S3 daily using AWS Data Pipeline and then truncate the Amazon DynamoDB table.

Correct Answer: A


Question 6:

A company has an on-premises system that tracks various database operations that occur over the lifetime of a database, including database shutdown, deletion, creation, and backup.

The company recently moved two databases to Amazon RDS and is looking at a solution that would satisfy these requirements. The data could be used by other systems within the company.

Which solution will meet these requirements with minimal effort?

A. Create an Amazon Cloudwatch Events rule with the operations that need to be tracked on Amazon RDS. Create an AWS Lambda function to act on these rules and write the output to the tracking systems.

B. Create an AWS Lambda function to trigger on AWS CloudTrail API calls. Filter on specific RDS API calls and write the output to the tracking systems.

C. Create RDS event subscriptions. Have the tracking systems subscribe to specific RDS event system notifications.

D. Write RDS logs to Amazon Kinesis Data Firehose. Create an AWS Lambda function to act on these rules and write the output to the tracking systems.

Correct Answer: C


Question 7:

A clothing company uses a custom ecommerce application and a PostgreSQL database to sell clothes to thousands of users from multiple countries. The company is migrating its application and database from its on-premises data center to the AWS Cloud. The company has selected Amazon EC2 for the application and Amazon RDS for PostgreSQL for the database. The company requires database passwords to be changed every 60 days. A Database Specialist needs to ensure that the credentials used by the web application to connect to the database are managed securely.

Which approach should the Database Specialist take to securely manage the database credentials?

A. Store the credentials in a text file in an Amazon S3 bucket. Restrict permissions on the bucket to the IAM role associated with the instance profile only. Modify the application to download the text file and retrieve the credentials on start up. Update the text file every 60 days.

B. Configure IAM database authentication for the application to connect to the database. Create an IAM user and map it to a separate database user for each ecommerce user. Require users to update their passwords every 60 days.

C. Store the credentials in AWS Secrets Manager. Restrict permissions on the secret to only the IAM role associated with the instance profile. Modify the application to retrieve the credentials from Secrets Manager on start up. Configure the rotation interval to 60 days.

D. Store the credentials in an encrypted text file in the application AMI. Use AWS KMS to store the key for decrypting the text file. Modify the application to decrypt the text file and retrieve the credentials on start up. Update the text file and publish a new AMI every 60 days.

Correct Answer: B


Question 8:

A financial services company is developing a shared data service that supports different applications from throughout the company. A Database Specialist designed a solution to leverage Amazon ElastiCache for Redis with cluster mode enabled to enhance performance and scalability. The cluster is configured to listen on port 6379.

Which combination of steps should the Database Specialist take to secure the cache data and protect it from unauthorized access? (Choose three.)

A. Enable in-transit and at-rest encryption on the ElastiCache cluster.

B. Ensure that Amazon CloudWatch metrics are configured in the ElastiCache cluster.

C. Ensure the security group for the ElastiCache cluster allows all inbound traffic from itself and inbound traffic on TCP port 6379 from trusted clients only.

D. Create an IAM policy to allow the application service roles to access all ElastiCache API actions.

E. Ensure the security group for the ElastiCache clients authorize inbound TCP port 6379 and port 22 traffic from the trusted ElastiCache cluster\’s security group.

F. Ensure the cluster is created with the auth-token parameter and that the parameter is used in all subsequent commands.

Correct Answer: ABE

Reference: https://aws.amazon.com/getting-started/tutorials/setting-up-a-redis-cluster-with-amazonelasticache/


Question 9:

A company is running an Amazon RDS for PostgeSQL DB instance and wants to migrate it to an Amazon Aurora PostgreSQL DB cluster. The current database is 1 TB in size. The migration needs to have minimal downtime.

What is the FASTEST way to accomplish this?

A. Create an Aurora PostgreSQL DB cluster. Set up replication from the source RDS for PostgreSQL DB instance using AWS DMS to the target DB cluster.

B. Use the pg_dump and pg_restore utilities to extract and restore the RDS for PostgreSQL DB instance to the Aurora PostgreSQL DB cluster.

C. Create a database snapshot of the RDS for PostgreSQL DB instance and use this snapshot to create the Aurora PostgreSQL DB cluster.

D. Migrate data from the RDS for PostgreSQL DB instance to an Aurora PostgreSQL DB cluster using an Aurora Replica. Promote the replica during the cutover.

