AWS Big Data Blog

Category: Amazon Redshift

Benchmark the performance of the new Auto WLM with adaptive concurrency in Amazon Redshift

With Amazon Redshift, you can run a complex mix of workloads on your data warehouse clusters. For example, frequent data loads run alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads. Each workload type has different resource needs and different service level agreements. […]

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How GE Healthcare modernized their data platform using a Lake House Architecture

GE Healthcare (GEHC) operates as a subsidiary of General Electric. The company is headquartered in the US and serves customers in over 160 countries. As a leading global medical technology, diagnostics, and digital solutions innovator, GE Healthcare enables clinicians to make faster, more informed decisions through intelligent devices, data analytics, applications, and services, supported by […]

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Access Amazon Location Service from Amazon Redshift

Organizations typically store business and customer data in databases like Amazon Relational Database Service (Amazon RDS) and Amazon Redshift, and often want to enrich this data by integrating with external services. One such enrichment is to add spatial attributes such as location coordinates for an address. With the introduction of Amazon Location Service, you now […]

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Synchronize and control your Amazon Redshift clusters maintenance windows

Amazon Redshift is a data warehouse that can expand to exabyte-scale. Today, tens of thousands of AWS customers (including NTT DOCOMO, Finra, and Johnson & Johnson) use Amazon Redshift to run mission-critical business intelligence dashboards, analyze real-time streaming data, and run predictive analytics jobs. Amazon Redshift powers analytical workloads for Fortune 500 companies, startups, and […]

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Accelerate your data warehouse migration to Amazon Redshift – Part 2

This is the second post in a multi-part series. We’re excited to shared dozens of new features to automate your schema conversion; preserve your investment in existing scripts, reports, and applications; accelerate query performance; and potentially reduce your overall cost to migrate to Amazon Redshift. Check out the first post Accelerate your data warehouse migration […]

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How Jobcase is using Amazon Redshift ML to recommend job search content at scale

This post is co-written with Clay Martin and Ajay Joshi from Jobcase as the lead authors. Jobcase is an online community dedicated to empowering and advocating for the world’s workers. We’re the third-largest destination for job search in the United States, and connect millions of Jobcasers to relevant job opportunities, companies, and other resources on […]

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Case-insensitive collation support for string processing in Amazon Redshift

Amazon Redshift is a fast, fully managed, cloud-native data warehouse. Tens of thousands of customers have successfully migrated their workloads to Amazon Redshift. We hear from customers that they need case-insensitive collation for strings in Amazon Redshift in order to maintain the same functionality and meet their performance goals when they migrate their existing workloads […]

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Data preparation using Amazon Redshift with AWS Glue DataBrew

With AWS Glue DataBrew, data analysts and data scientists can easily access and visually explore any amount of data across their organization directly from their Amazon Simple Storage Service (Amazon S3) data lake, Amazon Redshift data warehouse, Amazon Aurora, and other Amazon Relational Database Service (Amazon RDS) databases. You can choose from over 250 built-in functions to merge, pivot, and transpose […]

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Work with semistructured data using Amazon Redshift SUPER

With the new SUPER data type and the PartiQL language, Amazon Redshift expands data warehouse capabilities to natively ingest, store, transform, and analyze semi-structured data. Semi-structured data (such as weblogs and sensor data) fall under the category of data that doesn’t conform to a rigid schema expected in relational databases. It often contain complex values […]

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Amazon Redshift identity federation with multi-factor authentication

Password-based access control alone is not considered secure enough, and many organizations are adopting multi-factor authentication (MFA) and single sign-on (SSO) as a de facto standard to prevent unauthorized access to systems and data. SSO frees up time and resources for both administrators and end users from the painful process of password-based credential management. MFA […]

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