DAS-C01 Free Practice Test

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?

1. A. Use an AWS Glue crawler to create and update a table in the Glue data catalog from the log
2. B. Use Athena to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.
3. C. Create a second Kinesis Data Firehose delivery stream to deliver the log files to Amazon Elasticsearch Service (Amazon ES). Use Amazon ES to perform text-based searches of the logs for ad-hoc analyses and use Kibana for data visualizations.
4. D. Create an AWS Lambda function to convert the logs into .csv forma
5. E. Then add the function to the Kinesis Data Firehose transformation configuratio
6. F. Use Amazon Redshift to perform ad-hoc analyses of the logs using SQL queries and use Amazon QuickSight to develop data visualizations.
7. G. Create an Amazon EMR cluster and use Amazon S3 as the data sourc
8. H. Create an Apache Spark job to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.

Correct Answer: A
https://aws.amazon.com/blogs/big-data/analyzing-aws-waf-logs-with-amazon-es-amazon-athena-and-amazon-qu

A banking company wants to collect large volumes of transactional data using Amazon Kinesis Data Streams for real-time analytics. The company uses PutRecord to send data to Amazon Kinesis, and has observed network outages during certain times of the day. The company wants to obtain exactly once semantics for the entire processing pipeline.
What should the company do to obtain these characteristics?

1. A. Design the application so it can remove duplicates during processing be embedding a unique ID in each record.
2. B. Rely on the processing semantics of Amazon Kinesis Data Analytics to avoid duplicate processing of events.
3. C. Design the data producer so events are not ingested into Kinesis Data Streams multiple times.
4. D. Rely on the exactly one processing semantics of Apache Flink and Apache Spark Streaming included in Amazon EMR.

Correct Answer: A

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.)

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

Correct Answer: BCF

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?

1. A. Use an AWS Glue job nightly to transform new log files into .csv format and partition by year, month, and da
2. B. Use AWS Glue crawlers to detect new partition
3. C. Use Amazon Athena to query data.
4. 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
5. E. Use Apache Presto to query the optimized format.
6. F. Launch a transient Amazon EMR cluster nightly to transform new log files into Apache ORC format and partition by year, month, and da
7. G. Use Amazon Redshift Spectrum to query the data.
8. H. Use an AWS Glue job nightly to transform new log files into Apache Parquet format and partition by year, month, and da
9. I. Use AWS Glue crawlers to detect new partition
10. J. Use Amazon Athena to querydata.

Correct Answer: C

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?

1. A. Increase the number of retrie
2. B. Decrease the timeout valu
3. C. Increase the job concurrency.
4. D. Keep the number of retries at 0. Decrease the timeout valu
5. E. Increase the job concurrency.
6. F. Keep the number of retries at 0. Decrease the timeout valu
7. G. Keep the job concurrency at 1.
8. H. Keep the number of retries at 0. Increase the timeout valu
9. I. Keep the job concurrency at 1.

Correct Answer: B