EXCELLENT DAS-C01 VCE TEST SIMULATOR - 100% PASS DAS-C01 EXAM

Excellent DAS-C01 Vce Test Simulator - 100% Pass DAS-C01 Exam

Excellent DAS-C01 Vce Test Simulator - 100% Pass DAS-C01 Exam

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Our AWS Certified Data Analytics - Specialty (DAS-C01) Exam study question is compiled and verified by the first-rate experts in the industry domestically and they are linked closely with the real exam. Our products’ contents cover the entire syllabus of the exam and refer to the past years’ exam papers. Our test bank provides all the questions which may appear in the real exam and all the important information about the exam. You can use the practice test software to test whether you have mastered the AWS Certified Data Analytics - Specialty (DAS-C01) Exam test practice dump and the function of stimulating the exam to be familiar with the real exam’s pace, atmosphere and environment. So our DAS-C01 Exam Questions are real-exam-based and convenient for the clients to prepare for the exam.

The Amazon DAS-C01 Exam includes multiple-choice and multiple-response questions, as well as scenario-based questions that require the candidate to apply their knowledge to real-world situations. DAS-C01 exam is timed and lasts for 3 hours. Candidates must score at least 750 out of 1000 to pass the exam and earn their certification.

Understanding functional and technical aspects of AWS Certified Data Analytics - Specialty (DAS-C01) Professional Exam Design for Organizational Complexity

The following will be dicussed in AMAZON DAS C01 exam dumps:

  • Pick a collection system that addresses the essential attributes of data, such as order, format, and compression
  • Choose a collection system that manages the cycle, volume, and source of data
  • Define the operational features of the collection system
  • Explain the Amazon Web Services Cloud & the value it provides:

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The cost of the AWS AWS Certified Data Analytics - Specialty (DAS-C01) Professional Exam is 300 USD. For more information related to exam price, please visit the official website AWS Website as the cost of exams may be subjected to vary county-wise.

Amazon AWS Certified Data Analytics - Specialty (DAS-C01) Exam Sample Questions (Q65-Q70):

NEW QUESTION # 65
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?

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

Answer: C

Explanation:
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.


NEW QUESTION # 66
A financial services company needs to aggregate daily stock trade data from the exchanges into a data store.
The company requires that data be streamed directly into the data store, but also occasionally allows data to be modified using SQL. The solution should integrate complex, analytic queries running with minimal latency.
The solution must provide a business intelligence dashboard that enables viewing of the top contributors to anomalies in stock prices.
Which solution meets the company's requirements?

  • A. Use Amazon Kinesis Data Firehose to stream data to Amazon Redshift. Use Amazon Redshift as a data source for Amazon QuickSight to create a business intelligence dashboard.
  • B. Use Amazon Kinesis Data Streams to stream data to Amazon S3. Use Amazon Athena as a data source for Amazon QuickSight to create a business intelligence dashboard.
  • C. Use Amazon Kinesis Data Streams to stream data to Amazon Redshift. Use Amazon Redshift as a data source for Amazon QuickSight to create a business intelligence dashboard.
  • D. Use Amazon Kinesis Data Firehose to stream data to Amazon S3. Use Amazon Athena as a data source for Amazon QuickSight to create a business intelligence dashboard.

Answer: B


NEW QUESTION # 67
A market data company aggregates external data sources to create a detailed view of product consumption in different countries. The company wants to sell this data to external parties through a subscription. To achieve this goal, the company needs to make its data securely available to external parties who are also AWS users.
What should the company do to meet these requirements with the LEAST operational overhead?

  • A. Store the data in Amazon S3. Share the data by using S3 bucket ACLs.
  • B. Store the data in Amazon S3. Share the data by using presigned URLs for security.
  • C. Upload the data to AWS Data Exchange for storage. Share the data by using the AWS Data Exchange sharing wizard.
  • D. Upload the data to AWS Data Exchange for storage. Share the data by using presigned URLs for security.

Answer: B


NEW QUESTION # 68
A marketing company wants to improve its reporting and business intelligence capabilities. During the planning phase, the company interviewed the relevant stakeholders and discovered that:
* The operations team reports are run hourly for the current month's data.
* The sales team wants to use multiple Amazon QuickSight dashboards to show a rolling view of the last
30 days based on several categories.
* The sales team also wants to view the data as soon as it reaches the reporting backend.
* The finance team's reports are run daily for last month's data and once a month for the last 24 months of data.
Currently, there is 400 TB of data in the system with an expected additional 100 TB added every month. The company is looking for a solution that is as cost-effective as possible.
Which solution meets the company's requirements?

  • A. Store the last 24 months of data in Amazon Redshift. Configure Amazon QuickSight with Amazon Redshift as the data source.
  • B. Store the last 2 months of data in Amazon Redshift and the rest of the months in Amazon S3. Set up an external schema and table for Amazon Redshift Spectrum. Configure Amazon QuickSight with Amazon Redshift as the data source.
  • C. Store the last 2 months of data in Amazon Redshift and the rest of the months in Amazon S3. Use a long- running Amazon EMR with Apache Spark cluster to query the data as needed. Configure Amazon QuickSight with Amazon EMR as the data source.
  • D. Store the last 24 months of data in Amazon S3 and query it using Amazon Redshift Spectrum.
    Configure Amazon QuickSight with Amazon Redshift Spectrum as the data source.

Answer: B


NEW QUESTION # 69
An education provider's learning management system (LMS) is hosted in a 100 TB data lake that is built on Amazon S3. The provider's LMS supports hundreds of schools. The provider wants to build an advanced analytics reporting platform using Amazon Redshift to handle complex queries with optimal performance. System users will query the most recent 4 months of data 95% of the time while 5% of the queries will leverage data from the previous 12 months.
Which solution meets these requirements in the MOST cost-effective way?

  • A. Store the most recent 4 months of data in the Amazon Redshift cluster. Use Amazon Redshift federated queries to join cluster data with the data lake to reduce costs. Ensure the S3 Standard storage class is in use with objects in the data lake.
  • B. Store the most recent 4 months of data in the Amazon Redshift cluster. Use Amazon Redshift Spectrum to query data in the data lake. Use S3 lifecycle management rules to store data from the previous 12 months in Amazon S3 Glacier storage.
  • C. Store the most recent 4 months of data in the Amazon Redshift cluster. Use Amazon Redshift Spectrum to query data in the data lake. Ensure the S3 Standard storage class is in use with objects in the data lake.
  • D. Leverage DS2 nodes for the Amazon Redshift cluster. Migrate all data from Amazon S3 to Amazon Redshift. Decommission the data lake.

Answer: C


NEW QUESTION # 70
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