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NEW QUESTION 28
A financial company hosts a data lake in Amazon S3 and a data warehouse on an Amazon Redshift cluster.
The company uses Amazon QuickSight to build dashboards and wants to secure access from its on-premises Active Directory to Amazon QuickSight.
How should the data be secured?

• A. Use an Active Directory connector and single sign-on (SSO) in a corporate network environment.
• B. Place Amazon QuickSight and Amazon Redshift in the security group and use an Amazon S3 endpoint to connect Amazon QuickSight to Amazon S3.
• C. Use a VPC endpoint to connect to Amazon S3 from Amazon QuickSight and an IAM role to authenticate Amazon Redshift.
• D. Establish a secure connection by creating an S3 endpoint to connect Amazon QuickSight and a VPC endpoint to connect to Amazon Redshift.

Answer: C

NEW QUESTION 29
A company wants to collect and process events data from different departments in near-real time. Before storing the data in Amazon S3, the company needs to clean the data by standardizing the format of the address and timestamp columns. The data varies in size based on the overall load at each particular point in time. A single data record can be 100 KB-10 MB.
How should a data analytics specialist design the solution for data ingestion?

• A. Use Amazon Kinesis Data Firehose. Configure a Firehose delivery stream with a preprocessing AWS Lambda function for data cleansing. Use a Kinesis Agent to write data to the delivery stream. Configure Kinesis Data Firehose to deliver the data to Amazon S3.
• B. Use Amazon Managed Streaming for Apache Kafka. Configure a topic for the raw data. Use a Kafka producer to write data to the topic. Create an application on Amazon EC2 that reads data from the topic by using the Apache Kafka consumer API, cleanses the data, and writes to Amazon S3.
• C. Use Amazon Kinesis Data Streams. Configure a stream for the raw data. Use a Kinesis Agent to write data to the stream. Create an Amazon Kinesis Data Analytics application that reads data from the raw stream, cleanses it, and stores the output to Amazon S3.
• D. Use Amazon Simple Queue Service (Amazon SQS). Configure an AWS Lambda function to read events from the SQS queue and upload the events to Amazon S3.

Answer: A

NEW QUESTION 30
An ecommerce company stores customer purchase data in Amazon RDS. The company wants a solution to store and analyze historical data. The most recent 6 months of data will be queried frequently for analytics workloads. This data is several terabytes large. Once a month, historical data for the last 5 years must be accessible and will be joined with the more recent data. The company wants to optimize performance and cost.
Which storage solution will meet these requirements?

• A. Use an ETL tool to incrementally load the most recent 6 months of data into an Amazon Redshift cluster.
  Run more frequent queries against this cluster. Create a read replica of the RDS database to run queries on the historical data.
• B. Create a read replica of the RDS database to store the most recent 6 months of data. Copy the historical data into Amazon S3. Create an AWS Glue Data Catalog of the data in Amazon S3 and Amazon RDS.
  Run historical queries using Amazon Athena.
• C. Incrementally copy data from Amazon RDS to Amazon S3. Create an AWS Glue Data Catalog of the data in Amazon S3. Use Amazon Athena to query the data.
• D. Incrementally copy data from Amazon RDS to Amazon S3. Load and store the most recent 6 months of data in Amazon Redshift. Configure an Amazon Redshift Spectrum table to connect to all historical data.

Answer: D

NEW QUESTION 31
A company is hosting an enterprise reporting solution with Amazon Redshift. The application provides reporting capabilities to three main groups: an executive group to access financial reports, a data analyst group to run long-running ad-hoc queries, and a data engineering group to run stored procedures and ETL processes.
The executive team requires queries to run with optimal performance. The data engineering team expects queries to take minutes.
Which Amazon Redshift feature meets the requirements for this task?

• A. Concurrency scaling
• B. Short query acceleration (SQA)
• C. Workload management (WLM)
• D. Materialized views

Answer: D

Explanation:
Explanation
Materialized views:

NEW QUESTION 32
A media company is using Amazon QuickSight dashboards to visualize its national sales dat a. The dashboard is using a dataset with these fields: ID, date, time_zone, city, state, country, longitude, latitude, sales_volume, and number_of_items.
To modify ongoing campaigns, the company wants an interactive and intuitive visualization of which states across the country recorded a significantly lower sales volume compared to the national average.
Which addition to the company's QuickSight dashboard will meet this requirement?

• A. A drill through to other dashboards containing state-level sales volume data.
• B. A drill-down layer for state-level sales volume data.
• C. A geospatial color-coded chart of sales volume data across the country.
• D. A pivot table of sales volume data summed up at the state level.

Answer: D

NEW QUESTION 33
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