Quiz IT certification exam

Question 1

A company using Amazon QuickSight Enterprise edition has thousands of dashboards, analyses, and datasets. The company struggles to manage and assign permissions for granting users access to various items within QuickSight. The company wants to make it easier to implement sharing and permissions management. Which solution should the company implement to simplify permissions management?

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Accepted Answer

Use QuickSight folders to organize dashboards, analyses, and datasets. Assign group permissions by using these folders.

Answer

Use QuickSight folders to organize dashboards, analyses, and datasets. Assign individual users permissions to these folders.

Answer

Use AWS IAM resource-based policies to assign group permissions to QuickSight items.

Answer

Use QuickSight user management APIs to provision group permissions based on dashboard naming conventions.

Question 2

A company launched a service that produces millions of messages every day and uses Amazon Kinesis Data Streams as the streaming service.The company uses the Kinesis SDK to write data to Kinesis Data Streams. A few months after launch, a data analyst found that write performance is significantly reduced. The data analyst investigated the metrics and determined that Kinesis is throttling the write requests. The data analyst wants to address this issue without significant changes to the architecture. Which actions should the data analyst take to resolve this issue? (Choose two.)

Accepted Answer

Increase the Kinesis Data Streams retention period to reduce throttling.

Accepted Answer

Increase the number of shards in the stream using the UpdateShardCount API.

Answer

Replace the Kinesis API-based data ingestion mechanism with Kinesis Agent.

Answer

Choose partition keys in a way that results in a uniform record distribution across shards.

Answer

Customize the application code to include retry logic to improve performance.

Question 3

A transportation company uses IoT sensors attached to trucks to collect vehicle data for its global delivery fleet. The company currently sends the sensor data in small .csv files to Amazon S3. The files are then loaded into a 10-node Amazon Redshift cluster with two slices per node and queried using both Amazon Athena and Amazon Redshift. The company wants to optimize the files to reduce the cost of querying and also improve the speed of data loading into the Amazon Redshift cluster.Which solution meets these requirements?

Accepted Answer

Use AWS Glue to convert the files from .csv to Apache Parquet to create 20 Parquet files. COPY the files into Amazon Redshift and query the files with Athena from Amazon S3.

Answer

Use AWS Glue to convert all the files from .csv to a single large Apache Parquet file. COPY the file into Amazon Redshift and query the file with Athena from Amazon S3.

Answer

Use Amazon EMR to convert each .csv file to Apache Avro. COPY the files into Amazon Redshift and query the file with Athena from Amazon S3.

Answer

Use AWS Glue to convert the files from .csv to a single large Apache ORC file. COPY the file into Amazon Redshift and query the file with Athena from Amazon S3.

Question 4

A data analytics specialist is building an automated ETL ingestion pipeline using AWS Glue to ingest compressed files that have been uploaded to an Amazon S3 bucket. The ingestion pipeline should support incremental data processing. Which AWS Glue feature should the data analytics specialist use to meet this requirement?

Accepted Answer

Triggers

Answer

Workflows

Answer

Job bookmarks

Answer

Classifiers

Question 5

A company developed a new elections reporting website that uses Amazon Kinesis Data Firehose to deliver full logs from AWS WAF to an Amazon S3 bucket. The company is now seeking a low-cost option to perform this infrequent data analysis with visualizations of logs in a way that requires minimal development effort. Which solution meets these requirements?

Accepted Answer

Create an Amazon EMR cluster and use Amazon S3 as the data source. Create an Apache Spark job to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.

Answer

Use an AWS Glue crawler to create and update a table in the Glue data catalog from the logs. Use Athena to perform adhoc analyses and use Amazon QuickSight to develop data visualizations.

Answer

Create a second Kinesis Data Firehose delivery stream to deliver the log files to Amazon OpenSearch Service (Amazon Elasticsearch Service). Use Amazon ES to perform text-based searches of the logs for ad-hoc analyses and useOpenSearch Dashboards (Kibana) for data visualizations.

Answer

Create an AWS Lambda function to convert the logs into .csv format. Then add the function to the Kinesis Data Firehose transformation configuration. Use Amazon Redshift to perform ad-hoc analyses of the logs using SQL queries anduse Amazon QuickSight to develop data visualizations.

