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Build and manage your modern data stack using dbt and AWS Glue through dbt-glue, the new “trusted” dbt adapter

AWS Big Data

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

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

AWS Big Data

This data is then used by various applications for streaming analytics, business intelligence, and reporting. Amazon SageMaker is used to build, train, and deploy a range of ML models. This ensures that the data is suitable for training purposes. Additionally, SageMaker training jobs are employed for training the models.

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End-to-end development lifecycle for data engineers to build a data integration pipeline using AWS Glue

AWS Big Data

In this post, we assume the following three accounts: Pipeline account – This hosts the end-to-end pipeline Dev account – This hosts the integration pipeline in the development environment Prod account – This hosts the data integration pipeline in the production environment If you want, you can use the same account and the same Region for all three.

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Applying Fine Grained Security to Apache Spark

Cloudera

The challenges of arbitrary code execution notwithstanding, there have been attempts to provide a stronger security model but with mixed results. The introduction of “Secure Access” mode to HWC avoids these drawbacks by relying on Hive to obtain a secure snapshot of the data that is then operated upon by Spark. df.show().

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How SafetyCulture scales unpredictable dbt Cloud workloads in a cost-effective manner with Amazon Redshift

AWS Big Data

A source of unpredictable workloads is dbt Cloud , which SafetyCulture uses to manage data transformations in the form of models. Whenever models are created or modified, a dbt Cloud CI job is triggered to test the models by materializing the models in Amazon Redshift.

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Cloudera Data Engineering 2021 Year End Review

Cloudera

Cloudera’s Shared Data Experience (SDX) provides all these capabilities allowing seamless data sharing across all the Data Services including CDE. We are excited to offer in Tech Preview this born-in-the-cloud table format that will help future proof data architectures at many of our public cloud customers.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Big data enables automated systems by intelligently routing many data sets and data streams. In a recent move towards a more autonomous logistical future, Amazon has launched an upgraded model of its highly-successful KIVA robots. Use our 14-days free trial today & transform your supply chain!

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