AWS Big Data Blog

Category: Amazon Redshift

Automating DBA tasks on Amazon Redshift securely using AWS IAM, AWS Lambda, Amazon EventBridge, and stored procedures

As a data warehouse administrator or data engineer, you may need to perform maintenance tasks and activities or perform some level of custom monitoring on a regular basis. You can combine these activities inside a stored procedure or invoke views to get details. Some of these activities include things like loading nightly staging tables, invoking […]

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Analyzing healthcare FHIR data with Amazon Redshift PartiQL

Healthcare organizations across the globe strive to provide the best possible patient care at the lowest cost. In a patient’s care journey, multiple organizations are often involved, including the healthcare provider, diagnostic labs, pharmacies, and health insurance payors. Each of these organizations needs to exchange health data efficiently with the others to ensure care continuity […]

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Building high-quality benchmark tests for Redshift using open-source tools: Best practices

Amazon Redshift is the most popular and fastest cloud data warehouse, offering seamless integration with your data lake, up to three times faster performance than any other cloud data warehouse, and up to 75% lower cost than any other cloud data warehouse. When you use Amazon Redshift to scale compute and storage independently, a need […]

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Enabling multi-factor authentication for an Amazon Redshift cluster using Okta as an identity provider

Many organizations have started using single sign-on (SSO) with multi-factor authentication (MFA) for enhanced security. This additional authentication factor is the new normal, which enhances the security provided by the user name and password model. Using SSO reduces the effort needed to maintain and remember multiple login credentials. In the past, you needed to manage […]

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How Cookpad scaled its Amazon Redshift cluster while controlling costs with usage limits

This is a guest post by Shimpei Kodama, data engineer at Cookpad Inc. Cookpad is a tech company that builds a community platform where people share recipe ideas and cooking tips. The company’s mission is to “make everyday cooking fun.” It’s one of the largest recipe-sharing platforms in Japan with over 50 million users per […]

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How to delete user data in an AWS data lake

General Data Protection Regulation (GDPR) is an important aspect of today’s technology world, and processing data in compliance with GDPR is a necessity for those who implement solutions within the AWS public cloud. One article of GDPR is the “right to erasure” or “right to be forgotten” which may require you to implement a solution […]

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Zoopla drives KPIs with centralized data using Fivetran ELT for Amazon Redshift

This is a guest post by Steven Collings, Senior Data Consultant at Zoopla Zoopla is a property website that enables users to find residential or commercial property to buy or rent in the UK and overseas. Since acquiring Property Software Group and Expert Agent, we also offer a backend software that agents can use to […]

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Fast and predictable performance with serverless compilation using Amazon Redshift

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Customers tell us that they want extremely fast query response times so they can make equally fast decisions. This post presents the recently launched, […]

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How Aruba Networks built a cost analysis solution using AWS Glue, Amazon Redshift, and Amazon QuickSight

This is a guest post co-written by Siddharth Thacker and Swatishree Sahu from Aruba Networks. Aruba Networks is a Silicon Valley company based in Santa Clara that was founded in 2002 by Keerti Melkote and Pankaj Manglik. Aruba is the industry leader in wired, wireless, and network security solutions. Hewlett-Packard acquired Aruba in 2015, making […]

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Top 10 performance tuning techniques for Amazon Redshift

Customers use Amazon Redshift for everything from accelerating existing database environments, to ingesting weblogs for big data analytics. Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that offers simple operations and high performance. Amazon Redshift provides an open standard JDBC/ODBC driver interface, which allows you to connect your existing business intelligence (BI) tools and reuse existing analytics queries. Amazon Redshift can run any type of data model, from a production transaction system third-normal-form model to star and snowflake schemas, data vault, or simple flat tables. This post takes you through the most common performance-related opportunities when adopting Amazon Redshift and gives you concrete guidance on how to optimize each one. 

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