Category: AWS Big Data

This is a guest post by Arvind Godbole, Lead Software Engineer with FactSet and Tarik Makota, AWS Principal Solutions Architect. In their own words “FactSet creates flexible, open data and software solutions for tens of thousands of investment professionals around the world, which provides instant access to financial data and analytics that investors use to […]

The annual AWS re:Invent learning conference is an exciting time full of new product and program launches. At the first re:Invent conference in 2012, AWS announced Amazon Redshift. Since then, tens of thousands of customers have started using Amazon Redshift as their cloud data warehouse. In 2019, AWS shared several significant launches and dozens of […]

This is a guest post by Verizon Media Group. At Verizon Media Group (VMG), one of the major problems we faced was the inability to scale out computing capacity in a required amount of time—hardware acquisitions often took months to complete. Scaling and upgrading hardware to accommodate workload changes was not economically viable, and upgrading […]

Redshift Spectrum is a feature of Amazon Redshift that allows you to query data stored on Amazon S3 directly and supports nested data types. This post discusses which use cases can benefit from nested data types, how to use Amazon Redshift Spectrum with nested data types to achieve excellent performance and storage efficiency, and some […]

Real-time delivery of data and insights enables businesses to pivot quickly in response to changes in demand, user engagement, and infrastructure events, among many others. Amazon Kinesis offers a managed service that lets you focus on building your applications, rather than managing infrastructure. Scalability is provided out-of-the-box, allowing you to ingest and process gigabytes of […]

Part 1 of this multi-post series, ETL and ELT design patterns for lake house architecture using Amazon Redshift: Part 1, discussed common customer use cases and design best practices for building ELT and ETL data processing pipelines for data lake architecture using Amazon Redshift Spectrum, Concurrency Scaling, and recent support for data lake export. This […]

Part 1 of this multi-post series discusses design best practices for building scalable ETL (extract, transform, load) and ELT (extract, load, transform) data processing pipelines using both primary and short-lived Amazon Redshift clusters. You also learn about related use cases for some key Amazon Redshift features such as Amazon Redshift Spectrum, Concurrency Scaling, and recent […]

Patient matching is a major obstacle in achieving healthcare interoperability. Mismatched patient records and inability to retrieve patient history can cause significant barriers to informed clinical decision-making and result in missed diagnoses or delayed treatments. Additionally, healthcare providers often invest in patient data deduplication, especially when the number of patient records is growing rapidly in […]

AWS offers the broadest set of analytic tools and engines that analyzes data using open formats and open standards. To validate expertise with AWS data analytics solutions, builders can now take the beta for the AWS Certified Data Analytics — Specialty certification. The AWS Certified Data Analytics — Specialty certification validates technical expertise with designing, […]

Amazon Athena is an interactive query service that makes it easy to analyze the data stored in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. You can reduce your per-query costs and get better performance by compressing, partitioning, […]