New AWS-Certified-Data-Analytics-Specialty Practice Materials | Amazon New AWS-Certified-Data-Analytics-Specialty Exam Camp: AWS Certified Data Analytics - Specialty (DAS-C01) Exam Latest Released
New AWS-Certified-Data-Analytics-Specialty Practice Materials | Amazon New AWS-Certified-Data-Analytics-Specialty Exam Camp: AWS Certified Data Analytics - Specialty (DAS-C01) Exam Latest Released
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To take the AWS Certified Data Analytics - Specialty (DAS-C01) certification exam, candidates must have at least five years of experience in data analytics or a related field. Candidates must also have a deep understanding of AWS services and the ability to design, implement, and troubleshoot data analytics solutions on AWS. AWS-Certified-Data-Analytics-Specialty exam consists of 65 multiple-choice and multiple-response questions, and candidates have 180 minutes to complete the exam.
To prepare for the Amazon DAS-C01 Certification Exam, candidates must have a solid understanding of AWS data analytics services such as Amazon Kinesis, Amazon Redshift, Amazon EMR, Amazon Athena, and Amazon QuickSight. They must also have experience in data analytics architectures, data security, and data governance. AWS-Certified-Data-Analytics-Specialty Exam consists of multiple-choice and multiple-answer questions, and candidates have 180 minutes to complete it.
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Amazon AWS Certified Data Analytics - Specialty (DAS-C01) Exam Sample Questions (Q18-Q23):
NEW QUESTION # 18
A US-based sneaker retail company launched its global website. All the transaction data is stored in Amazon RDS and curated historic transaction data is stored in Amazon Redshift in the us-east-1 Region. The business intelligence (BI) team wants to enhance the user experience by providing a dashboard for sneaker trends.
The BI team decides to use Amazon QuickSight to render the website dashboards. During development, a team in Japan provisioned Amazon QuickSight in ap-northeast-1. The team is having difficulty connecting Amazon QuickSight from ap-northeast-1 to Amazon Redshift in us-east-1.
Which solution will solve this issue and meet the requirements?
- A. Create a new security group for Amazon Redshift in us-east-1 with an inbound rule authorizing access from the appropriate IP address range for the Amazon QuickSight servers in ap-northeast-1.
- B. In the Amazon Redshift console, choose to configure cross-Region snapshots and set the destination Region as ap-northeast-1. Restore the Amazon Redshift Cluster from the snapshot and connect to Amazon QuickSight launched in ap-northeast-1.
- C. Create an Amazon Redshift endpoint connection string with Region information in the string and use this connection string in Amazon QuickSight to connect to Amazon Redshift.
- D. Create a VPC endpoint from the Amazon QuickSight VPC to the Amazon Redshift VPC so Amazon QuickSight can access data from Amazon Redshift.
Answer: D
NEW QUESTION # 19
An ecommerce company is migrating its business intelligence environment from on premises to the AWS Cloud. The company will use Amazon Redshift in a public subnet and Amazon QuickSight. The tables already are loaded into Amazon Redshift and can be accessed by a SQL tool.
The company starts QuickSight for the first time. During the creation of the data source, a data analytics specialist enters all the information and tries to validate the connection. An error with the following message occurs: "Creating a connection to your data source timed out." How should the data analytics specialist resolve this error?
- A. Create an IAM role for QuickSight to access Amazon Redshift.
- B. Grant the SELECT permission on Amazon Redshift tables.
- C. Add the QuickSight IP address range into the Amazon Redshift security group.
- D. Use a QuickSight admin user for creating the dataset.
Answer: B
Explanation:
Explanation
Connection to the database times out
Your client connection to the database appears to hang or time out when running long queries, such as a COPY command. In this case, you might observe that the Amazon Redshift console displays that the query has completed, but the client tool itself still appears to be running the query. The results of the query might be missing or incomplete depending on when the connection stopped.
NEW QUESTION # 20
A retail company leverages Amazon Athena for ad-hoc queries against an AWS Glue Data Catalog. The data analytics team manages the data catalog and data access for the company. The data analytics team wants to separate queries and manage the cost of running those queries by different workloads and teams. Ideally, the data analysts want to group the queries run by different users within a team, store the query results in individual Amazon S3 buckets specific to each team, and enforce cost constraints on the queries run against the Data Catalog.
Which solution meets these requirements?
- A. Create Athena workgroups for each team within the company. Set up IAM workgroup policies that control user access and actions on the workgroup resources.
- B. Create IAM groups and resource tags for each team within the company. Set up IAM policies that control user access and actions on the Data Catalog resources.
- C. Create Athena query groups for each team within the company and assign users to the groups.
- D. Create Athena resource groups for each team within the company and assign users to these groups. Add S3 bucket names and other query configurations to the properties list for the resource groups.
Answer: A
Explanation:
Explanation
https://aws.amazon.com/about-aws/whats-new/2019/02/athena_workgroups/
NEW QUESTION # 21
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 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.
- B. 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.
- C. 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.
- 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: D
NEW QUESTION # 22
A large university has adopted a strategic goal of increasing diversity among enrolled students. The data analytics team is creating a dashboard with data visualizations to enable stakeholders to view historical trends.
All access must be authenticated using Microsoft Active Directory. All data in transit and at rest must be encrypted.
Which solution meets these requirements?
- A. Amazon QuickSight Enterprise edition using AD Connector to authenticate using Active Directory.
Configure Amazon QuickSight to use customer-provided keys imported into AWS KMS. - B. Amazon QuickSight Enterprise edition configured to perform identity federation using SAML 2.0 and the default encryption settings.
- C. Amazon QuickSight Standard edition configured to perform identity federation using SAML 2.0. and the default encryption settings.
- D. Amazon QuckSight Standard edition using AD Connector to authenticate using Active Directory.
Configure Amazon QuickSight to use customer-provided keys imported into AWS KMS.
Answer: A
NEW QUESTION # 23
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