| Exam Name: | AWS Certified Data Analytics - Specialty | ||
| Exam Code: | DAS-C01 Dumps | ||
| Vendor: | Amazon Web Services | Certification: | AWS Certified Data Analytics |
| Questions: | 207 Q&A's | Shared By: | dawson |
A company is designing a data warehouse to support business intelligence reporting. Users will access the executive dashboard heavily each Monday and Friday morning
for I hour. These read-only queries will run on the active Amazon Redshift cluster, which runs on dc2.8xIarge compute nodes 24 hours a day, 7 days a week. There are
three queues set up in workload management: Dashboard, ETL, and System. The Amazon Redshift cluster needs to process the queries without wait time.
What is the MOST cost-effective way to ensure that the cluster processes these queries?
A technology company is creating a dashboard that will visualize and analyze time-sensitive data. The data will come in through Amazon Kinesis DataFirehose with the butter interval set to 60 seconds. The dashboard must support near-real-time data.
Which visualization solution will meet these requirements?
A company has developed several AWS Glue jobs to validate and transform its data from Amazon S3 and load it into Amazon RDS for MySQL in batches once every day. The ETL jobs read the S3 data using a DynamicFrame. Currently, the ETL developers are experiencing challenges in processing only the incremental data on every run, as the AWS Glue job processes all the S3 input data on each run.
Which approach would allow the developers to solve the issue with minimal coding effort?
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?
TESTED 22 Nov 2024
