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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. Open AWS Glue Studio. Choose ETL Jobs.

Data Lake 105
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Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight

AWS Big Data

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. Apache Hudi connector for AWS Glue For this post, we use AWS Glue 4.0,

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

AWS Big Data

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 116
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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

Grafana provides powerful customizable dashboards to view pipeline health. QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. Sample AWS CDK template This post provides a sample AWS CDK template for a dashboard using AWS Glue observability metrics.

Metrics 108
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Implement alerts in Amazon OpenSearch Service with PagerDuty

AWS Big Data

You can use this proactive alerting to monitor data patterns for existing data, monitor clusters, detect patterns, and more. OpenSearch Dashboard provides an alerting plugin that you can use to set up various types of monitors and alerts. For Host , enter events.PagerDuty.com. On the Channels tab, choose Create channel.

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Access Amazon Athena in your applications using the WebSocket API

AWS Big Data

Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.

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Automate deployment of an Amazon QuickSight analysis connecting to an Amazon Redshift data warehouse with an AWS CloudFormation template

AWS Big Data

In QuickSight, you analyze and visualize your data in analyses. When you’re finished, you can publish your analysis as a dashboard to share with others in your organization. Create an Amazon Redshift data source in AWS CloudFormation In this step, we add the AWS::QuickSight::DataSource section of the CloudFormation template.