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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. Refer to Amazon Kinesis Data Streams integrations for additional details.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. For more information, refer to Notions of Time: Event Time and Processing Time. For more information, refer to Dynamic Tables.

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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

By analyzing the historical report snapshot, you can identify areas for improvement, implement changes, and measure the effectiveness of those changes. For instructions, refer to Amazon DataZone quickstart with AWS Glue data. To learn more about Amazon DataZone, refer to the Amazon DataZone User Guide.

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Build a multi-Region and highly resilient modern data architecture using AWS Glue and AWS Lake Formation

AWS Big Data

This means that if data is moved from a bucket in the source Region to another bucket in the target Region, the data access permissions need to be reapplied in the target Region. AWS Glue Data Catalog The AWS Glue Data Catalog is a central repository of metadata about data stored in your data lake.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Many customers migrate their data warehousing workloads to Amazon Redshift and benefit from the rich capabilities it offers, such as the following: Amazon Redshift seamlessly integrates with broader data, analytics, and AI or machine learning (ML) services on AWS , enabling you to choose the right tool for the right job.

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Implement slowly changing dimensions in a data lake using AWS Glue and Delta

AWS Big Data

This post is designed to be implemented for a real customer use case, where you get full snapshot data on a daily basis. Over the years, he has helped multiple customers on data platform transformations across industry verticals. His core area of expertise include Technology Strategy, Data Analytics, and Data Science.

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Estimating Scope 1 Carbon Footprint with Amazon Athena

AWS Big Data

Using existing analytics tools such as Amazon Athena and Amazon QuickSight an organization can gain insight into its estimated carbon footprint. The data architecture diagram below shows an example of how you could use AWS services to calculate and visualize an organization’s estimated carbon footprint.