Amazon DAS-C01 Dumps

Amazon DAS-C01 Dumps

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Frequently Asked Questions

AWS DAS-C01 Sample Questions

Question # 1

A human resources company maintains a 10-node Amazon Redshift cluster to run analytics queries on the company’s data. The Amazon Redshift cluster contains a product table and a transactions table, and both tables have a product_sku column. The tables are over 100 GB in size. The majority of queries run on both tables.Which distribution style should the company use for the two tables to achieve optimal query performance?

A. An EVEN distribution style for both tables 
B. A KEY distribution style for both tables 
C. An ALL distribution style for the product table and an EVEN distribution style for the transactions table 
D. An EVEN distribution style for the product table and an KEY distribution style for the transactions table 

ANSWER : B

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Question # 2

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

ANSWER : C

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Question # 3

An analytics software as a service (SaaS) provider wants to offer its customers business intelligence <BI) reporting capabilities that are self-service The provider is using AmazonQuickSight to build these reports The data for the reports resides in a multi-tenant database, but each customer should only be able to access their own data The provider wants to give customers two user role options • Read-only users for individuals who only need to view dashboards • Power users for individuals who are allowed to create and share new dashboards withother users Which QuickSight feature allows the provider to meet these requirements'?

A. Embedded dashboards 
B. Table calculations 
C. Isolated namespaces 
D. SPICE 

ANSWER : A

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Question # 4

A software company wants to use instrumentation data to detect and resolve errors to improve application recovery time. The company requires API usage anomalies, like error rate and response time spikes, to be detected in near-real time (NRT) The company also requires that data analysts have access to dashboards for log analysis in NRT Which solution meets these requirements'? 

A. Use Amazon Kinesis Data Firehose as the data transport layer for logging data Use Amazon Kinesis Data Analytics to uncover the NRT API usage anomalies Use Kinesis Data Firehose to deliver log data to Amazon OpenSearch Service (Amazon Elasticsearch Service) for search, log analytics, and application monitoring Use OpenSearch Dashboards (Kibana) in Amazon OpenSearch Service (Amazon Elasticsearch Service) for the dashboards. 
B. Use Amazon Kinesis Data Analytics as the data transport layer for logging data. Use Amazon Kinesis Data Streams to uncover NRT monitoring metrics. Use Amazon Kinesis Data Firehose to deliver log data to Amazon OpenSearch Service (Amazon Elasticsearch Service) for search, log analytics, and application monitoring Use Amazon QuickSight for the dashboards 
C. Use Amazon Kinesis Data Analytics as the data transport layer for logging data and to uncover NRT monitoring metrics Use Amazon Kinesis Data Firehose to deliver log data to Amazon OpenSearch Service (Amazon Elasticsearch Service) for search, log analytics, and application monitoring Use OpenSearch Dashboards (Kibana) in Amazon OpenSearch Service (Amazon Elasticsearch Service) for the dashboards 
D. Use Amazon Kinesis Data Firehose as the data transport layer for logging data Use Amazon Kinesis Data Analytics to uncover NRT monitoring metrics Use Amazon Kinesis Data Streams to deliver log data to Amazon OpenSearch Service (Amazon Elasticsearch Service) for search, log analytics, and application monitoring Use Amazon QuickSight for the dashboards.

ANSWER : C

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