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DEA-C01 · Question #224

A company has several new datasets in CSV and JSON formats. A data engineer needs to make the data available to a team of data analysts who will analyze the data by using SQL queries. Which solution…

The correct answer is C. Store the data in an Amazon S3 bucket. Use an AWS Glue crawler to catalog the S3 bucket as. By storing the CSV and JSON files in Amazon S3 and running an AWS Glue crawler, you automatically catalog them as tables without upfront ETL. Amazon Athena then lets analysts run SQL queries directly against those tables on a pay-per- query basis. Using an Athena workgroup with…

Data Store Management

Question

A company has several new datasets in CSV and JSON formats. A data engineer needs to make the data available to a team of data analysts who will analyze the data by using SQL queries. Which solution will meet these requirements in the MOST cost-effective way?

Options

  • ACreate an Amazon RDS MySQL cluster. Use AWS Glue to transform and load the CSV and
  • BCreate an AWS Glue DataBrew project that contains the new data. Make the DataBrew project
  • CStore the data in an Amazon S3 bucket. Use an AWS Glue crawler to catalog the S3 bucket as
  • DLoad the data into Super-fast, Parallel, In-memory Calculation Engine (SPICE) in Amazon

How the community answered

(34 responses)
  • A
    3% (1)
  • B
    9% (3)
  • C
    82% (28)
  • D
    6% (2)

Explanation

By storing the CSV and JSON files in Amazon S3 and running an AWS Glue crawler, you automatically catalog them as tables without upfront ETL. Amazon Athena then lets analysts run SQL queries directly against those tables on a pay-per- query basis. Using an Athena workgroup with a usage threshold keeps costs under control, making this the most cost-effective, low-operational-overhead solution.

Topics

#Data Lake#AWS Glue Data Catalog#Amazon S3#Serverless SQL Analytics

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