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WorksheetsRedshift 2
Total questions: 4
Worksheet time: 12mins
Amazon Redshift is used to store revenue data for a business. A data analyst must develop a dashboard that enables the company's sales staff to view previous revenue and anticipate revenue properly for the next months. Which solution will satisfy these needs the MOST EFFECTIVELY?
Create an Amazon QuickSight analysis by using the data in Amazon Redshift. Add a custom field in QuickSight that applies a linear regression function to the data. Publish the analysis as a dashboard.
Create a JavaScript dashboard by using D3.js charts and the data in Amazon Redshift. Export the data to Amazon SageMaker. Run a Python script to run a regression model to forecast revenue. Import the data back into Amazon Redshift. Add the new forecast information to the dashboard.
Create an Amazon QuickSight analysis by using the data in Amazon Redshift. Add a forecasting widget Publish the analysis as a dashboard.
Create an Amazon SageMaker model for forecasting. Integrate the model with an Amazon QuickSight dataset. Create a widget for the dataset. Publish the analysis as a dashboard.
A business owns an Amazon Redshift cluster that is encrypted. The organization just enabled audit logs in Amazon Redshift and wants to guarantee that audit logs are likewise encrypted at rest. The logs are kept for one year. The auditor conducts a monthly audit of the logs. How might these needs be met in the MOST cost-effective manner possible?
Encrypt the Amazon S3 bucket where the logs are stored by using AWS Key Management Service (AWS KMS). Copy the data into the Amazon Redshift cluster from Amazon S3 on a daily basis. Query the data as required
Enable default encryption on the Amazon S3 bucket where the logs are stored by using AES-256 encryption. Copy the data into the Amazon Redshift cluster from Amazon S3 on a daily basis. Query the data as required
Disable encryption on the Amazon Redshift cluster, configure audit logging, and encrypt the Amazon Redshift cluster. Use Amazon Redshift Spectrum to query the data as required
Enable default encryption on the Amazon S3 bucket where the logs are stored by using AES-256 encryption. Use Amazon Redshift Spectrum to query the data as required
A business stores its data on Amazon Redshift. The reporting team generates reports from the Amazon Redshift database using ad-hoc queries. Recently, the reporting team began to notice discrepancies in report creation. Ad-hoc queries, which are commonly used to create results in minutes, might take hours to perform. A data analytics professional troubleshooting the problem discovers that ad-hoc searches are being caught behind long-running inquiries in the queue. How should the data analyst address the situation?
Configure automatic workload management (WLM) from the Amazon Redshift console.
Create partitions in the tables queried in ad-hoc queries.
Create Amazon Simple Queue Service (Amazon SQS) queues with different priorities. Assign queries to a queue based on priority.
Run the VACUUM command for all tables in the database.
You are Head of Words at AnalyzerComp. You are using S3 to store campaign response data. Each campaign's data was compiled from a consistent set of sources. The data is uploaded to S3 in the form of.csv files. You have to examine the data from each campaign using Athena. The organization requires a reduction in the cost of continuing data analysis using Athena. Which steps should you perform in combination to achieve these requirements? (CHOOSE TWO.)
Convert the .csv files to Apache Parquet.
Convert the .csv files to Apache Avro.
Compress the .csv files.
Partition the data by campaign.
Partition the data by sources.
