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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. or a later version) database.

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From data lakes to insights: dbt adapter for Amazon Athena now supported in dbt Cloud

AWS Big Data

The need for streamlined data transformations As organizations increasingly adopt cloud-based data lakes and warehouses, the demand for efficient data transformation tools has grown. This enables you to extract insights from your data without the complexity of managing infrastructure.

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How AppsFlyer modernized their interactive workload by moving to Amazon Athena and saved 80% of costs

AWS Big Data

AppsFlyer develops a leading measurement solution focused on privacy, which enables marketers to gauge the effectiveness of their marketing activities and integrates them with the broader marketing world, managing a vast volume of 100 billion events every day.

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Accelerate your data workflows with Amazon Redshift Data API persistent sessions

AWS Big Data

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that you can use to analyze your data at scale. Building event-driven applications with Amazon EventBridge and Lambda. Scheduling SQL scripts to simplify data load, unload, and refresh of materialized views.

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Fauna’s Data Platform Combines Agility and Transaction Integrity

David Menninger's Analyst Perspectives

Traditionally, operational data platforms support applications used to run the business. Data is then extracted and loaded into analytic data platforms for analysis. The emergence of intelligent applications does not eradicate the use of specialist analytic data platforms, such as data warehouses and data lakehouses.

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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. For a table that will be converted, it invokes the converter Lambda function through an event.

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Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

These types of queries are suited for a data warehouse. The goal of a data warehouse is to enable businesses to analyze their data fast; this is important because it means they are able to gain valuable insights in a timely manner. Amazon Redshift is fully managed, scalable, cloud data warehouse.