Correct Answer: C


Question 10:

A Database Specialist is migrating a 2 TB Amazon RDS for Oracle DB instance to an RDS for PostgreSQL DB instance using AWS DMS. The source RDS Oracle DB instance is in a VPC in the us-east-1 Region. The target RDS for PostgreSQL DB instance is in a VPC in the use-west-2 Region.

Where should the AWS DMS replication instance be placed for the MOST optimal performance?

A. In the same Region and VPC of the source DB instance

B. In the same Region and VPC as the target DB instance

C. In the same VPC and Availability Zone as the target DB instance

D. In the same VPC and Availability Zone as the source DB instance

Correct Answer: D


Question 11:

The Development team recently executed a database script containing several data definition language (DDL) and data manipulation language (DML) statements on an Amazon Aurora MySQL DB cluster. The release accidentally deleted thousands of rows from an important table and broke some application functionality. This was discovered 4 hours after the release. Upon investigation, a Database Specialist tracked the issue to a DELETE command in the script with an incorrect WHERE clause filtering the wrong set of rows. The Aurora DB cluster has Backtrack enabled with an 8-hour backtrack window. The Database Administrator also took a manual snapshot of the DB cluster before the release started. The database needs to be returned to the correct state as quickly as possible to resume full application functionality. Data loss must be minimal. How can the Database Specialist accomplish this?

A. Quickly rewind the DB cluster to a point in time before the release using Backtrack.

B. Perform a point-in-time recovery (PITR) of the DB cluster to a time before the release and copy the deleted rows from the restored database to the original database.

C. Restore the DB cluster using the manual backup snapshot created before the release and change the application configuration settings to point to the new DB cluster.

D. Create a clone of the DB cluster with Backtrack enabled. Rewind the cloned cluster to a point in time before the release. Copy deleted rows from the clone to the original database.

Correct Answer: D


Question 12:

A company is load testing its three-tier production web application deployed with an AWS CloudFormation template on AWS. The Application team is making changes to deploy additional Amazon EC2 and AWS Lambda resources to expand the load testing capacity. A Database Specialist wants to ensure that the changes made by the Application team will not change the Amazon RDS database resources already deployed. Which combination of steps would allow the Database Specialist to accomplish this? (Choose two.)

A. Review the stack drift before modifying the template

B. Create and review a change set before applying it

C. Export the database resources as stack outputs

D. Define the database resources in a nested stack

E. Set a stack policy for the database resources

Correct Answer: AD


Question 13:

A manufacturing company\’s website uses an Amazon Aurora PostgreSQL DB cluster.

Which configurations will result in the LEAST application downtime during a failover? (Choose three.)

A. Use the provided read and write Aurora endpoints to establish a connection to the Aurora DB cluster.

B. Create an Amazon CloudWatch alert triggering a restore in another Availability Zone when the primary Aurora DB cluster is unreachable.

C. Edit and enable Aurora DB cluster cache management in parameter groups.

D. Set TCP keepalive parameters to a high value.

E. Set JDBC connection string timeout variables to a low value.

F. Set Java DNS caching timeouts to a high value.

Correct Answer: ABC


Question 14:

A company is hosting critical business data in an Amazon Redshift cluster. Due to the sensitive nature of the data, the cluster is encrypted at rest using AWS KMS. As a part of disaster recovery requirements, the company needs to copy the Amazon Redshift snapshots to another Region.

Which steps should be taken in the AWS Management Console to meet the disaster recovery requirements?

A. Create a new KMS customer master key in the source Region. Switch to the destination Region, enable Amazon Redshift cross-Region snapshots, and use the KMS key of the source Region.

B. Create a new IAM role with access to the KMS key. Enable Amazon Redshift cross-Region replication using the new IAM role, and use the KMS key of the source Region.

C. Enable Amazon Redshift cross-Region snapshots in the source Region, and create a snapshot copy grant and use a KMS key in the destination Region.

D. Create a new KMS customer master key in the destination Region and create a new IAM role with access to the new KMS key. Enable Amazon Redshift cross-Region replication in the source Region and use the KMS key of the destination Region.

Correct Answer: A

Reference: https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-snapshots.html


Question 15:

A company has a production Amazon Aurora Db cluster that serves both online transaction processing (OLTP) transactions and compute-intensive reports. The reports run for 10% of the total cluster uptime while the OLTP transactions run all the time. The company has benchmarked its workload and determined that a six-node Aurora DB cluster is appropriate for the peak workload. The company is now looking at cutting costs for this DB cluster, but needs to have a sufficient number of nodes in the cluster to support the workload at different times. The workload has not changed since the previous benchmarking exercise. How can a Database Specialist address these requirements with minimal user involvement?

