Amazon Amazon Certifications DAS-C01 Questions & Answers

• Question 111:

  A technology company has an application with millions of active users every day. The company queries daily usage data with Amazon Athena to understand how users interact with the application. The data includes the date and time, the location ID, and the services used. The company wants to use Athena to run queries to analyze the data with the lowest latency possible.

  Which solution meets these requirements?

  A. Store the data in Apache Avro format with the date and time as the partition, with the data sorted by the location ID.

  B. Store the data in Apache Parquet format with the date and time as the partition, with the data sorted by the location ID.

  C. Store the data in Apache ORC format with the location ID as the partition, with the data sorted by the date and time.

  D. Store the data in .csv format with the location ID as the partition, with the data sorted by the date and time.

  Correct Answer: B

  Reference: https://cwiki.apache.org/confluence/display/hive/languagemanual+orc

• Question 112:

  A real estate company maintains data about all properties listed in a market. The company receives data about new property listings from vendors who upload the data daily as compressed files into Amazon S3. The company's leadership team wants to see the most up-to-date listings as soon as the data is uploaded to Amazon S3. The data analytics team must automate and orchestrate the data processing workflow of the listings to feed a dashboard. The team also must provide the ability to perform one-time queries and analytical reporting in a scalable manner.

  Which solution meets these requirements MOST cost-effectively?

  A. Use Amazon EMR for processing incoming data. Use AWS Step Functions for workflow orchestration. Use Apache Hive for one-time queries and analytical reporting. Bulk ingest the data in Amazon OpenSearch Service (Amazon Elasticsearch Service). Use OpenSearch Dashboards (Kibana) on Amazon OpenSearch Service (Amazon Elasticsearch Service) for the dashboard.

  B. Use Amazon EMR for processing incoming data. Use AWS Step Functions for workflow orchestration. Use Amazon Athena for one-time queries and analytical reporting. Use Amazon QuickSight for the dashboard.

  C. Use AWS Glue for processing incoming data. Use AWS Step Functions for workflow orchestration. Use Amazon Redshift Spectrum for one-time queries and analytical reporting. Use OpenSearch Dashboards (Kibana) on Amazon OpenSearch Service (Amazon Elasticsearch Service) for the dashboard.

  D. Use AWS Glue for processing incoming data. Use AWS Lambda and S3 Event Notifications for workflow orchestration. Use Amazon Athena for one-time queries and analytical reporting. Use Amazon QuickSight for the dashboard.

  Correct Answer: B

  Reference: https://aws.amazon.com/blogs/compute/visualizing-aws-step-functions-workflows-from-the-amazon-athena-console/

• Question 113:

  A company hosts an Apache Flink application on premises. The application processes data from several Apache Kafka clusters. The data originates from a variety of sources, such as web applications, mobile apps, and operational databases. The company has migrated some of these sources to AWS and now wants to migrate the Flink application. The company must ensure that data that resides in databases within the VPC does not traverse the internet. The application must be able to process all the data that comes from the company's AWS solution, on-premises resources, and the public internet.

  Which solution will meet these requirements with the LEAST operational overhead?

  A. Implement Flink on Amazon EC2 within the company's VPC. Create Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in the VPC to collect data that comes from applications and databases within the VPC. Use Amazon Kinesis Data Streams to collect data that comes from the public internet. Configure Flink to have sources from Kinesis Data Streams Amazon MSK, and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect.

  B. Implement Flink on Amazon EC2 within the company's VPC. Use Amazon Kinesis Data Streams to collect data that comes from applications and databases within the VPC and the public internet. Configure Flink to have sources from Kinesis Data Streams and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect.

  C. Create an Amazon Kinesis Data Analytics application by uploading the compiled Flink .jar file. Use Amazon Kinesis Data Streams to collect data that comes from applications and databases within the VPC and the public internet. Configure the Kinesis Data Analytics application to have sources from Kinesis Data Streams and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect.

  D. Create an Amazon Kinesis Data Analytics application by uploading the compiled Flink .jar file. Create Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in the company's VPC to collect data that comes from applications and databases within the VPC. Use Amazon Kinesis Data Streams to collect data that comes from the public internet. Configure the Kinesis Data Analytics application to have sources from Kinesis Data Streams, Amazon MSK, and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect.

