DUMP AWS-CERTIFIED-DATA-ANALYTICS-SPECIALTY FILE & VALID AWS-CERTIFIED-DATA-ANALYTICS-SPECIALTY TEST PRACTICE

Dump AWS-Certified-Data-Analytics-Specialty File & Valid AWS-Certified-Data-Analytics-Specialty Test Practice

Dump AWS-Certified-Data-Analytics-Specialty File & Valid AWS-Certified-Data-Analytics-Specialty Test Practice

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The DAS-C01 exam is intended for AWS solution architects, developers, data analysts, and data scientists who want to enhance their skills in data analytics. AWS-Certified-Data-Analytics-Specialty Exam requires a solid understanding of AWS fundamentals, as well as proficiency in designing and implementing data analytics solutions on the AWS platform. Earning this certification demonstrates a candidate's ability to leverage AWS data services to deliver insights and value to their organization.

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Amazon AWS Certified Data Analytics - Specialty (DAS-C01) Exam Sample Questions (Q45-Q50):

NEW QUESTION # 45
A company wants to improve the data load time of a sales data dashboard. Data has been collected as .csv files and stored within an Amazon S3 bucket that is partitioned by date. The data is then loaded to an Amazon Redshift data warehouse for frequent analysis. The data volume is up to 500 GB per day.
Which solution will improve the data loading performance?

  • A. Load the .csv files in an unsorted key order and vacuum the table in Amazon Redshift.
  • B. Use Amazon Kinesis Data Firehose to ingest data into Amazon Redshift.
  • C. Compress .csv files and use an INSERT statement to ingest data into Amazon Redshift.
  • D. Split large .csv files, then use a COPY command to load data into Amazon Redshift.

Answer: D

Explanation:
https://docs.aws.amazon.com/redshift/latest/dg/c_loading-data-best-practices.html


NEW QUESTION # 46
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 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.
  • B. 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.
  • C. Store the last 24 months of data in Amazon Redshift. Configure Amazon QuickSight with Amazon Redshift 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: A


NEW QUESTION # 47
A company stores its sales and marketing data that includes personally identifiable information (PII) in Amazon S3. The company allows its analysts to launch their own Amazon EMR cluster and run analytics reports with the data. To meet compliance requirements, the company must ensure the data is not publicly accessible throughout this process. A data engineer has secured Amazon S3 but must ensure the individual EMR clusters created by the analysts are not exposed to the public internet.
Which solution should the data engineer to meet this compliance requirement with LEAST amount of effort?

  • A. Check the security group of the EMR clusters regularly to ensure it does not allow inbound traffic from IPv4 0.0.0.0/0 or IPv6 ::/0.
  • B. Use AWS WAF to block public internet access to the EMR clusters across the board.
  • C. Enable the block public access setting for Amazon EMR at the account level before any EMR cluster is created.
  • D. Create an EMR security configuration and ensure the security configuration is associated with the EMR clusters when they are created.

Answer: A


NEW QUESTION # 48
A company hosts an Apache Flink application on premises. The application processes data from several Apache Kafka clusters. The data originates from a variety of sources, such as web applications mobile apps and operational databases The company has migrated some of these sources to AWS and now wants to migrate the Flink application. The company must ensure that data that resides in databases within the VPC does not traverse the internet The application must be able to process all the data that comes from the company's AWS solution, on-premises resources and the public internet Which solution will meet these requirements with the LEAST operational overhead?

  • A. Implement Flink on Amazon EC2 within the company's VPC Create Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in the VPC to collect data that comes from applications and databases within the VPC Use Amazon Kinesis Data Streams to collect data that comes from the public internet Configure Flink to have sources from Kinesis Data Streams Amazon MSK and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect
  • B. Implement Flink on Amazon EC2 within the company's VPC Use Amazon Kinesis Data Streams to collect data that comes from applications and databases within the VPC and the public internet Configure Flink to have sources from Kinesis Data Streams and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect
  • C. Create an Amazon Kinesis Data Analytics application by uploading the compiled Flink jar file Create Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in the company's VPC to collect data that comes from applications and databases within the VPC Use Amazon Kinesis Data Streams to collect data that comes from the public internet Configure the Kinesis Data Analytics application to have sources from Kinesis Data Streams. Amazon MSK and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect
  • D. Create an Amazon Kinesis Data Analytics application by uploading the compiled Flink jar file Use Amazon Kinesis Data Streams to collect data that comes from applications and databases within the VPC and the public internet Configure the Kinesis Data Analytics application to have sources from Kinesis Data Streams and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

Answer: C


NEW QUESTION # 49
A large ride-sharing company has thousands of drivers globally serving millions of unique customers every day. The company has decided to migrate an existing data mart to Amazon Redshift. The existing schema includes the following tables.
* A trips fact table for information on completed rides.
* A drivers dimension table for driver profiles.
* A customers fact table holding customer profile information.
The company analyzes trip details by date and destination to examine profitability by region. The drivers data rarely changes. The customers data frequently changes.
What table design provides optimal query performance?

  • A. Use DISTSTYLE KEY (destination) for the trips table and sort by date. Use DISTSTYLE ALL for the drivers table. Use DISTSTYLE EVEN for the customers table.
  • B. Use DISTSTYLE EVEN for the trips table and sort by date. Use DISTSTYLE ALL for the drivers table.
    Use DISTSTYLE EVEN for the customers table.
  • C. Use DISTSTYLE EVEN for the drivers table and sort by date. Use DISTSTYLE ALL for both fact tables.
  • D. Use DISTSTYLE KEY (destination) for the trips table and sort by date. Use DISTSTYLE ALL for the drivers and customers tables.

Answer: D


NEW QUESTION # 50
......

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