A. Split up the DB cluster into two different clusters: one for OLTP and the other for reporting. Monitor and set up replication between the two clusters to keep data consistent.

B. Review all evaluate the peak combined workload. Ensure that utilization of the DB cluster node is at an acceptable level. Adjust the number of instances, if necessary.

C. Use the stop cluster functionality to stop all the nodes of the DB cluster during times of minimal workload. The cluster can be restarted again depending on the workload at the time.

D. Set up automatic scaling on the DB cluster. This will allow the number of reader nodes to adjust automatically to the reporting workload, when needed.

Correct Answer: D


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Question 1:

Company A operates in Country X. Company A maintains a large dataset of historical purchase orders that contains personal data of their customers in the form of full names and telephone numbers. The dataset consists of 5 text files, 1TB each. Currently the dataset resides on-premises due to legal requirements of storing personal data in-country. The research and development department needs to run a clustering algorithm on the dataset and wants to use Elastic Map Reduce service in the closest AWS region. Due to geographic distance, the minimum latency between the on-premises system and the closet AWS region is 200 ms.

Which option allows Company A to do clustering in the AWS Cloud and meet the legal requirement of maintaining personal data in-country?

A. Anonymize the personal data portions of the dataset and transfer the data files into Amazon S3 in the AWS region. Have the EMR cluster read the dataset using EMRFS.

B. Establish a Direct Connect link between the on-premises system and the AWS region to reduce latency. Have the EMR cluster read the data directly from the on-premises storage system over Direct Connect.

C. Encrypt the data files according to encryption standards of Country X and store them on AWS region in Amazon S3. Have the EMR cluster read the dataset using EMRFS.

D. Use AWS Import/Export Snowball device to securely transfer the data to the AWS region and copy the files onto an EBS volume. Have the EMR cluster read the dataset using EMRFS.

Correct Answer: B


Question 2:

An administrator needs to design a strategy for the schema in a Redshift cluster. The administrator needs to determine the optimal distribution style for the tables in the Redshift schema. In which two circumstances would choosing EVEN distribution be most appropriate? (Choose two.)

A. When the tables are highly denormalized and do NOT participate in frequent joins.

B. When data must be grouped based on a specific key on a defined slice.

C. When data transfer between nodes must be eliminated.

D. When a new table has been loaded and it is unclear how it will be joined to dimension tables.

Correct Answer: BD


Question 3:

A large grocery distributor receives daily depletion reports from the field in the form of gzip archives od CSV files uploaded to Amazon S3. The files range from 500MB to 5GB. These files are processed daily by an EMR job. Recently it has been observed that the file sizes vary, and the EMR jobs take too long. The distributor needs to tune and optimize the data processing workflow with this limited information to improve the performance of the EMR job. Which recommendation should an administrator provide?

A. Reduce the HDFS block size to increase the number of task processors.

B. Use bzip2 or Snappy rather than gzip for the archives.

C. Decompress the gzip archives and store the data as CSV files.

D. Use Avro rather than gzip for the archives.

Correct Answer: B


Question 4:

A company has several teams of analysts. Each team of analysts has their own cluster. The teams need to run SQL queries using Hive, Spark-SQL, and Presto with Amazon EMR. The company needs to enable a centralized metadata layer to expose the Amazon S3 objects as tables to the analysts.

Which approach meets the requirement for a centralized metadata layer?

A. EMRFS consistent view with a common Amazon DynamoDB table

B. Bootstrap action to change the Hive Metastore to an Amazon RDS database

C. s3distcp with the outputManifest option to generate RDS DDL

D. Naming scheme support with automatic partition discovery from Amazon S3

Correct Answer: A


Question 5:

An administrator needs to manage a large catalog of items from various external sellers. The administrator needs to determine if the items should be identified as minimally dangerous, dangerous, or highly dangerous based on their textual

descriptions. The administrator already has some items with the danger attribute, but receives hundreds of new item descriptions every day without such classification.

The administrator has a system that captures dangerous goods reports from customer support team or from user feedback.

What is a cost-effective architecture to solve this issue?

A. Build a set of regular expression rules that are based on the existing examples, and run them on the DynamoDB Streams as every new item description is added to the system.

B. Build a Kinesis Streams process that captures and marks the relevant items in the dangerous goods reports using a Lambda function once more than two reports have been filed.