  Correct Answer: C

  Reference: https://aws.amazon.com/blogs/big-data/streaming-etl-with-apache-flink-and-amazon-kinesis-data-analytics/ https://docs.aws.amazon.com/streams/latest/dev/vpc.html

• Question 114:

  A company uses Amazon Redshift as its data warehouse. A new table includes some columns that contain sensitive data and some columns that contain non-sensitive data. The data in the table eventually will be referenced by several existing queries that run many times each day.

  A data analytics specialist must ensure that only members of the company's auditing team can read the columns that contain sensitive data. All other users must have read-only access to the columns that contain non-sensitive data.

  Which solution will meet these requirements with the LEAST operational overhead?

  A. Grant the auditing team permission to read from the table. Load the columns that contain non-sensitive data into a second table. Grant the appropriate users read-only permissions to the second table.

  B. Grant all users read-only permissions to the columns that contain non-sensitive data. Use the GRANT SELECT command to allow the auditing team to access the columns that contain sensitive data.

  C. Grant all users read-only permissions to the columns that contain non-sensitive data. Attach an IAM policy to the auditing team with an explicit. Allow action that grants access to the columns that contain sensitive data.

  D. Grant the auditing team permission to read from the table. Create a view of the table that includes the columns that contain non-sensitive data. Grant the appropriate users read-only permissions to that view.

  Correct Answer: D

  Users with SELECT permission on a table can view the table data. Columns that are defined as masked, will display the masked data. Grant the UNMASK permission to a user to enable them to retrieve unmasked data from the columns for which masking is defined.

  Reference: https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking?view=sql-server-ver15

• Question 115:

  An online retail company is using Amazon Redshift to run queries and perform analytics on customer shopping behavior. When multiple queries are running on the cluster, runtime for small queries increases significantly. The company's data analytics team to decrease the runtime of these small queries by prioritizing them ahead of large queries.

  Which solution will meet these requirements?

  A. Use Amazon Redshift Spectrum for small queries

  B. Increase the concurrency limit in workload management (WLM)

  C. Configure short query acceleration in workload management (WLM)

  D. Add a dedicated compute node for small queries

  Correct Answer: C

  Short query acceleration (SQA) prioritizes selected short-running queries ahead of longer-running queries. SQA executes short-running queries in a dedicated space, so that SQA queries aren't forced to wait in queues behind longer queries.

  Reference: https://docs.aws.amazon.com/redshift/latest/mgmt/workload-mgmt-config.html

• Question 116:

  A company has multiple data workflows to ingest data from its operational databases into its data lake on Amazon S3. The workflows use AWS Glue and Amazon EMR for data processing and ETL. The company wants to enhance its architecture to provide automated orchestration and minimize manual intervention.

  Which solution should the company use to manage the data workflows to meet these requirements?

  A. AWS Glue workflows

  B. AWS Step Functions

  C. AWS Lambda

  D. AWS Batch

  Correct Answer: D

  Reference: https://aws.amazon.com/batch/use-cases/

• Question 117:

  A web retail company wants to implement a near-real-time clickstream analytics solution. The company wants to analyze the data with an open-source package. The analytics application will process the raw data only once, but other applications will need immediate access to the raw data for up to 1 year.

  Which solution meets these requirements with the LEAST amount of operational effort?

  A. Use Amazon Kinesis Data Streams to collect the data. Use Amazon EMR with Apache Flink to consume and process the data from the Kinesis data stream. Set the retention period of the Kinesis data stream to 8.760 hours.

  B. Use Amazon Kinesis Data Streams to collect the data. Use Amazon Kinesis Data Analytics with Apache Flink to process the data in real time. Set the retention period of the Kinesis data stream to 8,760 hours.

  C. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to collect the data. Use Amazon EMR with Apache Flink to consume and process the data from the Amazon MSK stream. Set the log retention hours to 8,760.