Question 6

A bank operates in a regulated environment. The compliance requirements for the country in which the bank operates say that customer data for each state should only be accessible by the bank’s employees located in the same state. Bank employees in one state should NOT be able to access data for customers who have provided a home address in a different state.The bank’s marketing team has hired a data analyst to gather insights from customer data for a new campaign being launched in certain states. Currently, data linking each customer account to its home state is stored in a tabular .csv file within a single Amazon S3 folder in a private S3 bucket. The total size of the S3 folder is 2 GB uncompressed. Due to the country’s compliance requirements, the marketing team is not able to access this folder.The data analyst is responsible for ensuring that the marketing team gets one-time access to customer data for their campaign analytics project, while being subject to all the compliance requirements and controls.Which solution should the data analyst implement to meet the desired requirements with the LEAST amount of setup effort?

Accepted Answer

Load tabular data from Amazon S3 to Amazon Redshift with the COPY command. Use the built-in row-level security feature in Amazon Redshift to provide marketing employees with appropriate data access under compliance controls. Delete the Amazon Redshift tables after the project.

Answer

Re-arrange data in Amazon S3 to store customer data about each state in a different S3 folder within the same bucket.Set up S3 bucket policies to provide marketing employees with appropriate data access under compliance controls. Delete the bucket policies after the project.

Answer

Load tabular data from Amazon S3 to an Amazon EMR cluster using s3DistCp. Implement a custom Hadoop-based rowlevel security solution on the Hadoop Distributed File System (HDFS) to provide marketing employees withappropriate data access under compliance controls. Terminate the EMR cluster after the project.

Answer

Load tabular data from Amazon S3 to Amazon QuickSight Enterprise edition by directly importing it as a data source. Use the built-in row-level security feature in Amazon QuickSight to provide marketing employees with appropriate dataaccess under compliance controls. Delete Amazon QuickSight data sources after the project is complete.

Question 7

A transport company wants to track vehicular movements by capturing geolocation records. The records are 10 B in size and up to 10,000 records are captured each second. Data transmission delays of a few minutes are acceptable, considering unreliable network conditions. The transport company decided to use Amazon Kinesis Data Streams to ingest the data. The company is looking for a reliable mechanism to send data to Kinesis Data Streams while maximizing the throughput efficiency of the Kinesis shards. Which solution will meet the company’s requirements?

Accepted Answer

Kinesis Producer Library (KPL)

Answer

Kinesis Agent

Answer

Kinesis Data Firehose

Answer

Kinesis SDK

Question 8

A power utility company is deploying thousands of smart meters to obtain real-time updates about power consumption. The company is using Amazon Kinesis Data Streams to collect the data streams from smart meters. The consumer application uses the Kinesis Client Library (KCL) to retrieve the stream data. The company has only one consumer application.The company observes an average of 1 second of latency from the moment that a record is written to the stream until the record is read by a consumer application. The company must reduce this latency to 500 milliseconds. Which solution meets these requirements?

Accepted Answer

Reduce the propagation delay by overriding the KCL default settings.

Answer

Use enhanced fan-out in Kinesis Data Streams.

Answer

Increase the number of shards for the Kinesis data stream.

Answer

Develop consumers by using Amazon Kinesis Data Firehose.

Question 9

A company has a marketing department and a finance department. The departments are storing data in Amazon S3 in their own AWS accounts in AWS Organizations. Both departments use AWS Lake Formation to catalog and secure their data.The departments have some databases and tables that share common names.The marketing department needs to securely access some tables from the finance department. Which two steps are required for this process? (Choose two.)

Accepted Answer

The finance department grants Lake Formation permissions for the tables to the external account for the marketing department.

Accepted Answer

The finance department creates cross-account IAM permissions to the table for the marketing department role.

Answer

The marketing department creates an IAM role that has permissions to the Lake Formation tables.

Question 10

A data analyst is designing a solution to interactively query datasets with SQL using a JDBC connection. Users will join data stored in Amazon S3 in Apache ORC format with data stored in Amazon OpenSearch Service (Amazon Elasticsearch Service) and Amazon Aurora MySQL.Which solution will provide the MOST up-to-date results?

Accepted Answer

Query all the datasets in place with Apache Spark SQL running on an AWS Glue developer endpoint.

Answer

Use AWS Glue jobs to ETL data from Amazon ES and Aurora MySQL to Amazon S3. Query the data with Amazon Athena.

Answer

Use Amazon DMS to stream data from Amazon ES and Aurora MySQL to Amazon Redshift. Query the data with Amazon Redshift.

Answer

Query all the datasets in place with Apache Presto running on Amazon EMR.

Question 11

An online retailer needs to deploy a product sales reporting solution. The source data is exported from an external online transaction processing (OLTP) system for reporting. Roll-up data is calculated each day for the previous day’s activities. The reporting system has the following requirements:Have the daily roll-up data readily available for 1 year.After 1 year, archive the daily roll-up data for occasional but immediate access.The source data exports stored in the reporting system must be retained for 5 years. Query access will be needed only for re-evaluation, which may occur within the first 90 days. Which combination of actions will meet these requirements while keeping storage costs to a minimum? (Choose two.)