C. Build a machine learning model to properly classify dangerous goods and run it on the DynamoDB Streams as every new item description is added to the system.

D. Build a machine learning model with binary classification for dangerous goods and run it on the DynamoDB Streams as every new item description is added to the system.

Correct Answer: C


Question 6:

A company receives data sets coming from external providers on Amazon S3. Data sets from different providers are dependent on one another. Data sets will arrive at different times and in no particular order. A data architect needs to design a solution that enables the company to do the following:

1.

Rapidly perform cross data set analysis as soon as the data becomes available

2.

Manage dependencies between data sets that arrive at different times

Which architecture strategy offers a scalable and cost-effective solution that meets these requirements?

A. Maintain data dependency information in Amazon RDS for MySQL. Use an AWS Data Pipeline job to load an Amazon EMR Hive table based on task dependencies and event notification triggers in Amazon S3.

B. Maintain data dependency information in an Amazon DynamoDB table. Use Amazon SNS and event notifications to publish data to fleet of Amazon EC2 workers. Once the task dependencies have been resolved, process the data with Amazon EMR.

C. Maintain data dependency information in an Amazon ElastiCache Redis cluster. Use Amazon S3 event notifications to trigger an AWS Lambda function that maps the S3 object to Redis. Once the task dependencies have been resolved, process the data with Amazon EMR.

D. Maintain data dependency information in an Amazon DynamoDB table. Use Amazon S3 event notifications to trigger an AWS Lambda function that maps the S3 object to the task associated with it in DynamoDB. Once all task dependencies have been resolved, process the data with Amazon EMR.

Correct Answer: C


Question 7:

A Redshift data warehouse has different user teams that need to query the same table with very different query types. These user teams are experiencing poor performance. Which action improves performance for the user teams in this situation?

A. Create custom table views.

B. Add interleaved sort keys per team.

C. Maintain team-specific copies of the table.

D. Add support for workload management queue hopping.

Correct Answer: D

Reference: https://docs.aws.amazon.com/redshift/latest/dg/cm-c-implementing-workload-management.html


Question 8:

A company operates an international business served from a single AWS region. The company wants to expand into a new country. The regulator for that country requires the Data Architect to maintain a log of financial transactions in the country within 24 hours of the product transaction. The production application is latency insensitive. The new country contains another AWS region.

What is the most cost-effective way to meet this requirement?

A. Use CloudFormation to replicate the production application to the new region.

B. Use Amazon CloudFront to serve application content locally in the country; Amazon CloudFront logs will satisfy the requirement.

C. Continue to serve customers from the existing region while using Amazon Kinesis to stream transaction data to the regulator.

D. Use Amazon S3 cross-region replication to copy and persist production transaction logs to a bucket in the new country\’s region.

Correct Answer: B


Question 9:

A social media customer has data from different data sources including RDS running MySQL, Redshift, and Hive on EMR. To support better analysis, the customer needs to be able to analyze data from different data sources and to combine the results.

What is the most cost-effective solution to meet these requirements?

A. Load all data from a different database/warehouse to S3. Use Redshift COPY command to copy data to Redshift for analysis.

B. Install Presto on the EMR cluster where Hive sits. Configure MySQL and PostgreSQL connector to select from different data sources in a single query.

C. Spin up an Elasticsearch cluster. Load data from all three data sources and use Kibana to analyze.

D. Write a program running on a separate EC2 instance to run queries to three different systems. Aggregate the results after getting the responses from all three systems.

Correct Answer: B


Question 10:

An Amazon EMR cluster using EMRFS has access to petabytes of data on Amazon S3, originating from multiple unique data sources. The customer needs to query common fields across some of the data sets to be able to perform interactive joins and then display results quickly.

Which technology is most appropriate to enable this capability?

A. Presto

B. MicroStrategy

C. Pig

D. R Studio

Correct Answer: C


Question 11:

A game company needs to properly scale its game application, which is backed by DynamoDB. Amazon Redshift has the past two years of historical data. Game traffic varies throughout the year based on various factors such as season, movie release, and holiday season. An administrator needs to calculate how much read and write throughput should be provisioned for DynamoDB table for each week in advance.

How should the administrator accomplish this task?

