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

AWS Big Data

Amazon Q data integration , introduced in January 2024, allows you to use natural language to author extract, transform, load (ETL) jobs and operations in AWS Glue specific data abstraction DynamicFrame. In this post, we discuss how Amazon Q data integration transforms ETL workflow development.

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Oracle Wants to Be the Database for AI

David Menninger's Analyst Perspectives

The software provider also claims to be working on other types of assistants, such as creating data integration and transformation pipelines, test data and generating schemas. Rounding out the portfolio of data platform offerings is the announced but not-yet-available Intelligent Data Lake.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. They are the same.

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Recap of Amazon Redshift key product announcements in 2024

AWS Big Data

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

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Accelerate data integration with Salesforce and AWS using AWS Glue

AWS Big Data

Effective data analytics relies on seamlessly integrating data from disparate systems through identifying, gathering, cleansing, and combining relevant data into a unified format. This solution also allows you to update certain fields of the account object in the data lake and push it back to Salesforce.

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How Cloudinary transformed their petabyte scale streaming data lake with Apache Iceberg and AWS Analytics

AWS Big Data

Many of the tests to check performance and volumes of data scanned have used Athena because it provides a simple to use, fully serverless, cost effective, interface without the need to setup infrastructure. Iceberg provides several maintenance operations to keep your tables in good shape.

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Fire Your Super-Smart Data Consultants with DataOps

DataKitchen

DataOps improves the robustness, transparency and efficiency of data workflows through automation. For example, DataOps can be used to automate data integration. Previously, the consulting team had been using a patchwork of ETL to consolidate data from disparate sources into a data lake.