How Many Questions Of DAS-C01 Test

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NEW QUESTION 1
A company wants to improve user satisfaction for its smart home system by adding more features to its recommendation engine. Each sensor asynchronously pushes its nested JSON data into Amazon Kinesis Data Streams using the Kinesis Producer Library (KPL) in Java. Statistics from a set of failed sensors showed that, when a sensor is malfunctioning, its recorded data is not always sent to the cloud.
The company needs a solution that offers near-real-time analytics on the data from the most updated sensors. Which solution enables the company to meet these requirements?

  • A. Set the RecordMaxBufferedTime property of the KPL to "1" to disable the buffering on the sensor side.Use Kinesis Data Analytics to enrich the data based on a company-developed anomaly detection SQL scrip
  • B. Push the enriched data to a fleet of Kinesis data streams and enable the data transformation feature to flatten the JSON fil
  • C. Instantiate a dense storage Amazon Redshift cluster and use it as the destination for the Kinesis Data Firehose delivery stream.
  • D. Update the sensors code to use the PutRecord/PutRecords call from the Kinesis Data Streams API with the AWS SDK for Jav
  • E. Use Kinesis Data Analytics to enrich the data based on a company-developed anomaly detection SQL scrip
  • F. Direct the output of KDA application to a Kinesis Data Firehose delivery stream, enable the data transformation feature to flatten the JSON file, and set the Kinesis Data Firehose destination to an Amazon Elasticsearch Service cluster.
  • G. Set the RecordMaxBufferedTime property of the KPL to "0" to disable the buffering on the sensor side.Connect for each stream a dedicated Kinesis Data Firehose delivery stream and enable the data transformation feature to flatten the JSON file before sending it to an Amazon S3 bucke
  • H. Load the S3 data into an Amazon Redshift cluster.
  • I. Update the sensors code to use the PutRecord/PutRecords call from the Kinesis Data Streams API withthe AWS SDK for Jav
  • J. Use AWS Glue to fetch and process data from the stream using the Kinesis Client Library (KCL). Instantiate an Amazon Elasticsearch Service cluster and use AWS Lambda to directly push data into it.

Answer: B

Explanation:
https://docs.aws.amazon.com/streams/latest/dev/developing-producers-with-kpl.html
The KPL can incur an additional processing delay of up to RecordMaxBufferedTime within the library (user-configurable). Larger values of RecordMaxBufferedTime results in higher packing efficiencies and better performance. Applications that cannot tolerate this additional delay may need to use the AWS SDK directly.

NEW QUESTION 2
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?

  • A. Increase the number of retrie
  • B. Decrease the timeout valu
  • C. Increase the job concurrency.
  • D. Keep the number of retries at 0. Decrease the timeout valu
  • E. Increase the job concurrency.
  • F. Keep the number of retries at 0. Decrease the timeout valu
  • G. Keep the job concurrency at 1.
  • H. Keep the number of retries at 0. Increase the timeout valu
  • I. Keep the job concurrency at 1.

Answer: B

NEW QUESTION 3
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-month-day_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.)

  • A. Convert the log files to Apace Avro format.
  • B. Add a key prefix of the form date=year-month-day/ to the S3 objects to partition the data.
  • C. Convert the log files to Apache Parquet format.
  • D. Add a key prefix of the form year-month-day/ to the S3 objects to partition the data.
  • E. Drop and recreate the table with the PARTITIONED BY claus
  • F. Run the ALTER TABLE ADD PARTITION statement.
  • G. Drop and recreate the table with the PARTITIONED BY claus
  • H. Run the MSCK REPAIR TABLE statement.

Answer: BCF

NEW QUESTION 4
A marketing company is using Amazon EMR clusters for its workloads. The company manually installs third party libraries on the clusters by logging in to the master nodes. A data analyst needs to create an automated solution to replace the manual process.
Which options can fulfill these requirements? (Choose two.)

  • A. Place the required installation scripts in Amazon S3 and execute them using custom bootstrap actions.
  • B. Place the required installation scripts in Amazon S3 and execute them through Apache Spark in Amazon EMR.
  • C. Install the required third-party libraries in the existing EMR master nod
  • D. Create an AMI out of that master node and use that custom AMI to re-create the EMR cluster.
  • E. Use an Amazon DynamoDB table to store the list of required application
  • F. Trigger an AWS Lambda function with DynamoDB Streams to install the software.
  • G. Launch an Amazon EC2 instance with Amazon Linux and install the required third-party libraries on the instanc
  • H. Create an AMI and use that AMI to create the EMR cluster.

