Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. It use the PrestoDB as the SQL engine under the hood.
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project2026-03-03
The article details Yggdrasil Gaming's migration from Google BigQuery to an AWS-based lakehouse architecture, highlighting the challenges faced due to multi-cloud operational complexity and the need for a scalable analytics foundation. It outlines the phased approach taken to establish a new architecture using AWS services, including Amazon S3, Apache Iceberg, and Amazon Athena, which enabled real-time data ingestion and advanced analytics capabilities. The migration resulted in significant cost savings, improved data freshness, and enhanced governance for analytics workloads. The article serves as a case study for organizations looking to modernize their data architecture.
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project2026-01-30
The article outlines Halodoc's comprehensive approach to data validation within a Lakehouse architecture, emphasizing the importance of data accuracy and reliability. It describes a multi-layered validation strategy that employs AI to enhance data quality checks at various stages of the data pipeline. The validation layers include checks for data consistency, structural correctness, business correctness, and reconciliation, ensuring that data remains trustworthy throughout its journey. The implementation of this strategy has led to reduced data incidents and increased trust among analytics and product teams.
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project2025-07-22
This Data Processing MCP Server can fully manage all the EMR, Athena and Glue services. You really don't need code any more...
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project2024-12-05
Twitch has leveraged Views in their Data Lake to enhance data agility, minimize downtime, and streamline development workflows. By utilizing Views as interfaces to underlying data tables, they've enabled seamless schema modifications, such as column renames and VARCHAR resizing, without necessitating data reprocessing. This approach has facilitated rapid responses to data quality issues and supported efficient ETL processes, contributing to a scalable and adaptable data infrastructure.
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product2024-12-12
Build a process to built the complete data lineage information by merging the partial lineage generated by dbt automatically.
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project2022-06-22
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project2024-10-29
With AWS LakeFormation, creating filter packages and controlling access. A filter package provides a restricted view of a data asset by defining column and row filters on the tables.
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product2024-11-22
I think the challenges part still is the adaption of this kind of system, integration and change the workflow is a huge cost for the stakeholder team.
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