A. Feed the data into Amazon Machine Learning and build a regression model.

B. Feed the data into Spark Mlib and build a random forest modest.

C. Feed the data into Apache Mahout and build a multi-classification model.

D. Feed the data into Amazon Machine Learning and build a binary classification model.

Correct Answer: B


Question 12:

A large oil and gas company needs to provide near real-time alerts when peak thresholds are exceeded in its pipeline system. The company has developed a system to capture pipeline metrics such as flow rate, pressure, and temperature using millions of sensors. The sensors deliver to AWS IoT.

What is a cost-effective way to provide near real-time alerts on the pipeline metrics?

A. Create an AWS IoT rule to generate an Amazon SNS notification.

B. Store the data points in an Amazon DynamoDB table and poll if for peak metrics data from an Amazon EC2 application.

C. Create an Amazon Machine Learning model and invoke it with AWS Lambda.

D. Use Amazon Kinesis Streams and a KCL-based application deployed on AWS Elastic Beanstalk.

Correct Answer: C


Question 13:

A company is using Amazon Machine Learning as part of a medical software application. The application will predict the most likely blood type for a patient based on a variety of other clinical tests that are available when blood type knowledge

is unavailable.

What is the appropriate model choice and target attribute combination for this problem?

A. Multi-class classification model with a categorical target attribute.

B. Regression model with a numeric target attribute.

C. Binary Classification with a categorical target attribute.

D. K-Nearest Neighbors model with a multi-class target attribute.

Correct Answer: A


Question 14:

A data engineer is running a DWH on a 25-node Redshift cluster of a SaaS service. The data engineer needs to build a dashboard that will be used by customers. Five big customers represent 80% of usage, and there is a long tail of dozens of smaller customers. The data engineer has selected the dashboarding tool.

How should the data engineer make sure that the larger customer workloads do NOT interfere with the smaller customer workloads?

A. Apply query filters based on customer-id that can NOT be changed by the user and apply distribution keys on customer-id.

B. Place the largest customers into a single user group with a dedicated query queue and place the rest of the customers into a different query queue.

C. Push aggregations into an RDS for Aurora instance. Connect the dashboard application to Aurora rather than Redshift for faster queries.

D. Route the largest customers to a dedicated Redshift cluster. Raise the concurrency of the multi-tenant Redshift cluster to accommodate the remaining customers.

Correct Answer: D


Question 15:

An online photo album app has a key design feature to support multiple screens (e.g, desktop, mobile phone, and tablet) with high-quality displays. Multiple versions of the image must be saved in different resolutions and layouts. The image-processing Java program takes an average of five seconds per upload, depending on the image size and format. Each image upload captures the following image metadata: user, album, photo label, upload timestamp. The app should support the following requirements:

1.

Hundreds of user image uploads per second

2.

Maximum image upload size of 10 MB

3.

Maximum image metadata size of 1 KB

4.

Image displayed in optimized resolution in all supported screens no later than one minute after image upload Which strategy should be used to meet these requirements?

A. Write images and metadata to Amazon Kinesis. Use a Kinesis Client Library (KCL) application to run the image processing and save the image output to Amazon S3 and metadata to the app repository DB.

B. Write image and metadata RDS with BLOB data type. Use AWS Data Pipeline to run the image processing and save the image output to Amazon S3 and metadata to the app repository DB.

C. Upload image with metadata to Amazon S3, use Lambda function to run the image processing and save the images output to Amazon S3 and metadata to the app repository DB.

D. Write image and metadata to Amazon Kinesis. Use Amazon Elastic MapReduce (EMR) with Spark Streaming to run image processing and save the images output to Amazon S3 and metadata to app repository DB.

Correct Answer: C


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Question 1:

A financial services company needs to aggregate daily stock trade data from the exchanges into a data store. The company requires that data be streamed directly into the data store, but also occasionally allows data to be modified using SQL. The solution should integrate complex, analytic queries running with minimal latency. The solution must provide a business intelligence dashboard that enables viewing of the top contributors to anomalies in stock prices.

Which solution meets the company\’s requirements?

A. Use Amazon Kinesis Data Firehose to stream data to Amazon S3. Use Amazon Athena as a data source for Amazon QuickSight to create a business intelligence dashboard.

B. Use Amazon Kinesis Data Streams to stream data to Amazon Redshift. Use Amazon Redshift as a data source for Amazon QuickSight to create a business intelligence dashboard.

C. Use Amazon Kinesis Data Firehose to stream data to Amazon Redshift. Use Amazon Redshift as a data source for Amazon QuickSight to create a business intelligence dashboard.

D. Use Amazon Kinesis Data Streams to stream data to Amazon S3. Use Amazon Athena as a data source for Amazon QuickSight to create a business intelligence dashboard.

