AWS (Amazon Web Services) provides a comprehensive suite of services for data analytics, catering to various data processing, storage, and analysis needs. These services are designed to help businesses extract valuable insights from their data, improve decision-making, and enable data-driven strategies. Here are some of the key AWS data analytics services:

1. Amazon S3 (Simple Storage Service): Amazon S3 is a scalable object storage service, commonly used to store and retrieve vast amounts of data, including raw data and data processed for analysis.

2. Amazon Redshift: Amazon Redshift is a fully managed data warehouse service, designed for high-performance analysis of large datasets. It allows you to run complex queries on your data and provides integrations with various data visualization tools.

3. Amazon Athena: Amazon Athena is an interactive query service that enables you to analyze data stored in Amazon S3 using standard SQL queries without the need for any infrastructure management.

4. Amazon EMR (Elastic MapReduce): Amazon EMR is a cloud-based big data platform that allows you to process vast amounts of data using popular frameworks such as Apache Hadoop, Apache Spark, and more.

5. AWS Glue: AWS Glue is a fully managed extract, transform, and load (ETL) service that helps prepare and transform data for analytics purposes. It automatically generates ETL code and can work with various data sources.

6. Amazon QuickSight: Amazon QuickSight is a business intelligence service that enables users to build interactive dashboards and perform ad-hoc data analysis. It integrates with various data sources, including AWS services and on-premises databases.

7. Amazon Kinesis: Amazon Kinesis provides real-time data streaming capabilities, allowing you to collect and process data from a wide variety of sources, such as website clickstreams, IoT devices, and log data.

8. AWS Data Pipeline: AWS Data Pipeline is a web service for orchestrating and automating the movement and transformation of data between different AWS services and on-premises data sources.

9. AWS Data Lake Formation: AWS Data Lake Formation simplifies the process of setting up a data lake, making it easy to ingest, catalog, and clean data from various sources.

10. AWS Lake Formation: AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. It helps automate the process of collecting, cataloging, and cleaning data for analytics and machine learning.

11. AWS DataSync: AWS DataSync is a service that simplifies, automates, and accelerates data transfer between on-premises storage systems and Amazon S3 or Amazon Elastic File System (Amazon EFS).

These services can be used individually or combined to build end-to-end data analytics solutions, catering to various business needs and data processing requirements.