Accepted Answer

Store the source data initially in the Amazon S3 Glacier storage class. Apply a lifecycle configuration that changes the storage class from Amazon S3 Glacier to Amazon S3 Glacier Deep Archive 90 days after creation, and then deletes the data 5 years after creation.

Accepted Answer

Store the daily roll-up data initially in the Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage class. Apply a lifecycle configuration that changes the storage class to Amazon S3 Glacier 1 year after data creation.

Answer

Store the source data initially in the Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage class. Apply a lifecycle configuration that changes the storage class to Amazon S3 Glacier Deep Archive 90 days after creation, and then deletes the data 5 years after creation.

Answer

Store the daily roll-up data initially in the Amazon S3 Standard storage class. Apply a lifecycle configuration that changes the storage class to Amazon S3 Glacier Deep Archive 1 year after data creation.

Answer

Store the daily roll-up data initially in the Amazon S3 Standard storage class. Apply a lifecycle configuration that changes the storage class to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) 1 year after data creation.

Question 12

A large university has adopted a strategic goal of increasing diversity among enrolled students. The data analytics team is creating a dashboard with data visualizations to enable stakeholders to view historical trends. All access must be authenticated using Microsoft Active Directory. All data in transit and at rest must be encrypted. Which solution meets these requirements?

Accepted Answer

Amazon QuickSight Enterprise edition using AD Connector to authenticate using Active Directory. Configure Amazon QuickSight to use customer-provided keys imported into AWS KMS.

Answer

Amazon QuickSight Standard edition configured to perform identity federation using SAML 2.0. and the default encryption settings.

Answer

Amazon QuickSight Enterprise edition configured to perform identity federation using SAML 2.0 and the default encryption settings.

Answer

Amazon QuckSight Standard edition using AD Connector to authenticate using Active Directory. Configure Amazon QuickSight to use customer-provided keys imported into AWS KMS.

Question 13

A data analytics specialist is setting up workload management in manual mode for an Amazon Redshift environment. The data analytics specialist is defining query monitoring rules to manage system performance and user experience of an Amazon Redshift cluster.Which elements must each query monitoring rule include?

Accepted Answer

A unique rule name, one to three predicates, and an action

Answer

A unique rule name, a query runtime condition, and an AWS Lambda function to resubmit any failed queries in off hours

Answer

A queue name, a unique rule name, and a predicate-based stop condition

Answer

A workload name, a unique rule name, and a query runtime-based condition

Question 14

A large company receives files from external parties in Amazon EC2 throughout the day. At the end of the day, the files are combined into a single file, compressed into a gzip file, and uploaded to Amazon S3. The total size of all the files is close to 100 GB daily. Once the files are uploaded to Amazon S3, an AWS Batch program executes a COPY command to load the files into an Amazon Redshift cluster. Which program modification will accelerate the COPY process?

Accepted Answer

Split the number of files so they are equal to a multiple of the number of slices in the Amazon Redshift cluster. Gzip and upload the files to Amazon S3. Run the COPY command on the files.

Answer

Upload the individual files to Amazon S3 and run the COPY command as soon as the files become available.

Answer

Split the number of files so they are equal to a multiple of the number of compute nodes in the Amazon Redshift cluster.Gzip and upload the files to Amazon S3. Run the COPY command on the files.

Answer

Apply sharding by breaking up the files so the distkey columns with the same values go to the same file. Gzip and upload the sharded files to Amazon S3. Run the COPY command on the files.

Question 15

A machinery company wants to collect data from sensors. A data analytics specialist needs to implement a solution that aggregates the data in near-real time and saves the data to a persistent data store. The data must be stored in nested JSON format and must be queried from the data store with a latency of single-digit milliseconds. Which solution will meet these requirements?

Accepted Answer

Use Amazon Kinesis Data Streams to receive the data from the sensors. Use Amazon Kinesis Data Analytics to read the stream, aggregate the data, and send the data to an AWS Lambda function. Configure the Lambda function tostore the data in Amazon DynamoDB.

Answer

Use Amazon Kinesis Data Firehose to receive the data from the sensors. Use Amazon Kinesis Data Analytics to aggregate the data. Use an AWS Lambda function to read the data from Kinesis Data Analytics and store the data inAmazon S3.

Answer

Use Amazon Kinesis Data Firehose to receive the data from the sensors. Use an AWS Lambda function to aggregate the data during capture. Store the data from Kinesis Data Firehose in Amazon DynamoDB.

