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

AWS Big Data

At AWS, we are committed to empowering organizations with tools that streamline data analytics and transformation processes. This integration enables data teams to efficiently transform and manage data using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience.

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SQL Streambuilder Data Transformations

Cloudera

SQL Stream Builder (SSB) is a versatile platform for data analytics using SQL as a part of Cloudera Streaming Analytics, built on top of Apache Flink. It enables users to easily write, run, and manage real-time continuous SQL queries on stream data and a smooth user experience. What is a data transformation?

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Amazon Q data integration adds DataFrame support and in-prompt context-aware job creation

AWS Big Data

Your generated jobs can use a variety of data transformations, including filters, projections, unions, joins, and aggregations, giving you the flexibility to handle complex data processing requirements. In this post, we discuss how Amazon Q data integration transforms ETL workflow development.

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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

Together with price-performance, Amazon Redshift offers capabilities such as serverless architecture, machine learning integration within your data warehouse and secure data sharing across the organization. dbt Cloud is a hosted service that helps data teams productionize dbt deployments. or a later version) database.

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Migrate from Amazon Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics Studio

AWS Big Data

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. This approach supports both the immediate needs of visualization tools such as Tableau and the long-term demands of digital twin and IoT data analytics.

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Accelerate your data workflows with Amazon Redshift Data API persistent sessions

AWS Big Data

In this post, we’ll walk through an example ETL process that uses session reuse to efficiently create, populate, and query temporary staging tables across the full data transformation workflow—all within the same persistent Amazon Redshift database session. Building event-driven applications with Amazon EventBridge and Lambda.