How BMW Enhanced Data Accessibility Utilizing AWS Lake Formation’s Precision Access Control
In this article, we delve into how BMW successfully integrated AWS Lake Formation’s fine-grained access control (FGAC) within their Cloud Data Hub, leading to a remarkable 25% reduction in compute and storage expenses. By leveraging the FGAC features of AWS Lake Formation, BMW has efficiently implemented more precise data access management within their Cloud Data Hub. This integration allows data stewards to define and allocate specific access rights to various data subsets, significantly minimizing expensive data duplication.
For further insights, you might find this other blog post engaging as it explores related topics.
Analyzing Amazon EMR on EC2 Cluster Usage with Amazon Athena and Amazon QuickSight
by Jake Wilson, Mia Lee, Ethan Green, and Sophia Adams
on 25 OCT 2024
in Amazon Athena, Amazon EC2, Amazon EMR, Amazon QuickSight, Technical How-to
This post will guide you through establishing a robust solution in your Amazon Web Services (AWS) environment to evaluate Amazon EMR on your EC2 cluster usage. Implementing this solution will provide a comprehensive understanding of resource consumption and costs associated with individual applications running on your EMR cluster. Moreover, for those interested in deepening their knowledge, this resource offers excellent insights.
Maximizing Price-Performance in Amazon Redshift with Elastic Histograms for Selectivity Estimation
by Brian Carter, Zoe Parker, Liam Harris, and Ava Scott
on 25 OCT 2024
in Amazon Redshift, Analytics, Intermediate (200)
Amazon Redshift has introduced enhanced query performance optimizations such as Enhanced Histograms for Selectivity Estimation, which rely on metadata gathered during data ingestion in the absence of current statistics. This article discusses the new performance enhancements in Redshift’s data warehouse query processing and how elastic histogram statistics improve selectivity estimation, ultimately enhancing the quality of query plans for Amazon Redshift data warehouse queries.
Implementing Access Control and Auditing on Amazon Redshift with Immuta
by David Wilson, Nathan Young, Olivia Martin, and Grace King
on 24 OCT 2024
in Advanced (300), Amazon Redshift, Analytics, Security & Governance
This post, co-authored with Olivia Martin from Immuta, highlights how organizations seek solutions that allow them to focus more on essential business functions while reducing time spent managing data. With the integration of Immuta and Amazon Redshift, user and data security operations are effectively managed, streamlining the data oversight process.
Managing Amazon OpenSearch Service Visualizations, Alerts, and More with GitHub and Jenkins
by Rachel Brooks
on 24 OCT 2024
in Amazon OpenSearch Service, Analytics
OpenSearch Service encapsulates various stored objects, such as dashboards and alerts, within its domain. As the user base and number of Amazon OpenSearch Service domains expand, tracking changes and activities related to saved objects becomes more challenging. In this post, we present a strategy for deploying these stored objects using GitHub and Jenkins while preventing users from directly altering the OpenSearch Service domain.
Simplifying Query Performance Diagnostics in Amazon Redshift with Query Profiler
by Lucy Nguyen, Sean Rodriguez, and Emily Taylor
on 23 OCT 2024
in Advanced (300), Amazon Redshift, Analytics, AWS Big Data, Technical How-to
Amazon Redshift has launched a new feature known as the Query Profiler. This graphical tool assists users in analyzing the components and performance of a query. Integrated into the Amazon Redshift console, it provides a visual representation of query execution, plans, and various statistics. The Query Profiler simplifies the understanding and troubleshooting of queries. This post outlines two common use cases for diagnosing query performance, demonstrating step-by-step how to analyze and address long-running queries using the Query Profiler.
Enhancing Interaction with the Airflow REST API in Amazon MWAA
by Kevin Smith and Julia Martinez
on 23 OCT 2024
in Amazon Managed Workflows for Apache Airflow (Amazon MWAA), Announcements, Application Integration, Launch
We are thrilled to announce an enhancement to the Amazon MWAA integration with the Airflow REST API. This upgrade simplifies access to and management of your Airflow environments, enabling programmatic interaction with workflows. The Airflow REST API supports a variety of use cases, from automating administrative tasks to constructing event-driven, data-aware pipelines. This post discusses the enhancements and presents various use cases that these upgrades unlock for your Amazon MWAA environment.
How Getir Pioneered Data Democratization Using a Data Mesh Architecture with Amazon Redshift
by Mia Thompson and Leo Garcia
on 23 OCT 2024
in Amazon Redshift, Architecture, Customer Solutions
In this article, we illustrate how Getir, a leader in ultra-fast delivery, harnessed data democratization on a massive scale through a data mesh architecture utilizing Amazon Redshift. We begin by introducing Getir and their vision: to share business data seamlessly, securely, and efficiently across various teams within the organization for business intelligence and analytics.
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