A company needs to store objects containing log data in JSON format. The objects are generated by eight applications running in AWS. Six of the applications generate a total of 500 KiB of data per second, and two of the applications can generate up to 2 MiB of data per second.
A data engineer wants to implement a scalable solution to capture and store usage data in an Amazon S3
bucket. The usage data objects need to be reformatted, converted to .csv format, and then compressed before they are stored in Amazon S3. The company requires the solution to include the least custom code possible and has authorized the data engineer to request a service quota increase if needed.
Which solution meets these requirements?

1. A. Configure an Amazon Kinesis Data Firehose delivery stream for each applicatio
2. B. Write AWS Lambda functions to read log data objects from the stream for each applicatio
3. C. Have the function perform reformatting and .csv conversio
4. D. Enable compression on all the delivery streams.
5. E. Configure an Amazon Kinesis data stream with one shard per applicatio
6. F. Write an AWS Lambda function to read usage data objects from the shard
7. G. Have the function perform .csv conversion, reformatting, and compression of the dat
8. H. Have the function store the output in Amazon S3.
9. I. Configure an Amazon Kinesis data stream for each applicatio
10. J. Write an AWS Lambda function to read usage data objects from the stream for each applicatio
11. K. Have the function perform .csv conversion, reformatting, and compression of the dat
12. L. Have the function store the output in Amazon S3.
13. M. Store usage data objects in an Amazon DynamoDB tabl
14. N. Configure a DynamoDB stream to copy the objects to an S3 bucke
15. O. Configure an AWS Lambda function to be triggered when objects are written to the S3 bucke
16. P. Have the function convert the objects into .csv format.

Correct Answer: A

A company has an application that uses the Amazon Kinesis Client Library (KCL) to read records from a Kinesis data stream.
After a successful marketing campaign, the application experienced a significant increase in usage. As a result, a data analyst had to split some shards in the data stream. When the shards were split, the application started
throwing an ExpiredIteratorExceptions error sporadically. What should the data analyst do to resolve this?

1. A. Increase the number of threads that process the stream records.
2. B. Increase the provisioned read capacity units assigned to the stream’s Amazon DynamoDB table.
3. C. Increase the provisioned write capacity units assigned to the stream’s Amazon DynamoDB table.
4. D. Decrease the provisioned write capacity units assigned to the stream’s Amazon DynamoDB table.

Correct Answer: C

A company wants to research user turnover by analyzing the past 3 months of user activities. With millions of users, 1.5 TB of uncompressed data is generated each day. A 30-node Amazon Redshift cluster with 2.56 TB of solid state drive (SSD) storage for each node is required to meet the query performance goals.
The company wants to run an additional analysis on a year’s worth of historical data to examine trends indicating which features are most popular. This analysis will be done once a week.
What is the MOST cost-effective solution?

1. A. Increase the size of the Amazon Redshift cluster to 120 nodes so it has enough storage capacity to hold 1 year of dat
2. B. Then use Amazon Redshift for the additional analysis.
3. C. Keep the data from the last 90 days in Amazon Redshif
4. D. Move data older than 90 days to Amazon S3 and store it in Apache Parquet format partitioned by dat
5. E. Then use Amazon Redshift Spectrum for the additional analysis.
6. F. Keep the data from the last 90 days in Amazon Redshif
7. G. Move data older than 90 days to Amazon S3 and store it in Apache Parquet format partitioned by dat
8. H. Then provision a persistent Amazon EMR cluster and use Apache Presto for the additional analysis.
9. I. Resize the cluster node type to the dense storage node type (DS2) for an additional 16 TB storagecapacity on each individual node in the Amazon Redshift cluste
10. J. Then use Amazon Redshift for the additional analysis.

Correct Answer: B

A company wants to enrich application logs in near-real-time and use the enriched dataset for further analysis. The application is running on Amazon EC2 instances across multiple Availability Zones and storing its logs using Amazon CloudWatch Logs. The enrichment source is stored in an Amazon DynamoDB table.
Which solution meets the requirements for the event collection and enrichment?

1. A. Use a CloudWatch Logs subscription to send the data to Amazon Kinesis Data Firehos
2. B. Use AWS Lambda to transform the data in the Kinesis Data Firehose delivery stream and enrich it with the data inthe DynamoDB tabl
3. C. Configure Amazon S3 as the Kinesis Data Firehose delivery destination.
4. D. Export the raw logs to Amazon S3 on an hourly basis using the AWS CL
5. E. Use AWS Glue crawlers to catalog the log
6. F. Set up an AWS Glue connection for the DynamoDB table and set up an AWS Glue ETL job to enrich the dat
7. G. Store the enriched data in Amazon S3.
8. H. Configure the application to write the logs locally and use Amazon Kinesis Agent to send the data to Amazon Kinesis Data Stream
9. I. Configure a Kinesis Data Analytics SQL application with the Kinesis data stream as the sourc
10. J. Join the SQL application input stream with DynamoDB records, and then store the enriched output stream in Amazon S3 using Amazon Kinesis Data Firehose.
11. K. Export the raw logs to Amazon S3 on an hourly basis using the AWS CL
12. L. Use Apache Spark SQL on Amazon EMR to read the logs from Amazon S3 and enrich the records with the data from DynamoD
13. M. Store the enriched data in Amazon S3.

Correct Answer: A
https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/SubscriptionFilters.html#FirehoseExample

A large financial company is running its ETL process. Part of this process is to move data from Amazon S3 into an Amazon Redshift cluster. The company wants to use the most cost-efficient method to load the dataset into Amazon Redshift.
Which combination of steps would meet these requirements? (Choose two.)

1. A. Use the COPY command with the manifest file to load data into Amazon Redshift.
2. B. Use S3DistCp to load files into Amazon Redshift.
3. C. Use temporary staging tables during the loading process.
4. D. Use the UNLOAD command to upload data into Amazon Redshift.
5. E. Use Amazon Redshift Spectrum to query files from Amazon S3.

Correct Answer: AC