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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.

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Introducing Amazon Q data integration in AWS Glue

AWS Big Data

Today, we’re excited to announce general availability of Amazon Q data integration in AWS Glue. Amazon Q data integration, a new generative AI-powered capability of Amazon Q Developer , enables you to build data integration pipelines using natural language.

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Author data integration jobs with an interactive data preparation experience with AWS Glue visual ETL

AWS Big Data

The AWS Glue Studio visual editor is a graphical interface that enables you to create, run, and monitor data integration jobs in AWS Glue. The new data preparation interface in AWS Glue Studio provides an intuitive, spreadsheet-style view for interactively working with tabular data. Choose Create policy.

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Load data incrementally from transactional data lakes to data warehouses

AWS Big Data

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

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Building Best-in-Class Enterprise Analytics

Speaker: Anthony Roach, Director of Product Management at Tableau Software, and Jeremiah Morrow, Partner Solution Marketing Director at Dremio

Tableau works with Strategic Partners like Dremio to build data integrations that bring the two technologies together, creating a seamless and efficient customer experience. As a result of a strategic partnership, Tableau and Dremio have built a native integration that goes well beyond a traditional connector.

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Accelerate analytics and AI innovation with the next generation of Amazon SageMaker

AWS Big Data

Unified access to your data is provided by Amazon SageMaker Lakehouse , a unified, open, and secure data lakehouse built on Apache Iceberg open standards. To overcome these hurdles, many organizations are building bespoke integrations between services, tools, and homegrown access management systems.

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Synchronize data lakes with CDC-based UPSERT using open table format, AWS Glue, and Amazon MSK

AWS Big Data

In the current industry landscape, data lakes have become a cornerstone of modern data architecture, serving as repositories for vast amounts of structured and unstructured data. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

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