Answer

Use Amazon Kinesis Data Firehose to receive the data from the sensors. Use an AWS Lambda function to aggregate the data during capture. Store the data in Amazon S3.

Question 16

A manufacturing company uses Amazon Connect to manage its contact center and Salesforce to manage its customer relationship management (CRM) data. The data engineering team must build a pipeline to ingest data from the contact center and CRM system into a data lake that is built on Amazon S3.What is the MOST efficient way to collect data in the data lake with the LEAST operational overhead?

Accepted Answer

Use Amazon Kinesis Data Firehose to ingest Amazon Connect data and Amazon Kinesis Data Streams to ingest Salesforce data.

Answer

Use Amazon Kinesis Data Streams to ingest Amazon Connect data and Amazon AppFlow to ingest Salesforce data.

Answer

Use Amazon Kinesis Data Firehose to ingest Amazon Connect data and Amazon AppFlow to ingest Salesforce data.

Answer

Use Amazon AppFlow to ingest Amazon Connect data and Amazon Kinesis Data Firehose to ingest Salesforce data.

Question 17

A data engineering team within a shared workspace company wants to build a centralized logging system for all weblogs generated by the space reservation system. The company has a fleet of Amazon EC2 instances that process requests for shared space reservations on its website. The data engineering team wants to ingest all weblogs into a service that will provide a near-real-time search engine. The team does not want to manage the maintenance and operation of the logging system.Which solution allows the data engineering team to efficiently set up the web logging system within AWS?

Accepted Answer

Set up the Amazon CloudWatch agent to stream weblogs to CloudWatch logs and subscribe the Amazon Kinesis data stream to CloudWatch. Choose Amazon OpenSearch Service (Amazon Elasticsearch Service) as the end destinationof the weblogs.

Answer

Set up the Amazon CloudWatch agent to stream weblogs to CloudWatch logs and subscribe the Amazon Kinesis Data Firehose delivery stream to CloudWatch. Choose Amazon OpenSearch Service (Amazon Elasticsearch Service) asthe end destination of the weblogs.

Answer

Set up the Amazon CloudWatch agent to stream weblogs to CloudWatch logs and subscribe the Amazon Kinesis data stream to CloudWatch. Configure Splunk as the end destination of the weblogs.

Answer

Set up the Amazon CloudWatch agent to stream weblogs to CloudWatch logs and subscribe the Amazon Kinesis Firehose delivery stream to CloudWatch. Configure Amazon DynamoDB as the end destination of the weblogs.

Question 18

A company has collected more than 100 TB of log files in the last 24 months. The files are stored as raw text in a dedicated Amazon S3 bucket. Each object has a key of the form year-monthday_ log_HHmmss.txt where HHmmss represents the time the log file was initially created. A table was created in Amazon Athena that points to the S3 bucket. One-time queries are run against a subset of columns in the table several times an hour.A data analyst must make changes to reduce the cost of running these queries. Management wants a solution with minimal maintenance overhead. Which combination of steps should the data analyst take to meet these requirements?(Choose three.)

Accepted Answer

Add a key prefix of the form date=year-month-day/ to the S3 objects to partition the data.

Accepted Answer

Convert the log files to Apache Parquet format.

Accepted Answer

Drop and recreate the table with the PARTITIONED BY clause. Run the MSCK REPAIR TABLE statement.

Answer

Convert the log files to Apace Avro format.

Answer

Add a key prefix of the form year-month-day/ to the S3 objects to partition the data.

Answer

Drop and recreate the table with the PARTITIONED BY clause. Run the ALTER TABLE ADD PARTITION statement.

Question 19

A company wants to provide its data analysts with uninterrupted access to the data in its Amazon Redshift cluster. All data is streamed to an Amazon S3 bucket with Amazon Kinesis Data Firehose. An AWS Glue job that is scheduled to run every 5 minutes issues a COPY command to move the data into Amazon Redshift.The amount of data delivered is uneven throughout the day, and cluster utilization is high during certain periods. The COPY command usually completes within a couple of seconds. However, when load spike occurs, locks can exist and data can be missed. Currently, the AWS Glue job is configured to run without retries, with timeout at 5 minutes and concurrency at 1.How should a data analytics specialist configure the AWS Glue job to optimize fault tolerance and improve data availability in the Amazon Redshift cluster?

Accepted Answer

Keep the number of retries at 0. Decrease the timeout value. Increase the job concurrency.

Answer

Increase the number of retries. Decrease the timeout value. Increase the job concurrency.

Answer

Keep the number of retries at 0. Decrease the timeout value. Keep the job concurrency at 1.

