DEA-C01 practice questions 51–60

1. Question 51 · 313 in bank

   A technology company currently uses Amazon Kinesis Data Streams to collect log data in real time. The company wants to use Amazon Redshift for downstream real-time queries and to enrich the log data. Which solution will ingest data into Amazon Redshift with the LEAST operational overhead?

   • ASet up an Amazon Kinesis Data Firehose delivery stream to send data to a Redshift provisioned cluster table.
   • BSet up an Amazon Kinesis Data Firehose delivery stream to send data to Amazon S3. Configure a Redshift provisioned cluster to load data every minute.
   • CConfigure Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to send data directly to a Redshift provisioned cluster table.
   • DUse Amazon Redshift streaming ingestion from Kinesis Data Streams and to present data as a materialized view.

   Show answer

   Answer: D

   Explanation

   Amazon Redshift supports streaming ingestion from Amazon Kinesis Data Streams. The Amazon Redshift streaming ingestion feature provides low-latency, high-speed ingestion of streaming data from Amazon Kinesis Data Streams into an Amazon Redshift materialized view. Amazon Redshift streaming ingestion removes the need to stage data in Amazon S3before ingesting into Amazon Redshift. link: https://docs.aws.amazon.com/streams/latest/dev/using-other-services-redshift.html

   Source: Adapted from community discussion — dashapetr

   References

   • AWS documentation

   Next question

2. Question 52 · 313 in bank

   A company maintains a data warehouse in an on-premises Oracle database. The company wants to build a data lake on AWS. The company wants to load data warehouse tables into Amazon S3 and synchronize the tables with incremental data that arrives from the data warehouse every day. Each table has a column that contains monotonically increasing values. The size of each table is less than 50 GB. The data warehouse tables are refreshed every night between 1 AM and 2 AM. A business intelligence team queries the tables between 10 AM and 8 PM every day. Which solution will meet these requirements in the MOST operationally efficient way?

   • AUse an AWS Database Migration Service (AWS DMS) full load plus CDC job to load tables that contain monotonically increasing data columns from the on-premises data warehouse to Amazon S3. Use custom logic in AWS Glue to append the daily incremental data to a full-load copy that is in Amazon S3.
   • BUse an AWS Glue Java Database Connectivity (JDBC) connection. Configure a job bookmark for a column that contains monotonically increasing values. Write custom logic to append the daily incremental data to a full-load copy that is in Amazon S3.
   • CUse an AWS Database Migration Service (AWS DMS) full load migration to load the data warehouse tables into Amazon S3 every day. Overwrite the previous day's full-load copy every day.
   • DUse AWS Glue to load a full copy of the data warehouse tables into Amazon S3 every day. Overwrite the previous day's full-load copy every day.

   Show answer

   Answer: A

   Next question

3. Question 53 · 313 in bank

   A company is building a data lake for a new analytics team. The company is using Amazon S3 for storage and Amazon Athena for query analysis. All data that is in Amazon S3 is in Apache Parquet format. The company is running a new Oracle database as a source system in the company’s data center. The company has 70 tables in the Oracle database. All the tables have primary keys. Data can occasionally change in the source system. The company wants to ingest the tables every day into the data lake. Which solution will meet this requirement with the LEAST effort?

   • ACreate an Apache Sqoop job in Amazon EMR to read the data from the Oracle database. Configure the Sqoop job to write the data to Amazon S3 in Parquet format.
   • BCreate an AWS Glue connection to the Oracle database. Create an AWS Glue bookmark job to ingest the data incrementally and to write the data to Amazon S3 in Parquet format.
   • CCreate an AWS Database Migration Service (AWS DMS) task for ongoing replication. Set the Oracle database as the source. Set Amazon S3 as the target. Configure the task to write the data in Parquet format.
   • DCreate an Oracle database in Amazon RDS. Use AWS Database Migration Service (AWS DMS) to migrate the on-premises Oracle database to Amazon RDS. Configure triggers on the tables to invoke AWS Lambda functions to write changed records to Amazon S3 in Parquet format.

   Show answer

   Answer: C

   References

   • AWS documentation

   Next question

4. Question 54 · 313 in bank

   A transportation company wants to track vehicle movements by capturing geolocation records. The records are 10 bytes in size. The company receives up to 10.000 records every second. Data transmission delays of a few minutes are acceptable because of unreliable network conditions. The transportation company wants to use Amazon Kinesis Data Streams to ingest the geolocation data. The company needs a reliable mechanism to send data to Kinesis Data Streams. The company needs to maximize the throughput efficiency of the Kinesis shards. Which solution will meet these requirements in the MOST operationally efficient way?

   • AKinesis Agent
   • BKinesis Producer Library (KPL)
   • CAmazon Kinesis Data Firehose
   • DKinesis SDK

   Show answer

   Answer: B

   Explanation

   KPL automatically batches and aggregates multiple records into a single payload before sending them to Kinesis Data Streams. This reduces the number of records sent and optimizes shard throughput usage.

   Source: Adapted from community discussion — HagarTheHorrible

   Next question

5. Question 55 · 313 in bank

   An investment company needs to manage and extract insights from a volume of semi-structured data that grows continuously. A data engineer needs to deduplicate the semi-structured data, remove records that are duplicates, and remove common misspellings of duplicates. Which solution will meet these requirements with the LEAST operational overhead?

   • AUse the FindMatches feature of AWS Glue to remove duplicate records.
   • BUse non-Windows functions in Amazon Athena to remove duplicate records.
   • CUse Amazon Neptune ML and an Apache Gremlin script to remove duplicate records.
   • DUse the global tables feature of Amazon DynamoDB to prevent duplicate data.

