AWS Analytics Services

Data Warehouse

A data warehouse is a data storage solution that aggregates massive amounts of historic data from disparate sources.

Benefits:

Data warehouses support querying, reporting, analytics. And business intelligence. They are not used for transaction processing.

Amazon Redshift

Redshift is a scalable data warehouse solution.

Features:

1. Data warehousing solution.
2. Handles exabyte-scale data.
3. Improves speed and efficiency.

Athena

Athena is a query service for Amazon S3.

Features:

1. Query service
2. Analyze S3 data using SQL.
3. Pay per query.
4. Considered serverless.

Glue

Glue prepares your data for analytics.

Features:

1. Prepare and load data.
2. Helps to better understand your data.
3. Extract, transform load (ETL) service.

Kinesis

Kinesis allows you to analyze data and video streams in real-time.

Features:

1. Analyze real-time streaming data.
2. Supports video, audio, application logs, website clickstreams, and IoT.

Elastic MapReduce (EMR)

EMR helps you process large amounts of data.

Features:

1. Process Big Data
2. Analyze data using Hadoop
3. Works with big data frameworks.

Data Pipeline

Data Pipeline helps you to move data between computing and storage services running either on AWS or on-premises,

Features:

1. Moves data at specific intervals.
2. Moves data based on conditions.
3. Sends notification on success or failure.

QuickSight

QuickSight helps you to visualize your data.

Features:

1. Build interactive dashboards.
2. Embed dashboards in your applications.

Important for the exam:

1. Going into the exam, don’t forget Athena is used to querying S3.
2. Going to the exam, don’t forget the real-world use cases of Redshift.