AWS Big Data Blog

Category: Amazon Redshift

Build a modern analytics stack optimized for sharing and collaborating with Mode and Amazon Redshift

Leading technology companies, such as Netflix and Airbnb, are building on AWS to solve problems on the edge of the data ecosystem. While these companies show us what data and analytics make possible, the complexity and scale of their problems aren’t typical. Most of our challenges aren’t figuring out how to process billions of records […]

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How to enable cross-account Amazon Redshift COPY and Redshift Spectrum query for AWS KMS–encrypted data in Amazon S3

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 […]

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Bannerconnect uses Amazon Redshift to help clients improve digital marketing results

Bannerconnect uses programmatic marketing solutions that empower advertisers to win attention and customers by getting their ads seen by the right person at the right time and place. Data-driven insights help large advertisers, trade desks, and agencies boost brand awareness and maximize the results of their digital marketing. Timely analysis of log data is critical […]

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Run Amazon payments analytics with 750 TB of data on Amazon Redshift

The Amazon Payments Data Engineering team is responsible for data ingestion, transformation, and storage of a growing dataset of more than 750 TB. The team makes these services available to more than 300 business customers around the globe. These customers include managers from the product, marketing, and programs domains; as well as data scientists, business analysts, […]

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Scale your Amazon Redshift clusters up and down in minutes to get the performance you need, when you need it

Amazon Redshift is the cloud data warehouse of choice for organizations of all sizes—from fast-growing technology companies such as Turo and Yelp to Fortune 500 companies such as 21st Century Fox and Johnson & Johnson. With quickly expanding use cases, data sizes, and analyst populations, these customers have a critical need for scalable data warehouses. […]

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Create cross-account and cross-region AWS Glue connections

In this blog post, we describe how to configure the networking routes and interfaces to give AWS Glue access to a data store in an AWS Region different from the one with your AWS Glue resources. In our example, we connect AWS Glue, located in Region A, to an Amazon Redshift data warehouse located in Region B.

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Connect to and run ETL jobs across multiple VPCs using a dedicated AWS Glue VPC

In this blog post, we’ll go through the steps needed to build an ETL pipeline that consumes from one source in one VPC and outputs it to another source in a different VPC. We’ll set up in multiple VPCs to reproduce a situation where your database instances are in multiple VPCs for isolation related to security, audit, or other purposes.

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Chasing earthquakes: How to prepare an unstructured dataset for visualization via ETL processing with Amazon Redshift

As organizations expand analytics practices and hire data scientists and other specialized roles, big data pipelines are growing increasingly complex. Sophisticated models are being built using the troves of data being collected every second. The bottleneck today is often not the know-how of analytical techniques. Rather, it’s the difficulty of building and maintaining ETL (extract, transform, and load) jobs using tools that might be unsuitable for the cloud. In this post, I demonstrate a solution to this challenge.

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Close the customer journey loop with Amazon Redshift at Equinox Fitness Clubs

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 […]

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How Annalect built an event log data analytics solution using Amazon Redshift

By establishing a data warehouse strategy using Amazon S3 for storage and Redshift Spectrum for analytics, we increased the size of the datasets we support by over an order of magnitude. In addition, we improved our ability to ingest large volumes of data quickly, and maintained fast performance without increasing our costs. Our analysts and modelers can now perform deeper analytics to improve ad buying strategies and results.

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