Remove Data Architecture Remove Experimentation Remove Metadata
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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.

IoT 111
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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 post explains how to create a design that automatically backs up Amazon Simple Storage Service (Amazon S3), the AWS Glue Data Catalog, and Lake Formation permissions in different Regions and provides backup and restore options for disaster recovery. The Data Catalog organizes this information in the form of metadata tables and databases.

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How Swisscom automated Amazon Redshift as part of their One Data Platform solution using AWS CDK – Part 1

AWS Big Data

One Data Platform The ODP architecture is based on the AWS Well Architected Framework Analytics Lens and follows the pattern of having raw, standardized, conformed, and enriched layers as described in Modern data architecture. See the following admin user code: admin_secret_kms_key_options = KmsKeyOptions(.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Metadata tables offer insights into the physical data storage layout of the tables and offer the convenience of querying them with Athena version 3.

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Four starting points to transform your organization into a data-driven enterprise

IBM Big Data Hub

IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. Data science and MLOps.

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Build end-to-end Apache Spark pipelines with Amazon MWAA, Batch Processing Gateway, and Amazon EMR on EKS clusters

AWS Big Data

The Clinical Insights Data Science team runs critical end-of-day batch processes that need guaranteed resources, whereas the Digital Analytics team can use cost-optimized spot instances for their variable workloads. Additionally, data scientists from both teams require environments for experimentation and prototyping as needed.