AWS-Certified-Data-Analytics-Specialty Free Practice Test

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?

1. A. Create a read replica of the RDS database to store the most recent 6 months of dat
2. B. Copy the historical data into Amazon S3. Create an AWS Glue Data Catalog of the data in Amazon S3 and Amazon RD
3. C. Run historical queries using Amazon Athena.
4. D. Use an ETL tool to incrementally load the most recent 6 months of data into an Amazon Redshift cluste
5. E. Run more frequent queries against this cluste
6. F. Create a read replica of the RDS database to run queries on the historical data.
7. G. 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.
8. H. Incrementally copy data from Amazon RDS to Amazon S3. Load and store the most recent 6 months of data in Amazon Redshif
9. I. Configure an Amazon Redshift Spectrum table to connect to all historical data.

Correct Answer: D

An airline has .csv-formatted data stored in Amazon S3 with an AWS Glue Data Catalog. Data analysts want to join this data with call center data stored in Amazon Redshift as part of a dally batch process. The Amazon Redshift cluster is already under a heavy load. The solution must be managed, serverless, well-functioning, and minimize the load on the existing Amazon Redshift cluster. The solution should also require minimal effort and development activity.
Which solution meets these requirements?

1. A. Unload the call center data from Amazon Redshift to Amazon S3 using an AWS Lambda function.Perform the join with AWS Glue ETL scripts.
2. B. Export the call center data from Amazon Redshift using a Python shell in AWS Glu
3. C. Perform the join with AWS Glue ETL scripts.
4. D. Create an external table using Amazon Redshift Spectrum for the call center data and perform the join with Amazon Redshift.
5. E. Export the call center data from Amazon Redshift to Amazon EMR using Apache Sqoo
6. F. Perform the join with Apache Hive.

Correct Answer: C
https://docs.aws.amazon.com/redshift/latest/dg/c-spectrum-external-tables.html

A retail company’s data analytics team recently created multiple product sales analysis dashboards for the average selling price per product using Amazon QuickSight. The dashboards were created from .csv files uploaded to Amazon S3. The team is now planning to share the dashboards with the respective external product owners by creating individual users in Amazon QuickSight. For compliance and governance reasons, restricting access is a key requirement. The product owners should view only their respective product analysis in the dashboard reports.
Which approach should the data analytics team take to allow product owners to view only their products in the dashboard?

1. A. Separate the data by product and use S3 bucket policies for authorization.
2. B. Separate the data by product and use IAM policies for authorization.
3. C. Create a manifest file with row-level security.
4. D. Create dataset rules with row-level security.

Correct Answer: D
https://docs.aws.amazon.com/quicksight/latest/user/restrict-access-to-a-data-set-using-row-level-security.html

A company’s marketing team has asked for help in identifying a high performing long-term storage service for their data based on the following requirements:
The data size is approximately 32 TB uncompressed.
There is a low volume of single-row inserts each day.
There is a high volume of aggregation queries each day.
Multiple complex joins are performed.
The queries typically involve a small subset of the columns in a table.
Which storage service will provide the MOST performant solution?

1. A. Amazon Aurora MySQL
2. B. Amazon Redshift
3. C. Amazon Neptune
4. D. Amazon Elasticsearch

Correct Answer: B

An online gaming company is using an Amazon Kinesis Data Analytics SQL application with a Kinesis data stream as its source. The source sends three non-null fields to the application: player_id, score, and us_5_digit_zip_code.
A data analyst has a .csv mapping file that maps a small number of us_5_digit_zip_code values to a territory code. The data analyst needs to include the territory code, if one exists, as an additional output of the Kinesis Data Analytics application.
How should the data analyst meet this requirement while minimizing costs?

1. A. Store the contents of the mapping file in an Amazon DynamoDB tabl
2. B. Preprocess the records as they arrive in the Kinesis Data Analytics application with an AWS Lambda function that fetches the mapping and supplements each record to include the territory code, if one exist
3. C. Change the SQL query in the application to include the new field in the SELECT statement.
4. D. Store the mapping file in an Amazon S3 bucket and configure the reference data column headers for the.csv file in the Kinesis Data Analytics applicatio
5. E. Change the SQL query in the application to include a join to the file’s S3 Amazon Resource Name (ARN), and add the territory code field to the SELECT columns.
6. F. Store the mapping file in an Amazon S3 bucket and configure it as a reference data source for the Kinesis Data Analytics applicatio
7. G. Change the SQL query in the application to include a join to the reference table and add the territory code field to the SELECT columns.
8. H. Store the contents of the mapping file in an Amazon DynamoDB tabl
9. I. Change the Kinesis Data Analytics application to send its output to an AWS Lambda function that fetches the mapping and supplements each record to include the territory code, if one exist
10. J. Forward the record from the Lambda function to the original application destination.

Correct Answer: C