Category: HAQM Redshift

This post focuses on active security for HAQM Redshift, in particular DataSunrise’s capabilities for masking and access control of personally identifiable information (PII), which you can back with DataSunrise’s passive security offerings such as auditing access of sensitive information. This post discusses DataSunrise security for HAQM Redshift, how it works, and how to get started.

In this post, I explain how to automate the deployment of an HAQM Redshift cluster in an AWS account. AWS best practices for security and high availability drive the cluster’s configuration, and you can create it quickly by using AWS CloudFormation. I walk you through a set of sample CloudFormation templates, which you can customize as per your needs.

In this article, we explain how this customer performed a large-scale data warehouse migration from IBM Netezza to HAQM Redshift without downtime, by following a thoroughly planned migration process, and leveraging AWS Schema Conversion Tool (SCT) and HAQM Redshift best practices.

HAQM always works backwards from the customer’s needs. Customers have made strong requests that they want stored procedures in HAQM Redshift, to make it easier to migrate their existing workloads from legacy, on-premises data warehouses.

With that primary goal in mind, AWS chose to implement PL/pqSQL stored procedure to maximize compatibility with existing procedures and simplify migrations. In this post, we discuss how and where to use stored procedures to improve operational efficiency and security. We also explain how to use stored procedures with AWS Schema Conversion Tool.

After reviewing many solutions, 3M HIS chose HAQM Redshift as the appropriate data warehouse solution. We concluded HAQM Redshift met our needs; a fast, fully managed, petabyte-scale data warehouse solution that uses columnar storage to minimize I/O, provides high data compression rates, and offers fast performance. We quickly spun up a cluster in our development environment, built out the dimensional model, loaded data, and made it available to perform benchmarking and testing of the user data. An extract, transform, load (ETL) tool was used to process and load the data from various sources into HAQM Redshift.

Data warehousing is a critical component for analyzing and extracting actionable insights from your data. HAQM Redshift is a fast, scalable data warehouse that makes it cost-effective to analyze all of your data across your data warehouse and data lake. The HAQM Redshift console recently launched the Query Editor. The Query Editor is an in-browser […]

This post shows a step-by-step walkthrough of how to set up a cross-account HAQM Redshift COPY and Spectrum query using a sample dataset in HAQM 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 […]

The HAQM 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, […]

HAQM 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. […]

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 HAQM Redshift data warehouse located in Region B.