Modernize your data warehouse by moving to Amazon Redshift (ANT345)

Overview of the Presentation

The presentation covered the following key points:

1. Importance of Data and Generative AI:

   • Data is at the heart of every business process and drives critical decisions.
   • Data has become a critical building block for generative AI, and customers are using it to power their data models.
   • Harnessing the power of data remains a challenge due to siloed, complex, and sprawling data systems.

2. AWS Analytics and Amazon Redshift:

   • AWS Analytics provides an end-to-end data strategy, allowing customers to ingest, process, analyze, and generate insights using purpose-built data stores or analytics tools.
   • Amazon Redshift is AWS's most price-performant SQL engine, working as a data warehouse for tens of thousands of customers.
   • Key innovations in Amazon Redshift include multi-warehouse architecture with data sharing, zero-ETL and auto-copy features, and integration with generative AI tools like Amazon Bedrock.

3. Customer Use Cases:

   • Hilton used a data sharing architecture and multi-warehouse approach to consolidate data from multiple properties, optimize operations, and serve 22,000 active users.
   • EchoStar employed a multi-warehouse architecture with Redshift Serverless to ingest 10TB of data daily and reduce ingestion latency from 2-3 days to 37 seconds.
   • Zalando and ADP shared their journeys of modernizing their data warehouses using Amazon Redshift.

4. Zalando's Journey:

   • Zalando is the leading multi-brand fashion destination in Europe, with 50+ million active customers and 14+ billion in GMV.
   • Zalando has a large data mesh platform with 5,000+ data products owned by 350+ teams.
   • The "fast-serving layer" is a key component for providing fast SQL access to their main data sets, but the current monolithic cluster was not scalable.
   • Zalando migrated to a multi-instance Amazon Redshift architecture, with separate producer and consumer clusters connected via data shares, which resulted in 76% of queries running faster.

5. ADP's Journey:

   • ADP is a global leader in human capital management solutions, serving over 1 million clients across 140 countries.
   • ADP's "Data Cloud" analytics application offers insights to over 50,000 customers, but faced challenges with scalability and performance.
   • ADP migrated their data warehouse and application to Amazon Redshift, leveraging features like cluster configuration, query optimization, and multi-tenancy to achieve sub-second response times and meet their SLAs.
   • ADP also realized additional benefits, such as reduced database footprint, 30% cost savings, and easier environment setup.

Key Takeaways

1. Importance of Data and Generative AI: Data is a critical asset for businesses, and customers are leveraging it to power their generative AI models and drive digital transformation.

2. AWS Analytics and Amazon Redshift: AWS Analytics provides an end-to-end data platform, with Amazon Redshift as a powerful and innovative data warehouse solution.

3. Customer Success Stories: Hilton, EchoStar, Zalando, and ADP shared how they have modernized their data warehouses and analytics capabilities using Amazon Redshift, achieving significant improvements in performance, scalability, and cost savings.

4. Migration and Modernization Guidance: The presenters offered resources and assistance to help customers start their own data warehouse modernization and migration journeys with Amazon Redshift.

5. Key Innovations in Amazon Redshift: Features like multi-warehouse architecture, zero-ETL, data sharing, and integration with generative AI tools demonstrate the continuous innovation in Amazon Redshift.