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NEW QUESTION 52 A company using Amazon QuickSight Enterprise edition has thousands of dashboards analyses and datasets. The company struggles to manage and assign permissions for granting users access to various items within QuickSight. The company wants to make it easier to implement sharing and permissions management. Which solution should the company implement to simplify permissions management?

  • A. Use QuickSight folders to organize dashboards analyses, and datasets Assign group permissions by using these folders.
  • B. Use AWS 1AM resource-based policies to assign group permissions to QuickSight items
  • C. Use QuickSight folders to organize dashboards, analyses, and datasets Assign individual users permissions to these folders
  • D. Use QuickSight user management APIs to provision group permissions based on dashboard naming conventions

Answer: B   NEW QUESTION 53 A manufacturing company has been collecting IoT sensor data from devices on its factory floor for a year and is storing the data in Amazon Redshift for daily analysis. A data analyst has determined that, at an expected ingestion rate of about 2 TB per day, the cluster will be undersized in less than 4 months. A long-term solution is needed. The data analyst has indicated that most queries only reference the most recent 13 months of data, yet there are also quarterly reports that need to query all the data generated from the past 7 years. The chief technology officer (CTO) is concerned about the costs, administrative effort, and performance of a long-term solution. Which solution should the data analyst use to meet these requirements?

  • A. Execute a CREATE TABLE AS SELECT (CTAS) statement to move records that are older than 13 months to quarterly partitioned data in Amazon Redshift Spectrum backed by Amazon S3.
  • B. Create a daily job in AWS Glue to UNLOAD records older than 13 months to Amazon S3 and delete those records from Amazon Redshift. Create an external table in Amazon Redshift to point to the S3 location. Use Amazon Redshift Spectrum to join to data that is older than 13 months.
  • C. Unload all the tables in Amazon Redshift to an Amazon S3 bucket using S3 Intelligent-Tiering. Use AWS Glue to crawl the S3 bucket location to create external tables in an AWS Glue Data Catalog. Create an Amazon EMR cluster using Auto Scaling for any daily analytics needs, and use Amazon Athena for the quarterly reports, with both using the same AWS Glue Data Catalog.
  • D. Take a snapshot of the Amazon Redshift cluster. Restore the cluster to a new cluster using dense storage nodes with additional storage capacity.

Answer: B   NEW QUESTION 54 A data analyst is designing a solution to interactively query datasets with SQL using a JDBC connection. Users will join data stored in Amazon S3 in Apache ORC format with data stored in Amazon Elasticsearch Service (Amazon ES) and Amazon Aurora MySQL. Which solution will provide the MOST up-to-date results?

  • A. Query all the datasets in place with Apache Presto running on Amazon EMR.
  • B. Use AWS Glue jobs to ETL data from Amazon ES and Aurora MySQL to Amazon S3. Query the data with Amazon Athena.
  • C. Query all the datasets in place with Apache Spark SQL running on an AWS Glue developer endpoint.
  • D. Use Amazon DMS to stream data from Amazon ES and Aurora MySQL to Amazon Redshift. Query the data with Amazon Redshift.

Answer: C   NEW QUESTION 55 A retail company is building its data warehouse solution using Amazon Redshift. As a part of that effort, the company is loading hundreds of files into the fact table created in its Amazon Redshift cluster. The company wants the solution to achieve the highest throughput and optimally use cluster resources when loading data into the company's fact table. How should the company meet these requirements?

  • A. Use LOAD commands equal to the number of Amazon Redshift cluster nodes and load the data in parallel into each node.
  • B. Use multiple COPY commands to load the data into the Amazon Redshift cluster.
  • C. Use a single COPY command to load the data into the Amazon Redshift cluster.
  • D. Use S3DistCp to load multiple files into the Hadoop Distributed File System (HDFS) and use an HDFS connector to ingest the data into the Amazon Redshift cluster.

Answer: D   NEW QUESTION 56 ......