Answer: AE

Explanation:
https://aws.amazon.com/about-aws/whats-new/2017/07/amazon-emr-now-supports-launching-clusters-with-cust https://docs.aws.amazon.com/de_de/emr/latest/ManagementGuide/emr-plan-bootstrap.html

NEW QUESTION 5
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.

Answer: A

Explanation:
https://aws.amazon.com/blogs/big-data/top-10-performance-tuning-tips-for-amazon-athena/

NEW QUESTION 6
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.

Answer: BD

NEW QUESTION 7
A retail company has 15 stores across 6 cities in the United States. Once a month, the sales team requests a visualization in Amazon QuickSight that provides the ability to easily identify revenue trends across cities and stores. The visualization also helps identify outliers that need to be examined with further analysis.
Which visual type in QuickSight meets the sales team's requirements?

  • A. Geospatial chart
  • B. Line chart
  • C. Heat map
  • D. Tree map

Answer: A

NEW QUESTION 8
A company hosts an on-premises PostgreSQL database that contains historical data. An internal legacy application uses the database for read-only activities. The company’s business team wants to move the data to a data lake in Amazon S3 as soon as possible and enrich the data for analytics.
The company has set up an AWS Direct Connect connection between its VPC and its on-premises network. A data analytics specialist must design a solution that achieves the business team’s goals with the least operational overhead.
Which solution meets these requirements?

  • A. Upload the data from the on-premises PostgreSQL database to Amazon S3 by using a customized batch upload proces
  • B. Use the AWS Glue crawler to catalog the data in Amazon S3. Use an AWS Glue job to enrich and store the result in a separate S3 bucket in Apache Parquet forma
  • C. Use Amazon Athena to query the data.
  • D. Create an Amazon RDS for PostgreSQL database and use AWS Database Migration Service (AWS DMS) to migrate the data into Amazon RD
  • E. Use AWS Data Pipeline to copy and enrich the data from the Amazon RDS for PostgreSQL table and move the data to Amazon S3. Use Amazon Athena to querythe data.
  • F. Configure an AWS Glue crawler to use a JDBC connection to catalog the data in the on-premises databas
  • G. Use an AWS Glue job to enrich the data and save the result to Amazon S3 in Apache Parquet forma
  • H. Create an Amazon Redshift cluster and use Amazon Redshift Spectrum to query the data.
  • I. Configure an AWS Glue crawler to use a JDBC connection to catalog the data in the on-premises databas
  • J. Use an AWS Glue job to enrich the data and save the result to Amazon S3 in Apache Parquet forma
  • K. Use Amazon Athena to query the data.

Answer: B

NEW QUESTION 9
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 sub-organization 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?

  • A. Use Amazon QuickSight with Amazon Athena as the data sourc
  • B. Use heat maps as the visual type.
  • C. Use Amazon QuickSight with Amazon S3 as the data sourc
  • D. Use heat maps as the visual type.
  • E. Use Amazon QuickSight with Amazon Athena as the data sourc
  • F. Use pivot tables as the visual type.
  • G. Use Amazon QuickSight with Amazon S3 as the data sourc
  • H. Use pivot tables as the visual type.

Answer: A

NEW QUESTION 10
A company wants to collect and process events data from different departments in near-real time. Before storing the data in Amazon S3, the company needs to clean the data by standardizing the format of the address and timestamp columns. The data varies in size based on the overall load at each particular point in time. A single data record can be 100 KB-10 MB.
How should a data analytics specialist design the solution for data ingestion?

  • A. Use Amazon Kinesis Data Stream
  • B. Configure a stream for the raw dat
  • C. Use a Kinesis Agent to write data to the strea
  • D. Create an Amazon Kinesis Data Analytics application that reads data from the raw stream, cleanses it, and stores the output to Amazon S3.
  • E. Use Amazon Kinesis Data Firehos
  • F. Configure a Firehose delivery stream with a preprocessing AWS Lambda function for data cleansin
  • G. Use a Kinesis Agent to write data to the delivery strea
  • H. Configure Kinesis Data Firehose to deliver the data to Amazon S3.
  • I. Use Amazon Managed Streaming for Apache Kafk
  • J. Configure a topic for the raw dat
  • K. Use a Kafka producer to write data to the topi
  • L. Create an application on Amazon EC2 that reads data from the topic by using the Apache Kafka consumer API, cleanses the data, and writes to Amazon S3.
  • M. Use Amazon Simple Queue Service (Amazon SQS). Configure an AWS Lambda function to read events from the SQS queue and upload the events to Amazon S3.