Correct Answer: D


Question 2:

A financial company hosts a data lake in Amazon S3 and a data warehouse on an Amazon Redshift cluster. The company uses Amazon QuickSight to build dashboards and wants to secure access from its on-premises Active Directory to Amazon QuickSight.

How should the data be secured?

A. Use an Active Directory connector and single sign-on (SSO) in a corporate network environment.

B. Use a VPC endpoint to connect to Amazon S3 from Amazon QuickSight and an IAM role to authenticate Amazon Redshift.

C. Establish a secure connection by creating an S3 endpoint to connect Amazon QuickSight and a VPC endpoint to connect to Amazon Redshift.

D. Place Amazon QuickSight and Amazon Redshift in the security group and use an Amazon S3 endpoint to connect Amazon QuickSight to Amazon S3.

Correct Answer: B


Question 3:

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. 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.

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. 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.

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.

Correct Answer: C

Reference: https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-hbase-s3.html


Question 4:

A software company hosts an application on AWS, and new features are released weekly. As part of the application testing process, a solution must be developed that analyzes logs from each Amazon EC2 instance to ensure that the application is working as expected after each deployment. The collection and analysis solution should be highly available with the ability to display new information with minimal delays.

Which method should the company use to collect and analyze the logs?

A. Enable detailed monitoring on Amazon EC2, use Amazon CloudWatch agent to store logs in Amazon S3, and use Amazon Athena for fast, interactive log analytics.

B. Use the Amazon Kinesis Producer Library (KPL) agent on Amazon EC2 to collect and send data to Kinesis Data Streams to further push the data to Amazon OpenSearch Service (Amazon Elasticsearch Service) and visualize using Amazon QuickSight.

C. Use the Amazon Kinesis Producer Library (KPL) agent on Amazon EC2 to collect and send data to Kinesis Data Firehose to further push the data to Amazon OpenSearch Service (Amazon Elasticsearch Service) and OpenSearch Dashboards (Kibana).

D. Use Amazon CloudWatch subscriptions to get access to a real-time feed of logs and have the logs delivered to Amazon Kinesis Data Streams to further push the data to Amazon OpenSearch Service (Amazon Elasticsearch Service) and OpenSearch Dashboards (Kibana).

Correct Answer: D

Reference: https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/Subscriptions.html


Question 5:

A data analyst is using AWS Glue to organize, cleanse, validate, and format a 200 GB dataset. The data analyst triggered the job to run with the Standard worker type. After 3 hours, the AWS Glue job status is still RUNNING. Logs from the job run show no error codes. The data analyst wants to improve the job execution time without overprovisioning.

Which actions should the data analyst take?

A. Enable job bookmarks in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the executor-cores job parameter.

B. Enable job metrics in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the maximum capacity job parameter.

C. Enable job metrics in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the spark.yarn.executor.memoryOverhead job parameter.

D. Enable job bookmarks in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the num-executors job parameter.

Correct Answer: B

Reference: https://docs.aws.amazon.com/glue/latest/dg/monitor-debug-capacity.html


Question 6:

A company has a business unit uploading .csv files to an Amazon S3 bucket. The company\’s data platform team has set up an AWS Glue crawler to do discovery, and create tables and schemas. An AWS Glue job writes processed data from the created tables to an Amazon Redshift database. The AWS Glue job handles column mapping and creating the Amazon Redshift table appropriately. When the AWS Glue job is rerun for any reason in a day, duplicate records are introduced into the Amazon Redshift table.

Which solution will update the Redshift table without duplicates when jobs are rerun?

A. Modify the AWS Glue job to copy the rows into a staging table. Add SQL commands to replace the existing rows in the main table as postactions in the DynamicFrameWriter class.

B. Load the previously inserted data into a MySQL database in the AWS Glue job. Perform an upsert operation in MySQL, and copy the results to the Amazon Redshift table.

C. Use Apache Spark\’s DataFrame dropDuplicates() API to eliminate duplicates and then write the data to Amazon Redshift.

D. Use the AWS Glue ResolveChoice built-in transform to select the most recent value of the column.

Correct Answer: B


Question 7:

A streaming application is reading data from Amazon Kinesis Data Streams and immediately writing the data to an Amazon S3 bucket every 10 seconds. The application is reading data from hundreds of shards. The batch interval cannot be changed due to a separate requirement. The data is being accessed by Amazon Athena. Users are seeing degradation in query performance as time progresses.

