Amazon DAS-C01 AWS Certified Data Analytics - Specialty Exam Exam Practice Test Questions

• Question 1

  A marketing company collects clickstream data The company sends the data to Amazon Kinesis Data Firehose and stores the data in Amazon S3 The company wants to build a series of dashboards that will be used by hundreds of users across different departments The company will use Amazon QuickSight to develop these dashboards The company has limited resources and wants a solution that could scale and provide daily updates about clickstream activityWhich combination of options will provide the MOST cost-effective solution? (Select TWO )

  • Use Amazon Redshift to store and query the clickstream data
  • Use QuickSight with a direct SQL query
  • Use Amazon Athena to query the clickstream data in Amazon S3
  • Use S3 analytics to query the clickstream data
  • Use the QuickSight SPICE engine with a daily refresh

  Show Answer Answer: B, ,D Next

• Question 2

  A company has several Amazon EC2 instances sitting behind an Application Load Balancer (ALB) The company wants its IT Infrastructure team to analyze the IP addresses coming into the company's ALB The ALB is configured to store access logs in Amazon S3 The access logs create about 1 TB of data each day, and access to the data will be infrequent The company needs a solution that is scalable, cost-effective and has minimal maintenance requirementsWhich solution meets these requirements?

  • Copy the data into Amazon Redshift and query the data
  • Use Amazon EMR and Apache Hive to query the S3 data
  • Use Amazon Athena to query the S3 data
  • Use Amazon Redshift Spectrum to query the S3 data

  Show Answer Answer: D Next

• Question 3

  A company wants to ingest clickstream data from its website into an Amazon S3 bucket. The streaming data is in JSON format. The data in the S3 bucket must be partitioned by product_id. Which solution will meet these requirements MOST cost-effectively?

  • Create an Amazon Kinesis Data Firehose delivery stream to ingest the streaming data into the S3 bucket. Enable dynamic partitioning. Specify the data field of productjd as one partitioning key.
  • Create an AWS Glue streaming job to partition the data by productjd before delivering the data to the S3 bucket. Create an Amazon Kinesis Data Firehose delivery stream. Specify the AWS Glue job as the destination of the delivery stream.
  • Create an Amazon Kinesis Data Firehose delivery stream to ingest the streaming data into the S3 bucket. Create an AWS Glue ETL job to read the data stream in the S3 bucket, partition the data by productjd, and write the data into another S3 bucket.
  • Create an Amazon Kinesis Data Firehose delivery stream to ingest the streaming data into the S3 bucket. Create an Amazon EMR cluster that includes a job to read the data stream in the S3 bucket, partition the data by productjd, and write the data into another S3 bucket.

  Show Answer Answer: A Next

• Question 4

  A large ecommerce company uses Amazon DynamoDB with provisioned read capacity and auto scaled write capacity to store its product catalog. The company uses Apache HiveQL statements on an Amazon EMR cluster to query the DynamoDB table. After the company announced a sale on all of its products, wait times for each query have increased. The data analyst has determined that the longer wait times are being caused by throttling when querying the table.Which solution will solve this issue?

  • Increase the size of the EMR nodes that are provisioned.
  • Increase the number of EMR nodes that are in the cluster.
  • Increase the DynamoDB table's provisioned write throughput.
  • Increase the DynamoDB table's provisioned read throughput.

  Show Answer Answer: D Next

• Question 5

  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?

  • Store the contents of the mapping file in an Amazon DynamoDB table. 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 exists. Change the SQL query in the application to include the new field in the SELECT statement.
  • 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 application. 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.
  • Store the mapping file in an Amazon S3 bucket and configure it as a reference data source for the Kinesis Data Analytics application. 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.
  • Store the contents of the mapping file in an Amazon DynamoDB table. 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 exists. Forward the record from the Lambda function to the original application destination.

  Show Answer Answer: C Next