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Amazon AWS Certified Machine Learning – Specialty: What is the Easiest AWS Solution for Data Preparation and Predictive Modeling Without Coding?

By: Author Alex Lim

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Discover the simplest AWS solution for business analysts to prepare data and predict future production volume, without requiring any coding knowledge. Learn how to leverage AWS services like Glue DataBrew and SageMaker Canvas.

Table of Contents

Question

A manufacturing company stores production volume data in a PostgreSQL database.

The company needs an end-to-end solution that will give business analysts the ability to prepare data for processing and to predict future production volume based the previous year’s production volume. The solution must not require the company to have coding knowledge.

Which solution will meet these requirements with the LEAST effort?

A. Use AWS Database Migration Service (AWS DMS) to transfer the data from the PostgreSQL database to an Amazon S3 bucket. Create an Amazon EMR duster to read the S3 bucket and perform the data preparation. Use Amazon SageMaker Studio for the prediction modeling.
B. Use AWS Glue DataBrew to read the data that is in the PostgreSQL database and to perform the data preparation. Use Amazon SageMaker Canvas for the prediction modeling.
C. Use AWS Database Migration Service (AWS DMS) to transfer the data from the PostgreSQL database to an Amazon S3 bucket. Use AWS Glue to read the data in the S3 bucket and to perform the data preparation. Use Amazon SageMaker Canvas for the prediction modeling.
D. Use AWS Glue DataBrew to read the data that is in the PostgreSQL database and to perform the data preparation. Use Amazon SageMaker Studio for the prediction modeling.

Answer

The solution that will meet the requirements with the least effort is:

B. Use AWS Glue DataBrew to read the data that is in the PostgreSQL database and to perform the data preparation. Use Amazon SageMaker Canvas for the prediction modeling.

Explanation

Here’s why this is the most efficient solution:

  1. AWS Glue DataBrew can directly read data from the PostgreSQL database, so there’s no need to migrate the data to Amazon S3 using AWS Database Migration Service (DMS). This eliminates an extra step and reduces complexity.
  2. AWS Glue DataBrew is a visual data preparation tool that allows users to clean and normalize data without writing code. This meets the requirement of not needing coding knowledge for data preparation.
  3. Amazon SageMaker Canvas is a no-code machine learning platform that enables business analysts to build, train, and deploy machine learning models using a visual point-and-click interface. This aligns with the requirement of not requiring coding knowledge for prediction modeling.

The other options involve additional steps or tools that require more effort and potentially coding knowledge:

  • Option A uses AWS DMS and Amazon EMR, which are more complex and require more setup and management.
  • Option C includes the unnecessary step of migrating data to S3 using AWS DMS.
  • Option D uses Amazon SageMaker Studio, which is a more advanced tool that typically requires coding knowledge, making it less suitable for business analysts without coding skills.

Therefore, option B provides the most straightforward and code-free solution to meet the company’s requirements with the least effort.

Amazon AWS Certified Machine Learning – Specialty certification exam assessment practice question and answer (Q&A) dump including multiple choice questions (MCQ) and objective type questions, with detail explanation and reference available free, helpful to pass the Amazon AWS Certified Machine Learning – Specialty exam and earn Amazon AWS Certified Machine Learning – Specialty certification.