A retail company has 15 stores across 6 cities in the United States. Once a month, the sales team requests a visualization in Amazon QuickSight that provides the ability to easily identify revenue trends across cities and stores. The visualization also helps identify outliers that need to be examined with further analysis.
Which visual type in QuickSight meets the sales team's requirements?

• A.Tree map
• B.Geospatial chart
• C.Heat map
• D.Line chart

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A media content company has a streaming playback application. The company wants to collect and analyze the data to provide near-real-time feedback on playback issues. The company needs to consume this data and return results within 30 seconds according to the service-level agreement (SLA). The company needs the consumer to identify playback issues, such as quality during a specified timeframe. The data will be emitted as JSON and may change schemas over time.
Which solution will allow the company to collect data for processing while meeting these requirements?

• A.Send the data to Amazon Kinesis Data Firehose with delivery to Amazon S3. Configure an S3 event trigger an AWS Lambda function to process the data. The Lambda function will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon S3.
• B.Send the data to Amazon Managed Streaming for Kafka and configure an Amazon Kinesis Analytics for Java application as the consumer. The application will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon DynamoDB.
• C.Send the data to Amazon Kinesis Data Firehose with delivery to Amazon S3. Configure Amazon S3 to trigger an event for AWS Lambda to process. The Lambda function will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon DynamoDB.
• D.Send the data to Amazon Kinesis Data Streams and configure an Amazon Kinesis Analytics for Java application as the consumer. The application will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon S3.

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A real estate company has a mission-critical application using Apache HBase in Amazon EMR. Amazon EMR is configured with a single master node. The company has over 5 TB of data stored on an Hadoop Distributed File System (HDFS). The company wants a cost-effective solution to make its HBase data highly available.
Which architectural pattern meets company's requirements?

• A.Store the data on an EMR File System (EMRFS) instead of HDFS and enable EMRFS consistent view.
  Create a primary EMR HBase cluster with multiple master nodes. Create a secondary EMR HBase read- replica cluster in a separate Availability Zone. Point both clusters to the same HBase root directory in the same Amazon S3 bucket.
• B.Store the data on an EMR File System (EMRFS) instead of HDFS. Enable EMRFS consistent view.
  Create an EMR HBase cluster with multiple master nodes. Point the HBase root directory to an Amazon S3 bucket.
• C.Store the data on an EMR File System (EMRFS) instead of HDFS and enable EMRFS consistent view.
  Run two separate EMR clusters in two different Availability Zones. Point both clusters to the same HBase root directory in the same Amazon S3 bucket.
• D.Use Spot Instances for core and task nodes and a Reserved Instance for the EMR master node.
  Configure
  the EMR cluster with multiple master nodes. Schedule automated snapshots using Amazon EventBridge.

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A company has a data lake on AWS that ingests sources of data from multiple business units and uses Amazon Athena for queries. The storage layer is Amazon S3 using the AWS Glue Data Catalog. The company wants to make the data available to its data scientists and business analysts. However, the company first needs to manage data access for Athena based on user roles and responsibilities.
What should the company do to apply these access controls with the LEAST operational overhead?

• A.Define security policy-based rules for the tables and columns by role in AWS Glue.
• B.Define security policy-based rules for the users and applications by role in AWS Lake Formation.
• C.Define security policy-based rules for the users and applications by role in AWS Identity and Access Management (IAM).
• D.Define security policy-based rules for the tables and columns by role in AWS Identity and Access Management (IAM).

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A global company has different sub-organizations, and each sub-organization sells its products and services in various countries. The company's senior leadership wants to quickly identify which sub-organization is the strongest performer in each country. All sales data is stored in Amazon S3 in Parquet format.
Which approach can provide the visuals that senior leadership requested with the least amount of effort?

• A.Use Amazon QuickSight with Amazon Athena as the data source. Use heat maps as the visual type.
• B.Use Amazon QuickSight with Amazon S3 as the data source. Use pivot tables as the visual type.
• C.Use Amazon QuickSight with Amazon Athena as the data source. Use pivot tables as the visual type.
• D.Use Amazon QuickSight with Amazon S3 as the data source. Use heat maps as the visual type.

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