Analytics and Data Lake Use Cases
Simple and cost effective to run high performance queries on petabytes of semi-structured and structured data so that you can build powerful reports and dashboards.
Run SQL and complex, analytic queries against structured and unstructured data in your data warehouse and data lake, without the need for unnecessary data movement.
Scalable Data Lakes
Setting up and managing data lakes today usually involves a lot of manual and time-consuming tasks, but AWS automates these tasks so you can build and secure your data lake, in days instead of months.
Search, explore, filter, aggregate, and visualize your data in near real time for application monitoring, log analytics, and clickstream analytics.
Amazon Redshift Lake House Architecture
The amount of data generated by IoT, smart devices, cloud applications, and social is growing exponentially. You need ways to easily and cost-effectively analyze all of this data with minimal time-to-insight, regardless of the format or where the data is stored.
Amazon Redshift powers the lake house architecture – enabling you to query data across your data warehouse, data lake, and operational databases to gain faster and deeper insights not possible otherwise. With a lake house architecture, you can store data in open file formats in your Amazon S3 data lake. This allows you to make this data available easily to other analytics and machine learning tools rather than locking it in a new silo.
With an Amazon Redshift lake house architecture, you can:
- Easily query data in your data lake and write data back to your data lake in open formats.
- Use familiar SQL statements to combine and process data across all your data stores.
- Execute queries on live data in your operational databases without requiring any data loading and ETL pipelines.
Learn More About Additional AWS Analytics and Data Lake Products
Analytics and Data Lake product offers from the AWS Free Tier
Learn more about AWS Analytics and Data Lakes
Browse through our collection of videos and tutorials to deepen your knowledge and experience with AWS
The lake house approach to data warehousing with Amazon Redshift (24:40)
Introduction to Data Warehousing on AWS with Amazon Redshift (1:35)
An introduction to data lakes and analytics on AWS (32:28)
Amazon Redshift Data Lake Export (4:57)
Start with these free and simple tutorials to explore AWS analytics and data lake services
Deploy a Data Warehouse Using Amazon Redshift
In this project, you will create and configure an Amazon Redshift data warehouse, load sample data, and analyze it using a SQL client.
Migrate from Oracle to Amazon Redshift
In this tutorial, you will learn how to successfully migrate from Oracle to Amazon Redshift with minimal downtime.
Store and Retrieve a File with Amazon S3
This step-by-step tutorial will help you store your files in the cloud using Amazon Simple Storage Solution (S3). Amazon S3 is a service that enables you to store your data (referred to as objects) at massive scale. In this tutorial, you will create an Amazon S3 bucket, upload a file, retrieve the file and delete the file.
Create business intelligence dashboards with Amazon QuickSight
In this tutorial, you create data analyses, visualize the data, create stories and share the analyses through data dashboards in the cloud using Amazon QuickSight.