This video tutorial covers the AWS Certified Big Data Specialty exam's processing domain. It begins with AWS Lambda's role in connecting services for big data movement, followed by AWS Glue's ability to structure unstructured data in an S3 data lake. The tutorial then delves into Elastic MapReduce, a managed Hadoop cluster for processing large datasets, and explores various tools like Apache Spark and Hive. It also introduces AWS machine learning services, including SageMaker, and discusses the AWS Data Pipeline for creating processing workflows. The video concludes with hands-on activities, including building a product recommendation system and predicting order quantities.

What role does AWS Lambda play in the AWS Big Data ecosystem?

• It is used for data storage.

• It connects various services for data movement.

• It is a machine learning tool.

• It is a data visualization service.

How does AWS Glue assist in managing data?

• By providing data visualization tools.

• By structuring unstructured data in an S3 data lake.

• By offering machine learning capabilities.

• By storing data in a relational database.

What is the primary function of Elastic MapReduce (EMR) on AWS?

• To provide a managed Hadoop cluster for processing large datasets.

• To offer a data visualization platform.

• To store data in a NoSQL database.

• To manage network security.

Which of the following tools can be run on Elastic MapReduce?

• Amazon RDS

• AWS Lambda

• Apache Spark

• Amazon S3

What is the purpose of the AWS Data Pipeline?

• To visualize data in real-time.

• To provide machine learning models.

• To chain together larger processing workflows.

• To store data in a data lake.