Answer

Keep the number of retries at 0. Increase the timeout value. Keep the job concurrency at 1.

Question 20

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.)

Accepted Answer

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

Accepted Answer

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

Accepted Answer

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

Answer

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

Answer

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

Answer

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

Question 21

A global company has different sub-organizations, and each sub-organization sells its products and services in various countries. The company's senior leadership wants to quickly identify which suborganization is the strongest performer in each country. All sales data is stored in Amazon S3 in Parquet format.Which approach can provide the visuals that senior leadership requested with the least amount of effort?

Accepted Answer

Use Amazon QuickSight with Amazon Athena as the data source. Use pivot tables as the visual type.

Answer

Use Amazon QuickSight with Amazon Athena as the data source. Use heat maps as the visual type.

Answer

Use Amazon QuickSight with Amazon S3 as the data source. Use heat maps as the visual type.

Answer

Use Amazon QuickSight with Amazon S3 as the data source. Use pivot tables as the visual type.

Question 22

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?

Accepted Answer

Separate the data by product and use IAM policies for authorization.

Answer

Separate the data by product and use S3 bucket policies for authorization.

Answer

Create a manifest file with row-level security.

Answer

Create dataset rules with row-level security.

Question 23

An operations team notices that a few AWS Glue jobs for a given ETL application are failing. The AWS Glue jobs read a large number of small JSON files from an Amazon S3 bucket and write the data to a different S3 bucket in Apache Parquet format with no major transformations. Upon initial investigation, a data engineer notices the following error message in the History tab on the AWS Glue console:“Command Failed with Exit Code 1.”Upon further investigation, the data engineer notices that the driver memory profile of the failed jobs crosses the safe threshold of 50% usage quickly and reaches 90–95% soon after. The average memory usage across all executors continues to be less than 4%.The data engineer also notices the following error while examining the related Amazon CloudWatch Logs.<img alt="Amazon DAS-C01 image Question 143 2557 09162024005525000000"   width="367" height="50" src="https://examgecko.com/getfile/af3d6fd2-b6b9-49d3-b6c1-f6360d771aec">What should the data engineer do to solve the failure in the MOST cost-effective way?

Accepted Answer

Modify maximum capacity to increase the total maximum data processing units (DPUs) used.

Answer

Change the worker type from Standard to G.2X.

Answer

Modify the AWS Glue ETL code to use the ‘groupFiles’: ‘inPartition’ feature.

Answer

Increase the fetch size setting by using AWS Glue dynamics frame.

Question 24

A healthcare company uses AWS data and analytics tools to collect, ingest, and store electronic health record (EHR) data about its patients. The raw EHR data is stored in Amazon S3 in JSON format partitioned by hour, day, and year and is updated every hour. The company wants to maintain the data catalog and metadata in an AWS Glue Data Catalog to be able to access the data using Amazon Athena or Amazon Redshift Spectrum for analytics.When defining tables in the Data Catalog, the company has the following requirements:Choose the catalog table name and do not rely on the catalog table naming algorithm.Keep the table updated with new partitions loaded in the respective S3 bucket prefixes. Which solution meets these requirements with minimal effort?

Accepted Answer

Use the AWS Glue console to manually create a table in the Data Catalog and schedule an AWS Lambda function to update the table partitions hourly.

Answer

Run an AWS Glue crawler that connects to one or more data stores, determines the data structures, and writes tables in the Data Catalog.

Answer

Use the AWS Glue API CreateTable operation to create a table in the Data Catalog. Create an AWS Glue crawler and specify the table as the source.

Answer

Create an Apache Hive catalog in Amazon EMR with the table schema definition in Amazon S3, and update the table partition with a scheduled job. Migrate the Hive catalog to the Data Catalog.

Question 25

A company has 10-15 ?? of uncompressed .csv files in Amazon S3. The company is evaluating Amazon Athena as a onetime query engine. The company wants to transform the data to optimize query runtime and storage costs. Which option for data format and compression meets these requirements?

Accepted Answer

JSON compressed with bzip2

Answer

CSV compressed with zip

Answer

Apache Parquet compressed with Snappy

Answer

Apache Avro compressed with LZO

Question 26

A manufacturing company uses Amazon S3 to store its data. The company wants to use AWS Lake Formation to provide granular-level security on those data assets. The data is in Apache Parquet format. The company has set a deadline for a consultant to build a data lake.How should the consultant create the MOST cost-effective solution that meets these requirements?

Accepted Answer

Install Apache Ranger on an Amazon EC2 instance and integrate with Amazon EMR. Using Ranger policies, create rolebased access control for the existing data assets in Amazon S3.

