1. You are working on an ETL (Extract, Transform, Load) job using AWS Glue, and you want to write the transformed data to an S3 bucket. Which of the following are valid ways to accomplish this? Choose the correct option.

A) Use the write_dynamic_frame method of a Glue DynamicFrame object to write data to Redshift.
B) Use the create_dataframe_from_options method of the Glue DataFrameReader object to read data from S3 and transform it before writing it back to S3.
C) Use the write method of a Glue DataFrame object to write data to S3.
D) Use the write_dynamic_frame method of a Glue DynamicFrame object to write data to S3.
E) Use the create_dynamic_frame_from_options method of the Glue DynamicFrameReader object to read data from S3 and transform it before writing it back to S3.


2. A company is looking to build a dashboard to visualize real-time insights for their e-commerce platform. They want to use Amazon QuickSight as the BI tool to visualize data from multiple sources, including Amazon Redshift, Amazon RDS, and Amazon S3. Which of the following options describes the best way to achieve this?

A) Use AWS Lambda functions to extract data from each data source, transform it, and load it into a common data store such as Amazon DynamoDB. Use Amazon QuickSight to visualize the data from DynamoDB and create the dashboard. Share the dashboard with the users.
B) Export the data from each data source to a common format such as CSV or Parquet, store the files in Amazon S3, and use QuickSight's data preparation capabilities to combine the data. Use Amazon QuickSight Enterprise edition to publish the dashboard to the users.
C) Use the built-in connectors in Amazon QuickSight to connect to the data sources and combine the data using QuickSight's data preparation capabilities. Publish the dashboard to a group of users in QuickSight.
D) Use AWS Glue to crawl and catalog the data sources, and then create a Glue ETL job to transform and load the data into a single data store such as Amazon Redshift or Amazon RDS. Connect QuickSight to the data store and create the dashboard. Share the dashboard with the users.



3. A company wants to detect faces of celebrities in their social media campaign images to better understand the effectiveness of their influencer marketing strategy. Which feature of Amazon Rekognition would be most useful for this task?

A) Text detection
B) Facial analysis
C) Celebrity recognition
D) Scene detection
E) Object detection


4. Which AWS service provides a fully managed, real-time streaming data ingestion and processing solution that can be used for machine learning applications that require low-latency data processing?(Select 2answers)

A) Amazon Kinesis Data Streams
B) AWS AppSync
C) AWS IoT Analytics
D) Amazon Kinesis Data Analytics
E) Amazon API Gateway


5. You need to deploy a machine learning model for batch inference on AWS. The input data for the model is stored in an Amazon S3 bucket, and the output needs to be stored in a different S3 bucket. Which of the following AWS services would be the best fit for this use case?

A) Amazon SageMaker Batch Transform
B) AWS Lambda
C) Amazon Elastic Container Service (ECS)
D) AWS Glue