Free DAS-C01 Exam Braindumps

A central government organization is collecting events from various internal applications using Amazon Managed Streaming for Apache Kafka (Amazon MSK). The organization has configured a separate Kafka topic for each application to separate the data. For security reasons, the Kafka cluster has been configured to only allow TLS encrypted data and it encrypts the data at rest.
A recent application update showed that one of the applications was configured incorrectly, resulting in writing data to a Kafka topic that belongs to another application. This resulted in multiple errors in the analytics pipeline as data from different applications appeared on the same topic. After this incident, the organization wants to prevent applications from writing to a topic different than the one they should write to.
Which solution meets these requirements with the least amount of effort?

1. A. Create a different Amazon EC2 security group for each applicatio
2. B. Configure each security group to have access to a specific topic in the Amazon MSK cluste
3. C. Attach the security group to each application based on the topic that the applications should read and write to.
4. D. Install Kafka Connect on each application instance and configure each Kafka Connect instance to write to a specific topic only.
5. E. Use Kafka ACLs and configure read and write permissions for each topi
6. F. Use the distinguished name of the clients’ TLS certificates as the principal of the ACL.
7. G. Create a different Amazon EC2 security group for each applicatio
8. H. Create an Amazon MSK cluster and Kafka topic for each applicatio
9. I. Configure each security group to have access to the specific cluster.

Correct Answer: B

A company wants to use an automatic machine learning (ML) Random Cut Forest (RCF) algorithm to visualize complex real-world 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?

1. A. Use an AWS Glue ML transform to create a forecast and then use Amazon QuickSight to visualize the data.
2. B. Use Amazon QuickSight to visualize the data and then use ML-powered forecasting to forecast the key business metrics.
3. C. Use a pre-build ML AMI from the AWS Marketplace to create forecasts and then use Amazon QuickSight to visualize the data.
4. D. Use calculated fields to create a new forecast and then use Amazon QuickSight to visualize the data.

Correct Answer: A

A manufacturing company has been collecting IoT sensor data from devices on its factory floor for a year and is storing the data in Amazon Redshift for daily analysis. A data analyst has determined that, at an expected ingestion rate of about 2 TB per day, the cluster will be undersized in less than 4 months. A long-term solution is needed. The data analyst has indicated that most queries only reference the most recent 13 months of data, yet there are also quarterly reports that need to query all the data generated from the past 7 years. The chief technology officer (CTO) is concerned about the costs, administrative effort, and performance of a long-term solution.
Which solution should the data analyst use to meet these requirements?

1. A. Create a daily job in AWS Glue to UNLOAD records older than 13 months to Amazon S3 and delete those records from Amazon Redshif
2. B. Create an external table in Amazon Redshift to point to the S3 locatio
3. C. Use Amazon Redshift Spectrum to join to data that is older than 13 months.
4. D. Take a snapshot of the Amazon Redshift cluste
5. E. Restore the cluster to a new cluster using dense storage nodes with additional storage capacity.
6. F. Execute a CREATE TABLE AS SELECT (CTAS) statement to move records that are older than 13 months to quarterly partitioned data in Amazon Redshift Spectrum backed by Amazon S3.
7. G. Unload all the tables in Amazon Redshift to an Amazon S3 bucket using S3 Intelligent-Tierin
8. H. Use AWS Glue to crawl the S3 bucket location to create external tables in an AWS Glue Data Catalog.Create an Amazon EMR cluster using Auto Scaling for any daily analytics needs, and use Amazon Athena for the quarterly reports, with both using the same AWS Glue Data Catalog.

Correct Answer: A

A company is streaming its high-volume billing data (100 MBps) to Amazon Kinesis Data Streams. A data analyst partitioned the data on account_id to ensure that all records belonging to an account go to the same Kinesis shard and order is maintained. While building a custom consumer using the Kinesis Java SDK, the data analyst notices that, sometimes, the messages arrive out of order for account_id. Upon further investigation, the data analyst discovers the messages that are out of order seem to be arriving from different shards for the same account_id and are seen when a stream resize runs.
What is an explanation for this behavior and what is the solution?

1. A. There are multiple shards in a stream and order needs to be maintained in the shar
2. B. The data analyst needs to make sure there is only a single shard in the stream and no stream resize runs.
3. C. The hash key generation process for the records is not working correctl
4. D. The data analyst should generate an explicit hash key on the producer side so the records are directed to the appropriate shard accurately.
5. E. The records are not being received by Kinesis Data Streams in orde
6. F. The producer should use the PutRecords API call instead of the PutRecord API call with the SequenceNumberForOrdering parameter.
7. G. The consumer is not processing the parent shard completely before processing the child shards after a stream resiz
8. H. The data analyst should process the parent shard completely first before processing the child shards.

Correct Answer: D
https://docs.aws.amazon.com/streams/latest/dev/kinesis-using-sdk-java-after-resharding.html the parent shards that remain after the reshard could still contain data that you haven't read yet that was added to the stream before the reshard. If you read data from the child shards before having read all data from the parent shards, you could read data for a particular hash key out of the order given by the data records' sequence numbers.
Therefore, assuming that the order of the data is important, you should, after a reshard, always continue to read data from the parent shards until it is exhausted. Only then should you begin reading data from the child shards.

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?

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

Correct Answer: D