Answer

Run Lake Formation blueprints to move the data to Lake Formation. Once Lake Formation has the data, apply permissions on Lake Formation.

Answer

To create the data catalog, run an AWS Glue crawler on the existing Parquet data. Register the Amazon S3 path and then apply permissions through Lake Formation to provide granular-level security.

Answer

Create multiple IAM roles for different users and groups. Assign IAM roles to different data assets in Amazon S3 to create table-based and column-based access controls.

Question 27

A retail company leverages Amazon Athena for ad-hoc queries against an AWS Glue Data Catalog. The data analytics team manages the data catalog and data access for the company. The data analytics team wants to separate queries and manage the cost of running those queries by different workloads and teams. Ideally, the data analysts want to group the queries run by different users within a team, store the query results in individual Amazon S3 buckets specific to each team, and enforce cost constraints on the queries run against the Data Catalog. Which solution meets these requirements?

Accepted Answer

Create IAM groups and resource tags for each team within the company. Set up IAM policies that control user access and actions on the Data Catalog resources.

Answer

Create Athena resource groups for each team within the company and assign users to these groups. Add S3 bucket names and other query configurations to the properties list for the resource groups.

Answer

Create Athena workgroups for each team within the company. Set up IAM workgroup policies that control user access and actions on the workgroup resources.

Answer

Create Athena query groups for each team within the company and assign users to the groups.

Question 28

A team of data scientists plans to analyze market trend data for their company’s new investment strategy. The trend data comes from five different data sources in large volumes. The team wants to utilize Amazon Kinesis to support their use case.The team uses SQL-like queries to analyze trends and wants to send notifications based on certain significant patterns in the trends. Additionally, the data scientists want to save the data to Amazon S3 for archival and historical reprocessing, and use AWS managed services wherever possible. The team wants to implement the lowest-cost solution. Which solution meets these requirements?

Accepted Answer

Publish data to one Kinesis data stream. Deploy a custom application using the Kinesis Client Library (KCL) for analyzing trends, and send notifications using Amazon SNS. Configure Kinesis Data Firehose on the Kinesis data stream topersist data to an S3 bucket.

Answer

Publish data to one Kinesis data stream. Deploy Kinesis Data Analytic to the stream for analyzing trends, and configure an AWS Lambda function as an output to send notifications using Amazon SNS. Configure Kinesis Data Firehose onthe Kinesis data stream to persist data to an S3 bucket.

Answer

Publish data to two Kinesis data streams. Deploy Kinesis Data Analytics to the first stream for analyzing trends, and configure an AWS Lambda function as an output to send notifications using Amazon SNS. Configure Kinesis DataFirehose on the second Kinesis data stream to persist data to an S3 bucket.

Answer

Publish data to two Kinesis data streams. Deploy a custom application using the Kinesis Client Library (KCL) to the first stream for analyzing trends, and send notifications using Amazon SNS. Configure Kinesis Data Firehose on thesecond Kinesis data stream to persist data to an S3 bucket.

Question 29

A company analyzes its data in an Amazon Redshift data warehouse, which currently has a cluster of three dense storage nodes. Due to a recent business acquisition, the company needs to load an additional 4 TB of user data into Amazon Redshift. The engineering team will combine all the user data and apply complex calculations that require I/O intensive resources. The company needs to adjust the cluster's capacity to support the change in analytical and storage requirements.Which solution meets these requirements?

Accepted Answer

Resize the cluster using elastic resize with dense storage nodes.

Answer

Resize the cluster using elastic resize with dense compute nodes.

Answer

Resize the cluster using classic resize with dense compute nodes.

Answer

Resize the cluster using classic resize with dense storage nodes.

Question 30

A data architect is building an Amazon S3 data lake for a bank. The goal is to provide a single data repository for customer data needs, such as personalized recommendations. The bank uses Amazon Kinesis Data Firehose to ingest customers’ personal information bank accounts, and transactions in near-real time from a transactional relational database. The bank requires all personally identifiable information (PII) that is stored in the AWS Cloud to be masked. Which solution will meet these requirements?

Accepted Answer

Enable server-side encryption (SSE) in Amazon S3.

Answer

Invoke an AWS Lambda function from Kinesis Data Firehose to mask PII before delivering the data into Amazon S3.

Answer

Use Amazon Made, and configure it to discover and mask PII.

Answer

Invoke Amazon Comprehend from Kinesis Data Firehose to detect and mask PII before delivering the data into Amazon S3.