Which action can help improve query performance?

A. Merge the files in Amazon S3 to form larger files.

B. Increase the number of shards in Kinesis Data Streams.

C. Add more memory and CPU capacity to the streaming application.

D. Write the files to multiple S3 buckets.

Correct Answer: C


Question 8:

A company uses Amazon OpenSearch Service (Amazon Elasticsearch Service) to store and analyze its website clickstream data. The company ingests 1 TB of data daily using Amazon Kinesis Data Firehose and stores one day\’s worth of

data in an Amazon ES cluster.

The company has very slow query performance on the Amazon ES index and occasionally sees errors from Kinesis Data Firehose when attempting to write to the index. The Amazon ES cluster has 10 nodes running a single index and 3

dedicated master nodes. Each data node has 1.5 TB of Amazon EBS storage attached and the cluster is configured with 1,000 shards. Occasionally, JVMMemoryPressure errors are found in the cluster logs.

Which solution will improve the performance of Amazon ES?

A. Increase the memory of the Amazon ES master nodes.

B. Decrease the number of Amazon ES data nodes.

C. Decrease the number of Amazon ES shards for the index.

D. Increase the number of Amazon ES shards for the index.

Correct Answer: C


Question 9:

A manufacturing company has been collecting IoT sensor data from devices on its factory floor for a year and is storing the data in Amazon Redshift for daily analysis. A data analyst has determined that, at an expected ingestion rate of about 2 TB per day, the cluster will be undersized in less than 4 months. A long-term solution is needed. The data analyst has indicated that most queries only reference the most recent 13 months of data, yet there are also quarterly reports that need to query all the data generated from the past 7 years. The chief technology officer (CTO) is concerned about the costs, administrative effort, and performance of a long-term solution.

Which solution should the data analyst use to meet these requirements?

A. Create a daily job in AWS Glue to UNLOAD records older than 13 months to Amazon S3 and delete those records from Amazon Redshift. Create an external table in Amazon Redshift to point to the S3 location. Use Amazon Redshift Spectrum to join to data that is older than 13 months.

B. Take a snapshot of the Amazon Redshift cluster. Restore the cluster to a new cluster using dense storage nodes with additional storage capacity.

C. Execute a CREATE TABLE AS SELECT (CTAS) statement to move records that are older than 13 months to quarterly partitioned data in Amazon Redshift Spectrum backed by Amazon S3.

D. Unload all the tables in Amazon Redshift to an Amazon S3 bucket using S3 Intelligent-Tiering. Use AWS Glue to crawl the S3 bucket location to create external tables in an AWS Glue Data Catalog. Create an Amazon EMR cluster using Auto Scaling for any daily analytics needs, and use Amazon Athena for the quarterly reports, with both using the same AWS Glue Data Catalog.

Correct Answer: B


Question 10:

An insurance company has raw data in JSON format that is sent without a predefined schedule through an Amazon Kinesis Data Firehose delivery stream to an Amazon S3 bucket. An AWS Glue crawler is scheduled to run every 8 hours to update the schema in the data catalog of the tables stored in the S3 bucket. Data analysts analyze the data using Apache Spark SQL on Amazon EMR set up with AWS Glue Data Catalog as the metastore. Data analysts say that, occasionally, the data they receive is stale. A data engineer needs to provide access to the most up-to-date data.

Which solution meets these requirements?

A. Create an external schema based on the AWS Glue Data Catalog on the existing Amazon Redshift cluster to query new data in Amazon S3 with Amazon Redshift Spectrum.

B. Use Amazon CloudWatch Events with the rate (1 hour) expression to execute the AWS Glue crawler every hour.

C. Using the AWS CLI, modify the execution schedule of the AWS Glue crawler from 8 hours to 1 minute.

D. Run the AWS Glue crawler from an AWS Lambda function triggered by an S3:ObjectCreated:* event notification on the S3 bucket.

Correct Answer: A


Question 11:

A company that produces network devices has millions of users. Data is collected from the devices on an hourly basis and stored in an Amazon S3 data lake.

The company runs analyses on the last 24 hours of data flow logs for abnormality detection and to troubleshoot and resolve user issues. The company also analyzes historical logs dating back 2 years to discover patterns and look for improvement opportunities.

The data flow logs contain many metrics, such as date, timestamp, source IP, and target IP. There are about 10 billion events every day.

How should this data be stored for optimal performance?