  D. Use Amazon Kinesis Data Streams to collect the data. Use Amazon EMR with Apache Flink to consume and process the data from the Kinesis data stream. Create an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Set an S3 Lifecycle policy to delete the data after 365 days.

  Correct Answer: B

  Reference: https://docs.aws.amazon.com/streams/latest/dev/kinesis-dg.pdf

• Question 118:

  A data analyst runs a large number of data manipulation language (DML) queries by using Amazon Athena with the JDBC driver. Recently, a query failed after it ran for 30 minutes. The query returned the following message:

  java.sql.SQLException: Query timeout

  The data analyst does not immediately need the query results. However, the data analyst needs a long-term solution for this problem.

  Which solution will meet these requirements?

  A. Split the query into smaller queries to search smaller subsets of data

  B. In the settings for Athena, adjust the DML query timeout limit

  C. In the Service Quotas console, request an increase for the DML query timeout

  D. Save the tables as compressed .csv files

  Correct Answer: C

  Reference: https://docs.aws.amazon.com/athena/latest/ug/service-limits.html

• Question 119:

  A retail company is using an Amazon S3 bucket to host an ecommerce data lake. The company is using AWS Lake Formation to manage the data lake.

  A data analytics specialist must provide access to a new business analyst team. The team will use Amazon Athena from the AWS Management Console to query data from existing web_sales and customer tables in the ecommerce database. The team needs read-only access and the ability to uniquely identify customers by using first and last names. However, the team must not be able to see any other personally identifiable data. The table structure is as follows:

  

  Which combination of steps should the data analytics specialist take to provide the required permission by using the principle of least privilege? (Choose three.)

  A. In AWS Lake Formation, grant the business_analyst group SELECT and ALTER permissions for the web_sales table.

  B. In AWS Lake Formation, grant the business_analyst group the SELECT permission for the web_sales table.

  C. In AWS Lake Formation, grant the business_analyst group the SELECT permission for the customer table. Under columns, choose filter type "Include columns" with columns fisrt_name, last_name, and customer_id.

  D. In AWS Lake Formation, grant the business_analyst group SELECT and ALTER permissions for the customer table. Under columns, choose filter type "Include columns" with columns fisrt_name and last_name.

  E. Create users under a business_analyst IAM group. Create a policy that allows the lakeformation:GetDataAccess action, the athena:* action, and the glue:Get* action.

  F. Create users under a business_analyst IAM group. Create a policy that allows the lakeformation:GetDataAccess action, the athena:* action, and the glue:Get* action. In addition, allow the s3:GetObject action, the s3:PutObject action, and the s3:GetBucketLocation action for the Athena query results S3 bucket.

  Correct Answer: BCF

  Reference: https://docs.aws.amazon.com/athena/latest/ug/querying.html

• Question 120:

  A company is providing analytics services to its sales and marketing departments. The departments can access the data only through their business intelligence (BI) tools, which run queries on Amazon Redshift using an Amazon Redshift internal user to connect. Each department is assigned a user in the Amazon Redshift database with the permissions needed for that department. The marketing data analysts must be granted direct access to the advertising table, which is stored in Apache Parquet format in the marketing S3 bucket of the company data lake. The company data lake is managed by AWS Lake Formation. Finally, access must be limited to the three promotion columns in the table.

  Which combination of steps will meet these requirements? (Choose three.)

  A. Grant permissions in Amazon Redshift to allow the marketing Amazon Redshift user to access the three promotion columns of the advertising external table.

  B. Create an Amazon Redshift Spectrum IAM role with permissions for Lake Formation. Attach it to the Amazon Redshift cluster.

  C. Create an Amazon Redshift Spectrum IAM role with permissions for the marketing S3 bucket. Attach it to the Amazon Redshift cluster.

  D. Create an external schema in Amazon Redshift by using the Amazon Redshift Spectrum IAM role. Grant usage to the marketing Amazon Redshift user.

  E. Grant permissions in Lake Formation to allow the Amazon Redshift Spectrum role to access the three promotion columns of the advertising table.

  F. Grant permissions in Lake Formation to allow the marketing IAM group to access the three promotion columns of the advertising table.

  Correct Answer: BDE