Question 31

A data analyst is using Amazon QuickSight for data visualization across multiple datasets generated by applications. Each application stores files within a separate Amazon S3 bucket. AWS Glue Data Catalog is used as a central catalog across all application data in Amazon S3. A new application stores its data within a separate S3 bucket. After updating the catalog to include the new application data source, the data analyst created a new Amazon QuickSight data source from an Amazon Athena table, but the import into SPICE failed. How should the data analyst resolve the issue?

Accepted Answer

Edit the permissions for the new S3 bucket from within the Amazon QuickSight console.

Answer

Edit the permissions for the AWS Glue Data Catalog from within the Amazon QuickSight console.

Answer

Edit the permissions for the AWS Glue Data Catalog from within the AWS Glue console.

Answer

Edit the permissions for the new S3 bucket from within the S3 console.

Question 32

A company wants to use an automatic machine learning (ML) Random Cut Forest (RCF) algorithm to visualize complex realworld scenarios, such as detecting seasonality and trends, excluding outers, and imputing missing values. The team working on this project is non-technical and is looking for an out-of-the-box solution that will require the LEAST amount of management overhead. Which solution will meet these requirements?

Accepted Answer

Use an AWS Glue ML transform to create a forecast and then use Amazon QuickSight to visualize the data.

Answer

Use Amazon QuickSight to visualize the data and then use ML-powered forecasting to forecast the key business metrics.

Answer

Use a pre-build ML AMI from the AWS Marketplace to create forecasts and then use Amazon QuickSight to visualize the data.

Answer

Use calculated fields to create a new forecast and then use Amazon QuickSight to visualize the data.

Question 33

A media company has been performing analytics on log data generated by its applications. There has been a recent increase in the number of concurrent analytics jobs running, and the overall performance of existing jobs is decreasing as the number of new jobs is increasing. The partitioned data is stored in Amazon S3 One Zone-Infrequent Access (S3 One Zone-IA) and the analytic processing is performed on Amazon EMR clusters using the EMR File System (EMRFS) with consistent view enabled. A data analyst has determined that it is taking longer for the EMR task nodes to list objects in Amazon S3. Which action would MOST likely increase the performance of accessing log data in Amazon S3?

Accepted Answer

Redeploy the EMR clusters that are running slowly to a different Availability Zone.

Answer

Use a hash function to create a random string and add that to the beginning of the object prefixes when storing the log data in Amazon S3.

Answer

Use a lifecycle policy to change the S3 storage class to S3 Standard for the log data.

Answer

Increase the read capacity units (RCUs) for the shared Amazon DynamoDB table.

Question 34

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?

Accepted Answer

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

Answer

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

Answer

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

Answer

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

Question 35

A social media company is using business intelligence tools to analyze its data for forecasting. The company is using Apache Kafka to ingest the low-velocity data in near-real time. The company wants to build dynamic dashboards with machine learning (ML) insights to forecast key business trends. The dashboards must provide hourly updates from data in Amazon S3. Various teams at the company want to view the dashboards by using Amazon QuickSight with ML insights. The solution also must correct the scalability problems that the company experiences when it uses its current architecture to ingest data. Which solution will MOST cost-effectively meet these requirements?

Accepted Answer

Replace Kafka with an Amazon Kinesis data stream. Use an Amazon Kinesis Data Firehose delivery stream to consume the data and store the data in Amazon S3. Use QuickSight Enterprise edition to refresh the data in SPICE fromAmazon S3 hourly and create a dynamic dashboard with forecasting and ML insights.

Answer

Replace Kafka with Amazon Managed Streaming for Apache Kafka. Ingest the data by using AWS Lambda, and store the data in Amazon S3. Use QuickSight Standard edition to refresh the data in SPICE from Amazon S3 hourly andcreate a dynamic dashboard with forecasting and ML insights.

Answer

Configure the Kafka-Kinesis-Connector to publish the data to an Amazon Kinesis Data Firehose delivery stream that is configured to store the data in Amazon S3. Use QuickSight Enterprise edition to refresh the data in SPICE fromAmazon S3 hourly and create a dynamic dashboard with forecasting and ML insights.

Answer

Configure the Kafka-Kinesis-Connector to publish the data to an Amazon Kinesis Data Firehose delivery stream that is configured to store the data in Amazon S3. Configure an AWS Glue crawler to crawl the data. Use an AmazonAthena data source with QuickSight Standard edition to refresh the data in SPICE hourly and create a dynamic dashboard with forecasting and ML insights.

Question 36

A company owns facilities with IoT devices installed across the world. The company is using Amazon Kinesis Data Streams to stream data from the devices to Amazon S3. The company's operations team wants to get insights from the IoT data to monitor data quality at ingestion. The insights need to be derived in near-real time, and the output must be logged to Amazon DynamoDB for further analysis. Which solution meets these requirements?