Answer: B

NEW QUESTION 11
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?

  • A. Kinesis Agent
  • B. Kinesis Producer Library (KPL)
  • C. Kinesis Data Firehose
  • D. Kinesis SDK

Answer: B

NEW QUESTION 12
A company has an application that ingests streaming data. The company needs to analyze this stream over a 5-minute timeframe to evaluate the stream for anomalies with Random Cut Forest (RCF) and summarize the current count of status codes. The source and summarized data should be persisted for future use.
Which approach would enable the desired outcome while keeping data persistence costs low?

  • A. Ingest the data stream with Amazon Kinesis Data Stream
  • B. Have an AWS Lambda consumer evaluate the stream, collect the number status codes, and evaluate the data against a previously trained RCF mode
  • C. Persist the source and results as a time series to Amazon DynamoDB.
  • D. Ingest the data stream with Amazon Kinesis Data Stream
  • E. Have a Kinesis Data Analytics application evaluate the stream over a 5-minute window using the RCF function and summarize the count of status code
  • F. Persist the source and results to Amazon S3 through output delivery to Kinesis Data Firehouse.
  • G. Ingest the data stream with Amazon Kinesis Data Firehose with a delivery frequency of 1 minute or 1 MB in Amazon S3. Ensure Amazon S3 triggers an event to invoke an AWS Lambda consumer that evaluates the batch data, collects the number status codes, and evaluates the data against a previouslytrained RCF mode
  • H. Persist the source and results as a time series to Amazon DynamoDB.
  • I. Ingest the data stream with Amazon Kinesis Data Firehose with a delivery frequency of 5 minutes or 1 MB into Amazon S3. Have a Kinesis Data Analytics application evaluate the stream over a 1-minute window using the RCF function and summarize the count of status code
  • J. Persist the results to Amazon S3 through a Kinesis Data Analytics output to an AWS Lambda integration.

Answer: B

NEW QUESTION 13
A company wants to optimize the cost of its data and analytics platform. The company is ingesting a number of .c sv and JSON files in Amazon S3 from various data sources. Incoming data is expected to be 50 GB each day. The company is using Amazon Athena to query the raw data in Amazon S3 directly. Most queries aggregate data from the past 12 months, and data that is older than 5 years is infrequently queried. The typical query scans about 500 MB of data and is expected to return results in less than 1 minute. The raw data must be retained indefinitely for compliance requirements.
Which solution meets the company’s requirements?

  • A. Use an AWS Glue ETL job to compress, partition, and convert the data into a columnar data forma
  • B. Use Athena to query the processed datase
  • C. Configure a lifecycle policy to move the processed data into the Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage class 5 years after object creatio
  • D. Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier for long-term archival 7 days after object creation.
  • E. Use an AWS Glue ETL job to partition and convert the data into a row-based data forma
  • F. Use Athena to query the processed datase
  • G. Configure a lifecycle policy to move the data into the Amazon S3 Standard- Infrequent Access (S3 Standard-IA) storage class 5 years after object creatio
  • H. Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier for long-term archival 7 days after object creation.
  • I. Use an AWS Glue ETL job to compress, partition, and convert the data into a columnar data forma
  • J. Use Athena to query the processed datase
  • K. Configure a lifecycle policy to move the processed data into the Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage class 5 years after the object was last accesse
  • L. Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier forlong-term archival 7 days after the last date the object was accessed.
  • M. Use an AWS Glue ETL job to partition and convert the data into a row-based data forma
  • N. Use Athena to query the processed datase
  • O. Configure a lifecycle policy to move the data into the Amazon S3 Standard- Infrequent Access (S3 Standard-IA) storage class 5 years after the object was last accesse
  • P. Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier for long-term archival 7 days after the last date the object was accessed.

Answer: A

NEW QUESTION 14
An online retailer is rebuilding its inventory management system and inventory reordering system to automatically reorder products by using Amazon Kinesis Data Streams. The inventory management system uses the Kinesis Producer Library (KPL) to publish data to a stream. The inventory reordering system uses the Kinesis Client Library (KCL) to consume data from the stream. The stream has been configured to scale as needed. Just before production deployment, the retailer discovers that the inventory reordering system is receiving duplicated data.
Which factors could be causing the duplicated data? (Choose two.)

