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Amazon Web Services AWS Certified Data Analytics DAS-C01 New Questions

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Total 207 questions

AWS Certified Data Analytics - Specialty Questions and Answers

Question 33

A company wants to use automatic machine learning (ML) to create and visualize forecasts of complex scenarios and trends.

Which solution will meet these requirements with the LEAST management overhead?

Options:

A.

Use an AWS Glue ML job to transform the data and create forecasts. Use Amazon QuickSight to visualize the data.

B.

Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts.

C.

Use a prebuilt ML AMI from the AWS Marketplace to create forecasts. Use Amazon QuickSight to visualize the data.

D.

Use Amazon SageMaker inference pipelines to create and update forecasts. Use Amazon QuickSight to visualize the combined data.

Question 34

An analytics software as a service (SaaS) provider wants to offer its customers business intelligence

The provider wants to give customers two user role options

• Read-only users for individuals who only need to view dashboards

• Power users for individuals who are allowed to create and share new dashboards with other users

Which QuickSight feature allows the provider to meet these requirements'?

Options:

A.

Embedded dashboards

B.

Table calculations

C.

Isolated namespaces

D.

SPICE

Question 35

An IoT company wants to release a new device that will collect data to track sleep overnight on an intelligent mattress. Sensors will send data that will be uploaded to an Amazon S3 bucket. About 2 MB of data is generated each night for each bed. Data must be processed and summarized for each user, and the results need to be available as soon as possible. Part of the process consists of time windowing and other functions. Based on tests with a Python script, every run will require about 1 GB of memory and will complete within a couple of minutes.

Which solution will run the script in the MOST cost-effective way?

Options:

A.

AWS Lambda with a Python script

B.

AWS Glue with a Scala job

C.

Amazon EMR with an Apache Spark script

D.

AWS Glue with a PySpark job

Question 36

A company wants to use a data lake that is hosted on Amazon S3 to provide analytics services for historical data. The data lake consists of 800 tables but is expected to grow to thousands of tables. More than 50 departments use the tables, and each department has hundreds of users. Different departments need access to specific tables and columns.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Create an 1AM role for each department. Use AWS Lake Formation based access control to grant each 1AM role access to specific tables and columns. Use Amazon Athena to analyze the data.

B.

Create an Amazon Redshift cluster for each department. Use AWS Glue to ingest into the Redshift cluster only the tables and columns that are relevant to that department. Create Redshift database users. Grant the users access to the relevant department's Redshift cluster. Use Amazon Redshift to analyze the data.

C.

Create an 1AM role for each department. Use AWS Lake Formation tag-based access control to grant each 1AM role

access to only the relevant resources. Create LF-tags that are attached to tables and columns. Use Amazon Athena to analyze the data.

D.

Create an Amazon EMR cluster for each department. Configure an 1AM service role for each EMR cluster to access

E.

relevant S3 files. For each department's users, create an 1AM role that provides access to the relevant EMR cluster. Use Amazon EMR to analyze the data.

Page: 9 / 15
Total 207 questions