AWS Data Analytics & Machine Learning 1 — Questions and Answers
Question 1: Which AWS service is commonly used for big data processing?
- Amazon EMR (Correct answer)
- AWS Lambda
- AWS Glue
- Amazon S3
Correct answer: Amazon EMR
Amazon Elastic MapReduce (EMR) is a managed cluster platform that simplifies running big data frameworks like Apache Hadoop and Apache Spark on AWS. It allows you to process vast amounts of data quickly and cost-effectively. EMR is ideal for big data analytics, machine learning, and data transformations, scaling resources up or down as needed.
Question 2: What is the purpose of AWS Glue in data analytics?
- Perform ETL operations (Correct answer)
- Manage cloud security
- Optimize machine learning models
- Deploy containerized applications
Correct answer: Perform ETL operations
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy to prepare and combine data for analytics and machine learning. It automatically discovers and catalogs metadata, generates Python or Scala code for ETL jobs, and runs them on a serverless Apache Spark environment. Glue simplifies the process of moving data between data stores and transforming it into a usable format.
Question 3: Which AWS service enables real-time data streaming?
- Amazon Kinesis (Correct answer)
- Amazon Athena
- Amazon S3
- AWS Step Functions
Correct answer: Amazon Kinesis
Amazon Kinesis is a platform for streaming data on AWS, enabling you to process and analyze large streams of data in real time. It can ingest data from various sources, such as website clickstreams, IoT device data, and application logs. Kinesis allows for immediate processing, enabling real-time analytics, dashboards, and alerts.
Question 4: Which AWS service is designed for building and deploying machine learning models?
- Amazon SageMaker (Correct answer)
- AWS Lambda
- AWS Glue
- AWS Step Functions
Correct answer: Amazon SageMaker
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. It offers a comprehensive suite of tools, including notebooks, training jobs, and hosting endpoints, to streamline the entire ML workflow. SageMaker simplifies the process of bringing ML models into production.
Question 5: What is the function of Amazon Redshift?
- Perform large-scale data warehousing (Correct answer)
- Encrypt stored data
- Monitor network security
- Automate application deployments
Correct answer: Perform large-scale data warehousing
Amazon Redshift is a fully managed, petabyte-scale cloud data warehouse service. It is optimized for analytical workloads and can handle complex queries on large datasets, making it suitable for business intelligence and reporting. Redshift provides fast query performance by using columnar storage, data compression, and massively parallel processing (MPP).
Question 6: Which AWS service enables serverless data querying?
- Amazon Athena (Correct answer)
- AWS IAM
- AWS CloudFront
- Amazon RDS
Correct answer: Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data directly in Amazon S3 using standard SQL. It is serverless, so there is no infrastructure to manage, and you pay only for the queries you run. Athena is ideal for ad-hoc analysis and quick data exploration without needing to load data into a separate database.
AWS Data Analytics & Machine Learning 1
Which AWS service is commonly used for big data processing?