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Orchestrate an end-to-end ETL pipeline using Amazon S3, AWS Glue, and Amazon Redshift Serverless with Amazon MWAA

AWS Big Data

Additionally, it enables cost optimization by aligning resources with specific use cases, making sure that expenses are well controlled. By isolating workloads with specific security requirements or compliance needs, organizations can maintain the highest levels of data privacy and security.

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Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift

AWS Big Data

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. You can perform real-time transaction processing on data in Aurora while simultaneously using Amazon Redshift for analytics workloads such as reporting and dashboards. or higher).

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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Use ML to unlock new data types—e.g., Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. You also need solutions that let you understand what data you have and who can access it. images, audio, video. Source: O'Reilly.

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Simplify AWS Glue job orchestration and monitoring with Amazon MWAA

AWS Big Data

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

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Simplify external object access in Amazon Redshift using automatic mounting of the AWS Glue Data Catalog

AWS Big Data

To connect as a federated user with the Redshift provisioned cluster, you need to follow the steps in the previous section that detailed how to connect with Redshift Serverless and query the Data Catalog as a federated user using Query Editor V2 and a third-party SQL client. There are additional changes required in IAM policy.

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Design a data mesh on AWS that reflects the envisioned organization

AWS Big Data

Discussions with users showed they were happier to have faster access to data in a simpler way, a more structured data organization, and a clear mapping of who the producer is. A lot of progress has been made to advance their data-driven culture (data literacy, data sharing, and collaboration across business units).

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Data Science, Past & Future

Domino Data Lab

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.