There’s no question this year’s re:Invent was a massive event. With 32,000 attendees, 400+ breakout sessions, hands-on labs and tutorials, it can get overwhelming at times. Our interest in cloud databases and data engineering led us to curate and share our favorite sessions on Redshift – Amazon’s fast, peta-scale data warehouse – of which there were 20 alone!
1. Best Practices for Data Warehousing with Amazon Redshift
This is a fantastic session covering the major topics on Amazon Redshift, including its columnar storage, designing optimal schemas, loading data and work load management. Highly recommended!
2. Leveraging Amazon Machine Learning, Amazon Redshift, and an Amazon Simple Storage Service Data Lake for Strategic Advantage in Real Estate
This session is about creating an enterprise data lake on Amazon S3 by The Howard Hughes Corporation and 47Lining. Their business analytics built a lead-scoring model using Amazon Machine Learning (Amazon ML) to predict propensity to purchase high-end real estate. Some pretty impressive numbers – 400% increase in the number of identified qualified leads in their pipeline and more than 10x reduction is lead acquisition cost.