Remove Cost-Benefit Remove Data Lake Remove Machine Learning
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

The following requirements were essential to decide for adopting a modern data mesh architecture: Domain-oriented ownership and data-as-a-product : EUROGATE aims to: Enable scalable and straightforward data sharing across organizational boundaries. Eliminate centralized bottlenecks and complex data pipelines.

IoT 101
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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

Initially, data warehouses were the go-to solution for structured data and analytical workloads but were limited by proprietary storage formats and their inability to handle unstructured data. Eventually, transactional data lakes emerged to add transactional consistency and performance of a data warehouse to the data lake.

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Data Lakes on Cloud & it’s Usage in Healthcare

BizAcuity

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Deploying Data Lakes in the cloud. Best practices to build a Data Lake.

Data Lake 102
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Unleash deeper insights with Amazon Redshift data sharing for data lake tables

AWS Big Data

Over the years, this customer-centric approach has led to the introduction of groundbreaking features such as zero-ETL , data sharing , streaming ingestion , data lake integration , Amazon Redshift ML , Amazon Q generative SQL , and transactional data lake capabilities.

Data Lake 102
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How Cloudinary transformed their petabyte scale streaming data lake with Apache Iceberg and AWS Analytics

AWS Big Data

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used.

Data Lake 122
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Accelerate analytics and AI innovation with the next generation of Amazon SageMaker

AWS Big Data

At AWS re:Invent 2024, we announced the next generation of Amazon SageMaker , the center for all your data, analytics, and AI. In this post, we explore the benefits of SageMaker Unified Studio and how to get started. We are excited to announce the general availability of SageMaker Unified Studio.

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Accelerate Amazon Redshift Data Lake queries with AWS Glue Data Catalog Column Statistics

AWS Big Data

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 105