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Expanding data analysis and visualization options: Amazon DataZone now integrates with Tableau, Power BI, and more

AWS Big Data

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more.

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

AWS Big Data

These improvements are available through the Amazon Q chat experience on the AWS Management Console , and the Amazon SageMaker Unified Studio (preview) visual ETL and notebook interfaces. The DataFrame code generation now extends beyond AWS Glue DynamicFrame to support a broader range of data processing scenarios.

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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

With the ability to browse metadata, you can understand the structure and schema of the data source, identify relevant tables and fields, and discover useful data assets you may not be aware of. On your project, in the navigation pane, choose Data. For Add data source , choose Add connection. Choose the plus sign.

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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. The applications are hosted in dedicated AWS accounts and require a BI dashboard and reporting services based on Tableau. datazone_env_twinsimsilverdata"."cycle_end";')

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

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Use AWS Glue to streamline SFTP data processing

AWS Big Data

With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog. It enables you to visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes. Choose Store a new secret.

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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

These nodes can implement analytical platforms like data lake houses, data warehouses, or data marts, all united by producing data products. By treating the data as a product, the outcome is a reusable asset that outlives a project and meets the needs of the enterprise consumer.

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