AWS Big Data Blog

How FactSet automated exporting data from Amazon DynamoDB to Amazon S3 Parquet to build a data analytics platform

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 […]

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Amazon Redshift at re:Invent 2019

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 […]

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How Verizon Media Group migrated from on-premises Apache Hadoop and Spark to Amazon EMR

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 […]

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Maximize data ingestion and reporting performance on Amazon Redshift

This is a guest post from ZS. In their own words, “ZS is a professional services firm that works closely with companies to help develop and deliver products and solutions that drive customer value and company results. ZS engagements involve a blend of technology, consulting, analytics, and operations, and are targeted toward improving the commercial […]

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Amazon QuickSight: 2019 in review

2019 has been an exciting year for Amazon QuickSight. We onboarded thousands of customers, expanded our global presence to 10 AWS Regions, and launched over 60 features—more than a feature a week! We are inspired by you—our customers, and all that you do with Amazon QuickSight. We are thankful for the time you spend with […]

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Working with nested data types using Amazon Redshift Spectrum

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 […]

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Collect and distribute high-resolution crypto market data with ECS, S3, Athena, Lambda, and AWS Data Exchange

This is a guest post by Floating Point Group. In their own words, “Floating Point Group is on a mission to bring institutional-grade trading services to the world of cryptocurrency.” The need and demand for financial infrastructure designed specifically for trading digital assets may not be obvious. There’s a rather pervasive narrative that these coins […]

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Under the hood: Scaling your Kinesis data streams

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 […]

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ETL and ELT design patterns for lake house architecture using Amazon Redshift: Part 2

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 […]

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ETL and ELT design patterns for lake house architecture using Amazon Redshift: Part 1

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 […]

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