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Build a secure data visualization application using the Amazon Redshift Data API with AWS IAM Identity Center

AWS Big Data

In todays data-driven world, securely accessing, visualizing, and analyzing data is essential for making informed business decisions. For instance, a global sports gear company selling products across multiple regions needs to visualize its sales data, which includes country-level details. Choose Create workgroup.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Need for a data mesh architecture Because entities in the EUROGATE group generate vast amounts of data from various sourcesacross departments, locations, and technologiesthe traditional centralized data architecture struggles to keep up with the demands for real-time insights, agility, and scalability.

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Visualize data quality scores and metrics generated by AWS Glue Data Quality

AWS Big Data

In this post, we highlight the seamless integration of Amazon Athena and Amazon QuickSight , which enables the visualization of operational metrics for AWS Glue Data Quality rule evaluation in an efficient and effective manner. The following architecture diagram shows an overview of the complete pipeline.

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DataOps For Business Analytics Teams

DataKitchen

Data scientists derive insights from data while business analysts work closely with and tend to the data needs of business units. Business analysts sometimes perform data science, but usually, they integrate and visualize data and create reports and dashboards from data supplied by other groups.

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Exploring new ETL and ELT capabilities for Amazon Redshift from the AWS Glue Studio visual editor

AWS Big Data

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. Today, we are pleased to announce a new and enhanced visual job authoring capabilities for Amazon Redshift ETL and ELT workflows on the AWS Glue Studio visual editor.

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Why the Data Journey Manifesto?

DataKitchen

We put them into production but then hope all the steps that data goes through from source to customer value work out correctly. We all know that our customers frequently find data and dashboard problems. The Customer Journey visually represents the total sum of experiences any given customer has with a brand.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

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