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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

Add this policy to the AWS Glue role and Amazon MWAA role: { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "s3:GetObject", "s3:PutObject", "s3:PutObjectAcl" ], "Resource": "arn:aws:s3:::sample-inp-bucket-etl- /*" } ] } In Account B, create the IAM policy policy_for_roleB specifying Account A as a trusted entity.

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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

In the first part of this post, we walk through the integration between AWS Glue Data Quality and Amazon DataZone. We discuss how to visualize data quality scores in Amazon DataZone, enable AWS Glue Data Quality when creating a new Amazon DataZone data source, and enable data quality for an existing data asset.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. Athena is used to run geospatial queries on the location data stored in the S3 buckets. The ingestion approach is not in scope of this post. Choose Run.

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Process and analyze highly nested and large XML files using AWS Glue and Amazon Athena

AWS Big Data

In this post, we show how to process XML data using AWS Glue and Athena. This approach provides a user-friendly interface and is particularly suitable for individuals who prefer a graphical approach to managing their data. We use the AWS Glue crawler to extract XML file metadata. Choose Create.

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Build efficient ETL pipelines with AWS Step Functions distributed map and redrive feature

AWS Big Data

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of extract, transform, and load (ETL) technologies such as AWS Glue , Amazon EMR , and Amazon Redshift. There are multiple tables related to customers and order data in the RDS database.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

He’s been out of Wolfram for a while and writing exquisite science books including Elements: A Visual Explanation of Every Known Atom in the Universe and Molecules: The Architecture of Everything. The gist is, leveraging metadata about research datasets, projects, publications, etc., Data governance, for the win!

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Themes and Conferences per Pacoid, Episode 10

Domino Data Lab

She had much to say to leaders of data science teams, coming from perspectives of data engineering at scale. And by “scale” I’m referring to what is arguably the largest, most successful data analytics operation in the cloud of any public firm that isn’t a cloud provider. Rev 2 wrap up.