Tag: Amazon Redshift Spectrum

New: Read Amazon Redshift continues its price-performance leadership to learn what analytic workload trends we’re seeing from Amazon Redshift customers, new capabilities we have launched to improve Redshift’s price-performance, and the results from the latest benchmarks. Part 1 of this multi-post series, ETL and ELT design patterns for modern data architecture using Amazon Redshift: Part 1, […]

New: Read Amazon Redshift continues its price-performance leadership to learn what analytic workload trends we’re seeing from Amazon Redshift customers, new capabilities we have launched to improve Redshift’s price-performance, and the results from the latest benchmarks. Part 1 of this multi-post series discusses design best practices for building scalable ETL (extract, transform, load) and ELT (extract, […]

This post shows a step-by-step walkthrough of how to set up a cross-account Amazon Redshift COPY and Spectrum query using a sample dataset in Amazon S3. The sample dataset is encrypted at rest using AWS KMS-managed keys (SSE-KMS). About AWS Key Management Service (AWS KMS) With AWS Key Management Service (AWS KMS), you can have […]

Clickstream analysis tools handle their data well, and some even have impressive BI interfaces. However, analyzing clickstream data in isolation comes with many limitations. For example, a customer is interested in a product or service on your website. They go to your physical store to purchase it. The clickstream analyst asks, “What happened after they […]

We have been busy adding new features and capabilities to Amazon Redshift, and we wanted to give you a glimpse of what we’ve been doing over the past year. In this article, we recap a few of our enhancements and provide a set of resources that you can use to learn more and get the most out of your Amazon Redshift implementation.

Over the years, I have developed and created a number of data warehouses from scratch. Recently, I built a data warehouse for the iGaming industry single-handedly. To do it, I used the power and flexibility of Amazon Redshift and the wider AWS data management ecosystem. In this post, I explain how I was able to build a robust and scalable data warehouse without the large team of experts typically needed.

This is a guest post by Rafi Ton, founder and CEO of NUVIAD. The ability to provide fresh, up-to-the-minute data to our customers and partners was always a main goal with our platform. We saw other solutions provide data that was a few hours old, but this was not good enough for us. We insisted on providing the freshest data possible. For us, that meant loading Amazon Redshift in frequent micro batches and allowing our customers to query Amazon Redshift directly to get results in near real time. The benefits were immediately evident. Our customers could see how their campaigns performed faster than with other solutions, and react sooner to the ever-changing media supply pricing and availability. They were very happy.

We’re excited to announce today an update to our Amazon Redshift connector with support for Amazon Redshift Spectrum to analyze data in external Amazon S3 tables. With this update, you can quickly and directly connect Tableau to data in Amazon Redshift and analyze it in conjunction with data in Amazon S3—all with drag-and-drop ease.

Achieving a 360o-view of your customer has become increasingly challenging as companies embrace omni-channel strategies, engaging customers across websites, mobile, call centers, social media, physical sites, and beyond. The promise of a web where online and physical worlds blend makes understanding your customers more challenging, but also more important. Businesses that are successful in this […]

When we first looked into the possibility of building a cloud-based data warehouse many years ago, we were struck by the fact that our customers were storing ever-increasing amounts of data, and yet only a small fraction of that data ever made it into a data warehouse or Hadoop system for analysis. We saw that […]