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Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore federation

AWS Big Data

In this post, we delve into the key aspects of using Amazon EMR for modern data management, covering topics such as data governance, data mesh deployment, and streamlined data discovery. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

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Handle UPSERT data operations using open-source Delta Lake and AWS Glue

AWS Big Data

On the AWS Glue console, under Data Integration and ETL in the navigation pane, choose Jobs. load("s3://"+ args['s3_bucket']+"/fullload/") sdf.printSchema() # Write data as DELTA TABLE sdf.write.format("delta").mode("overwrite").save("s3://"+ Vivek Singh is Senior Solutions Architect with the AWS Data Lab team.

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Simplify AWS Glue job orchestration and monitoring with Amazon MWAA

AWS Big Data

In these scenarios, customers looking for a serverless data integration offering use AWS Glue as a core component for processing and cataloging data. Finally, we recommend visiting the AWS Big Data Blog for other material on analytics, ML, and data governance on AWS.

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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. Thus, many developers will need to curate data, train models, and analyze the results of models. A typical data pipeline for machine learning.