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Amazon Redshift powers data-driven decisions for tens of thousands of customers every day, across all industries, from identifying fraud patterns across billions of transactions or health trends across patients, to improving customer recommendations with targeted content.
Analyze massive amounts of data in near real-time to drive critical business insights faster with best-in-class security, governance, and compliance. Handle complex queries and data warehouses workloads cost effectively to detect fraud and analyze risk, optimize portfolios, value assets, and improve customer experiences.
Empower healthcare decisions with rapid analysis of large volumes of patient, genomic, and operational data to uncover disease patterns, optimize clinical trials, improve patient experience and protect health data while meeting the most stringent security and compliance regulations in the industry.
Get key insights to provide enhanced customer experience while driving advertising revenue. With fast query performance across petabytes of data, analyze audience engagement metrics, understand content consumption patterns, improve content recommendations, and develop targeted production strategies.
Build a modern data architecture with scalable data lakes and data warehouses, purpose-built to get the best performance, scale, and cost advantages, with unified data access, security, and governance and built-in AI and ML.
Amazon Redshift’s zero-ETL integrations with AWS databases such as Amazon Aurora, Amazon RDS, Amazon DynamoDB and integrations with AWS streaming data services enable near real-time analytics on petabytes of transactional data. Data is ingested continuously into data warehouses using a no code/low code approach.
Innovate faster with a serverless architecture and built-in generative AI/ML
Get started in a few seconds with Amazon Redshift Serverless to analyze your data. With Amazon Q generative SQL in Amazon Redshift Query Editor, you can simplify query authoring to increase your productivity. Create, train, and apply machine learning models using familiar SQL commands with Amazon Redshift ML.