Remove 2012 Remove Metadata Remove Visualization
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Manage Amazon OpenSearch Service Visualizations, Alerts, and More with GitHub and Jenkins

AWS Big Data

OpenSearch Service stores different types of stored objects, such as dashboards, visualizations, alerts, security roles, index templates, and more, within the domain. As your user base and number of Amazon OpenSearch Service domains grow, tracking activities and changes to those saved objects becomes increasingly difficult.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

Iceberg tables maintain metadata to abstract large collections of files, providing data management features including time travel, rollback, data compaction, and full schema evolution, reducing management overhead. You can use this same integration to take advantage of the data sharing and collaboration capabilities in Snowflake.

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Ingest and analyze your data using Amazon OpenSearch Service with Amazon OpenSearch Ingestion

AWS Big Data

A common use case that we see amongst customers is to search and visualize data. In this post, we show how to ingest CSV files from Amazon Simple Storage Service (Amazon S3) into Amazon OpenSearch Service using the Amazon OpenSearch Ingestion feature and visualize the ingested data using OpenSearch Dashboards.

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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.

Metadata 108
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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

With OpenSearch Ingestion, you can filter, enrich, transform, and deliver your data for downstream analysis and visualization. You can now analyze infrequently queried data in cloud object stores and simultaneously use the operational analytics and visualization capabilities of OpenSearch Service.

Data Lake 118
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Process and analyze highly nested and large XML files using AWS Glue and Amazon Athena

AWS Big Data

Solution overview We explore two distinct techniques that can streamline your XML file processing workflow: Technique 1: Use an AWS Glue crawler and the AWS Glue visual editor – You can use the AWS Glue user interface in conjunction with a crawler to define the table structure for your XML files. Choose Create.

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

AWS Big Data

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. If the asset has AWS Glue Data Quality enabled, you can now quickly visualize the data quality score directly in the catalog search pane.