   Show answer

   Answer: A

   Next question

6. Question 56 · 313 in bank

   Select 2

   A company is building an inventory management system and an inventory reordering system to automatically reorder products. Both systems use Amazon Kinesis Data Streams. The inventory management system uses the Amazon Kinesis Producer Library (KPL) to publish data to a stream. The inventory reordering system uses the Amazon Kinesis Client Library (KCL) to consume data from the stream. The company configures the stream to scale up and down as needed. Before the company deploys the systems to production, the company discovers that the inventory reordering system received duplicated data. Which factors could have caused the reordering system to receive duplicated data? (Choose two.)

   • AThe producer experienced network-related timeouts.
   • BThe stream’s value for the IteratorAgeMilliseconds metric was too high.
   • CThere was a change in the number of shards, record processors, or both.
   • DThe AggregationEnabled configuration property was set to true.
   • EThe max_records configuration property was set to a number that was too high.

   Show answer

   Answer: AC

   Explanation

   Answer is AC https://docs.aws.amazon.com/streams/latest/dev/kinesis-record-processor-duplicates.html Consumer can add duplicates due to network timeouts. Producer can consume duplicates due to shards and record processor related changes.

   Source: Adapted from community discussion — 0c2d840

   References

   • AWS documentation

   Next question

7. Question 57 · 313 in bank

   A data engineer needs to securely transfer 5 TB of data from an on-premises data center to an Amazon S3 bucket. Approximately 5% of the data changes every day. Updates to the data need to be regularly proliferated to the S3 bucket. The data includes files that are in multiple formats. The data engineer needs to automate the transfer process and must schedule the process to run periodically. Which AWS service should the data engineer use to transfer the data in the MOST operationally efficient way?

   • AAWS DataSync
   • BAWS Glue
   • CAWS Direct Connect
   • DAmazon S3 Transfer Acceleration

   Show answer

   Answer: A

   Explanation

   A. AWS DataSync Explanation: AWS DataSync is a managed data transfer service that simplifies and accelerates moving large amounts of data online between on-premises storage and Amazon S3, EFS, or FSx for Windows File Server. DataSync is optimized for efficient, incremental, and reliable transfers of large datasets, making it suitable for transferring 5 TB of data with daily updates.

   Source: Adapted from community discussion — TonyStark0122

   Next question

8. Question 58 · 313 in bank

   An ecommerce company operates a complex order fulfilment process that spans several operational systems hosted in AWS. Each of the operational systems has a Java Database Connectivity (JDBC)-compliant relational database where the latest processing state is captured. The company needs to give an operations team the ability to track orders on an hourly basis across the entire fulfillment process. Which solution will meet these requirements with the LEAST development overhead?

   • AUse AWS Glue to build ingestion pipelines from the operational systems into Amazon Redshift Build dashboards in Amazon QuickSight that track the orders.
   • BUse AWS Glue to build ingestion pipelines from the operational systems into Amazon DynamoDBuild dashboards in Amazon QuickSight that track the orders.
   • CUse AWS Database Migration Service (AWS DMS) to capture changed records in the operational systems. Publish the changes to an Amazon DynamoDB table in a different AWS region from the source database. Build Grafana dashboards that track the orders.
   • DUse AWS Database Migration Service (AWS DMS) to capture changed records in the operational systems. Publish the changes to an Amazon DynamoDB table in a different AWS region from the source database. Build Amazon QuickSight dashboards that track the orders.

   Show answer

   Answer: A

   References

   • AWS documentation

   Next question

9. Question 59 · 313 in bank

   Select 2

   A data engineer needs to use Amazon Neptune to develop graph applications. Which programming languages should the engineer use to develop the graph applications? (Choose two.)

   • AGremlin
   • BSQL
   • CANSI SQL
   • DSPARQL
   • ESpark SQL

   Show answer

   Answer: AD

   References

   • AWS documentation

   Next question

10. Question 60 · 313 in bank

    A mobile gaming company wants to capture data from its gaming app. The company wants to make the data available to three internal consumers of the data. The data records are approximately 20 KB in size. The company wants to achieve optimal throughput from each device that runs the gaming app. Additionally, the company wants to develop an application to process data streams. The stream-processing application must have dedicated throughput for each internal consumer. Which solution will meet these requirements?

    • AConfigure the mobile app to call the PutRecords API operation to send data to Amazon Kinesis Data Streams. Use the enhanced fan-out feature with a stream for each internal consumer.
    • BConfigure the mobile app to call the PutRecordBatch API operation to send data to Amazon Kinesis Data Firehose. Submit an AWS Support case to turn on dedicated throughput for the company’s AWS account. Allow each internal consumer to access the stream.
    • CConfigure the mobile app to use the Amazon Kinesis Producer Library (KPL) to send data to Amazon Kinesis Data Firehose. Use the enhanced fan-out feature with a stream for each internal consumer.
    • DConfigure the mobile app to call the PutRecords API operation to send data to Amazon Kinesis Data Streams. Host the stream-processing application for each internal consumer on Amazon EC2 instances. Configure auto scaling for the EC2 instances.

    Show answer

    Answer: A

    Explanation

    The correct answer is A. Here is why: Amazon Kinesis Data Streams is designed for real-time streaming data. The PutRecords API is efficient for sending multiple records to Kinesis in a single call, which is good for optimizing throughput from mobile devices. The enhanced fan-out feature allows multiple consumers to read from the same stream with dedicated throughput for each consumer, which meets the requirement of dedicated throughput for each internal consumer. This option uses uses Kinesis Data Streams for real-time processing, optimizes throughput from mobile devices with the PutRecords API, and provides dedicated throughput for each consumer using the enhanced fan-out feature.

    Source: Adapted from community discussion — AgboolaKun

    Next question

Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page

DEA-C01 practice, question 51. 313 questions available.