A. In Apache ORC partitioned by date and sorted by source IP

B. In compressed .csv partitioned by date and sorted by source IP

C. In Apache Parquet partitioned by source IP and sorted by date

D. In compressed nested JSON partitioned by source IP and sorted by date

Correct Answer: D


Question 12:

A banking company is currently using an Amazon Redshift cluster with dense storage (DS) nodes to store sensitive data. An audit found that the cluster is unencrypted. Compliance requirements state that a database with sensitive data must be encrypted through a hardware security module (HSM) with automated key rotation.

Which combination of steps is required to achieve compliance? (Choose two.)

A. Set up a trusted connection with HSM using a client and server certificate with automatic key rotation.

B. Modify the cluster with an HSM encryption option and automatic key rotation.

C. Create a new HSM-encrypted Amazon Redshift cluster and migrate the data to the new cluster.

D. Enable HSM with key rotation through the AWS CLI.

E. Enable Elliptic Curve Diffie-Hellman Ephemeral (ECDHE) encryption in the HSM.

Correct Answer: BD

Reference: https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-db-encryption.html


Question 13:

A company is planning to do a proof of concept for a machine learning (ML) project using Amazon SageMaker with a subset of existing on-premises data hosted in the company\’s 3 TB data warehouse. For part of the project, AWS Direct Connect is established and tested. To prepare the data for ML, data analysts are performing data curation. The data analysts want to perform multiple step, including mapping, dropping null fields, resolving choice, and splitting fields. The company needs the fastest solution to curate the data for this project.

Which solution meets these requirements?

A. Ingest data into Amazon S3 using AWS DataSync and use Apache Spark scrips to curate the data in an Amazon EMR cluster. Store the curated data in Amazon S3 for ML processing.

B. Create custom ETL jobs on-premises to curate the data. Use AWS DMS to ingest data into Amazon S3 for ML processing.

C. Ingest data into Amazon S3 using AWS DMS. Use AWS Glue to perform data curation and store the data in Amazon S3 for ML processing.

D. Take a full backup of the data store and ship the backup files using AWS Snowball. Upload Snowball data into Amazon S3 and schedule data curation jobs using AWS Batch to prepare the data for ML.

Correct Answer: C


Question 14:

A US-based sneaker retail company launched its global website. All the transaction data is stored in Amazon RDS and curated historic transaction data is stored in Amazon Redshift in the us-east-1 Region. The business intelligence (BI) team wants to enhance the user experience by providing a dashboard for sneaker trends.

The BI team decides to use Amazon QuickSight to render the website dashboards. During development, a team in Japan provisioned Amazon QuickSight in ap-northeast-1. The team is having difficulty connecting Amazon QuickSight from ap-northeast-1 to Amazon Redshift in us-east-1.

Which solution will solve this issue and meet the requirements?

A. In the Amazon Redshift console, choose to configure cross-Region snapshots and set the destination Region as ap-northeast-1. Restore the Amazon Redshift Cluster from the snapshot and connect to Amazon QuickSight launched in apnortheast-1.

B. Create a VPC endpoint from the Amazon QuickSight VPC to the Amazon Redshift VPC so Amazon QuickSight can access data from Amazon Redshift.

C. Create an Amazon Redshift endpoint connection string with Region information in the string and use this connection string in Amazon QuickSight to connect to Amazon Redshift.

D. Create a new security group for Amazon Redshift in us-east-1 with an inbound rule authorizing access from the appropriate IP address range for the Amazon QuickSight servers in ap-northeast-1.

Correct Answer: B


Question 15:

An airline has .csv-formatted data stored in Amazon S3 with an AWS Glue Data Catalog. Data analysts want to join this data with call center data stored in Amazon Redshift as part of a dally batch process. The Amazon Redshift cluster is already under a heavy load. The solution must be managed, serverless, well-functioning, and minimize the load on the existing Amazon Redshift cluster. The solution should also require minimal effort and development activity.

Which solution meets these requirements?

A. Unload the call center data from Amazon Redshift to Amazon S3 using an AWS Lambda function. Perform the join with AWS Glue ETL scripts.

B. Export the call center data from Amazon Redshift using a Python shell in AWS Glue. Perform the join with AWS Glue ETL scripts.

C. Create an external table using Amazon Redshift Spectrum for the call center data and perform the join with Amazon Redshift.

D. Export the call center data from Amazon Redshift to Amazon EMR using Apache Sqoop. Perform the join with Apache Hive.

Correct Answer: C