Accepted Answer

Connect Amazon Kinesis Data Firehose to analyze the stream data by using an AWS Lambda function. Save the output to DynamoDB by using the default output from Kinesis Data Firehose.

Answer

Connect Amazon Kinesis Data Analytics to analyze the stream data. Save the output to DynamoDB by using the default output from Kinesis Data Analytics.

Answer

Connect Amazon Kinesis Data Analytics to analyze the stream data. Save the output to DynamoDB by using an AWS Lambda function.

Answer

Connect Amazon Kinesis Data Firehose to analyze the stream data by using an AWS Lambda function. Save the data to Amazon S3. Then run an AWS Glue job on schedule to ingest the data into DynamoDB.

Question 37

A company has a data lake on AWS that ingests sources of data from multiple business units and uses Amazon Athena for queries. The storage layer is Amazon S3 using the AWS Glue Data Catalog. The company wants to make the data available to its data scientists and business analysts. However, the company first needs to manage data access for Athena based on user roles and responsibilities. What should the company do to apply these access controls with the LEAST operational overhead?

Accepted Answer

Define security policy-based rules for the tables and columns by role in AWS Identity and Access Management (IAM).

Answer

Define security policy-based rules for the users and applications by role in AWS Lake Formation.

Answer

Define security policy-based rules for the users and applications by role in AWS Identity and Access Management (IAM).

Answer

Define security policy-based rules for the tables and columns by role in AWS Glue.

Question 38

A media company wants to perform machine learning and analytics on the data residing in its Amazon S3 data lake. There are two data transformation requirements that will enable the consumers within the company to create reports: Daily transformations of 300 GB of data with different file formats landing in Amazon S3 at a scheduled time. One-time transformations of terabytes of archived data residing in the S3 data lake.Which combination of solutions cost-effectively meets the company’s requirements for transforming the data? (Choose three.)

Accepted Answer

For daily incoming data, use Amazon Athena to scan and identify the schema.

Accepted Answer

For daily incoming data, use Amazon Redshift to perform transformations.

Accepted Answer

For daily incoming data, use AWS Glue workflows with AWS Glue jobs to perform transformations.

Answer

For daily incoming data, use AWS Glue crawlers to scan and identify the schema.

Answer

For archived data, use Amazon EMR to perform data transformations.

Answer

For archived data, use Amazon SageMaker to perform data transformations.

Question 39

A company currently uses Amazon Athena to query its global datasets. The regional data is stored in Amazon S3 in the useast- 1 and us-west-2 Regions. The data is not encrypted. To simplify the query process and manage it centrally, the company wants to use Athena in us-west-2 to query data from Amazon S3 in both Regions. The solution should be as lowcost as possible. What should the company do to achieve this goal?

Accepted Answer

Enable cross-Region replication for the S3 buckets in us-east-1 to replicate data in us-west-2. Once the data is replicated in us-west-2, run the AWS Glue crawler there to update the AWS Glue Data Catalog in us-west-2 and run Athenaqueries.

Answer

Use AWS DMS to migrate the AWS Glue Data Catalog from us-east-1 to us-west-2. Run Athena queries in us-west-2.

Answer

Run the AWS Glue crawler in us-west-2 to catalog datasets in all Regions. Once the data is crawled, run Athena queries in us-west-2.

Answer

Update AWS Glue resource policies to provide us-east-1 AWS Glue Data Catalog access to us-west-2. Once the catalog in us-west-2 has access to the catalog in us-east-1, run Athena queries in uswest-2.

Question 40

A company uses Amazon Redshift for its data warehousing needs. ETL jobs run every night to load data, apply business rules, and create aggregate tables for reporting. The company's data analysis, data science, and business intelligence teams use the data warehouse during regular business hours. The workload management is set to auto, and separate queues exist for each team with the priority set to NORMAL.Recently, a sudden spike of read queries from the data analysis team has occurred at least twice daily, and queries wait in line for cluster resources. The company needs a solution that enables the data analysis team to avoid query queuing without impacting latency and the query times of other teams. Which solution meets these requirements?

Accepted Answer

Use workload management query queue hopping to route the query to the next matching queue.

Answer

Increase the query priority to HIGHEST for the data analysis queue.

Answer

Configure the data analysis queue to enable concurrency scaling.

Answer

Create a query monitoring rule to add more cluster capacity for the data analysis queue when queries are waiting for resources.

Amazon DAS-C01 Practice Test 4

Amazon DAS-C01 Practice Tests