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Load data incrementally from transactional data lakes to data warehouses

AWS Big Data

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

Data Lake 137
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United Airlines sets its flight plan for gen AI success

CIO Business Intelligence

With the core architectural backbone of the airlines gen AI roadmap in place, including United Data Hub and an AI and ML platform dubbed Mars, Birnbaum has released a handful of models into production use for employees and customers alike.

IT 131
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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

It has far-reaching implications as to how such applications should be developed and by whom: ML applications are directly exposed to the constantly changing real world through data, whereas traditional software operates in a simplified, static, abstract world which is directly constructed by the developer. This approach is not novel.

IT 364
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Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt

AWS Big Data

Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. Here, data modeling uses dbt on Amazon Redshift.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

cycle_end"', "sagemakedatalakeenvironment_sub_db", ctas_approach=False) A similar approach is used to connect to shared data from Amazon Redshift, which is also shared using Amazon DataZone. AWS Database Migration Service (AWS DMS) is used to securely transfer the relevant data to a central Amazon Redshift cluster.

IoT 111
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Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes

AWS Big Data

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. You can use either the AWS Glue Data Catalog (recommended) or a Hive catalog for Iceberg tables.

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Regeneron turns to IT to accelerate drug discovery

CIO Business Intelligence

The company’s multicloud infrastructure has since expanded to include Microsoft Azure for business applications and Google Cloud Platform to provide its scientists with a greater array of options for experimentation. Much of Regeneron’s data, of course, is confidential. That’s hard to do when you have 30 years of data.”

Data Lake 124