  • A. The producer has a network-related timeout.
  • B. The stream’s value for the IteratorAgeMilliseconds metric is too high.
  • C. There was a change in the number of shards, record processors, or both.
  • D. The AggregationEnabled configuration property was set to true.
  • E. The max_records configuration property was set to a number that is too high.

Answer: BD

NEW QUESTION 15
A mobile gaming company wants to capture data from its gaming app and make the data available for analysis immediately. The data record size will be approximately 20 KB. The company is concerned about achieving optimal throughput from each device. Additionally, the company wants to develop a data stream processing application with dedicated throughput for each consumer.
Which solution would achieve this goal?

  • A. Have the app call the PutRecords API to send data to Amazon Kinesis Data Stream
  • B. Use the enhanced fan-out feature while consuming the data.
  • C. Have the app call the PutRecordBatch API to send data to Amazon Kinesis Data Firehos
  • D. Submit a support case to enable dedicated throughput on the account.
  • E. Have the app use Amazon Kinesis Producer Library (KPL) to send data to Kinesis Data Firehos
  • F. Use the enhanced fan-out feature while consuming the data.
  • G. Have the app call the PutRecords API to send data to Amazon Kinesis Data Stream
  • H. Host the stream- processing application on Amazon EC2 with Auto Scaling.

Answer: A

Explanation:
https://docs.aws.amazon.com/streams/latest/dev/enhanced-consumers.html

NEW QUESTION 16
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?

  • A. Increase the query priority to HIGHEST for the data analysis queue.
  • B. Configure the data analysis queue to enable concurrency scaling.
  • C. Create a query monitoring rule to add more cluster capacity for the data analysis queue when queries are waiting for resources.
  • D. Use workload management query queue hopping to route the query to the next matching queue.

Answer: D

NEW QUESTION 17
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 Redshif
  • C. Use Amazon Redshift as a data source for Amazon QuickSight to create a business intelligence dashboard.
  • D. Use Amazon Kinesis Data Firehose to stream data to Amazon Redshif
  • E. Use Amazon Redshift as a data source for Amazon QuickSight to create a business intelligence dashboard.
  • F. 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.

Answer: C

NEW QUESTION 18
A company wants to run analytics on its Elastic Load Balancing logs stored in Amazon S3. A data analyst needs to be able to query all data from a desired year, month, or day. The data analyst should also be able to query a subset of the columns. The company requires minimal operational overhead and the most
cost-effective solution.
Which approach meets these requirements for optimizing and querying the log data?

  • A. Use an AWS Glue job nightly to transform new log files into .csv format and partition by year, month, and da
  • B. Use AWS Glue crawlers to detect new partition
  • C. Use Amazon Athena to query data.
  • D. Launch a long-running Amazon EMR cluster that continuously transforms new log files from Amazon S3 into its Hadoop Distributed File System (HDFS) storage and partitions by year, month, and da
  • E. Use Apache Presto to query the optimized format.
  • F. Launch a transient Amazon EMR cluster nightly to transform new log files into Apache ORC format and partition by year, month, and da
  • G. Use Amazon Redshift Spectrum to query the data.
  • H. Use an AWS Glue job nightly to transform new log files into Apache Parquet format and partition by year, month, and da
  • I. Use AWS Glue crawlers to detect new partition
  • J. Use Amazon Athena to querydata.

Answer: C

NEW QUESTION 19
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 ap-northeast-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.

Answer: B

NEW QUESTION 20
A media company is using Amazon QuickSight dashboards to visualize its national sales data. The dashboard is using a dataset with these fields: ID, date, time_zone, city, state, country, longitude, latitude, sales_volume, and number_of_items.
To modify ongoing campaigns, the company wants an interactive and intuitive visualization of which states across the country recorded a significantly lower sales volume compared to the national average.
Which addition to the company’s QuickSight dashboard will meet this requirement?

  • A. A geospatial color-coded chart of sales volume data across the country.
  • B. A pivot table of sales volume data summed up at the state level.
  • C. A drill-down layer for state-level sales volume data.
  • D. A drill through to other dashboards containing state-level sales volume data.

Answer: B

NEW QUESTION 21
......

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