AWS Big Data Blog
Category: AWS CloudFormation
Automate your validated dataset deployment using Amazon QuickSight and AWS CloudFormation
A lot of the power behind business intelligence (BI) and data visualization tools such as Amazon QuickSight comes from the ability to work interactively with data through a GUI. Report authors create dashboards using GUI-based tools, then in just a few clicks can share the dashboards with business users and decision-makers. This workflow empowers authors […]
Read MoreAutomate Amazon Redshift Cluster management operations using AWS CloudFormation
Amazon Redshift is the fastest and most widely used cloud data warehouse. Tens of thousands of customers run business-critical workloads on Amazon Redshift. Amazon Redshift offers many features that enable you to build scalable, highly performant, cost-effective, and easy-to-manage workloads. For example, you can scale an Amazon Redshift cluster up or down based on your […]
Read MoreIncrease Amazon Elasticsearch Service performance by upgrading to Graviton2
September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Amazon OpenSearch Service supports multiple instance types based on your use case. In 2021, AWS announced general purpose (M6g), compute optimized (C6g), and memory optimized (R6g, R6gd) instance types for Amazon OpenSearch Service version 7.9 or later powered by AWS […]
Read MoreData monetization and customer experience optimization using telco data assets: Part 2
Part 1 of this series explains the importance of building and implementing a customer experience (CX) management and data monetization strategy for telecom service providers (TSPs), and the major challenges driving these initiatives. It also includes an AWS CloudFormation template to set up a demonstration of the solution using AWS services. It covers transforming and enriching […]
Read MoreAccelerating Amazon Redshift federated query to Amazon Aurora MySQL with AWS CloudFormation
Amazon Redshift federated query allows you to combine data from one or more Amazon Relational Database Service (Amazon RDS) for MySQL and Amazon Aurora MySQL databases with data already in Amazon Redshift. You can also combine such data with data in an Amazon Simple Storage Service (Amazon S3) data lake. This post shows you how […]
Read MoreA public data lake for analysis of COVID-19 data
As the COVID-19 pandemic continues to threaten and take lives around the world, we must work together across organizations and scientific disciplines to fight this disease. Innumerable healthcare workers, medical researchers, scientists, and public health officials are already on the front lines caring for patients, searching for therapies, educating the public, and helping to set […]
Read MoreAutomate Amazon Redshift cluster creation using AWS CloudFormation
In this post, I explain how to automate the deployment of an Amazon Redshift cluster in an AWS account. AWS best practices for security and high availability drive the cluster’s configuration, and you can create it quickly by using AWS CloudFormation. I walk you through a set of sample CloudFormation templates, which you can customize as per your needs.
Read MoreBuild and automate a serverless data lake using an AWS Glue trigger for the Data Catalog and ETL jobs
Today, data is flowing from everywhere, whether it is unstructured data from resources like IoT sensors, application logs, and clickstreams, or structured data from transaction applications, relational databases, and spreadsheets. Data has become a crucial part of every business. This has resulted in a need to maintain a single source of truth and automate the […]
Read MoreImplement continuous integration and delivery of serverless AWS Glue ETL applications using AWS Developer Tools
In this post, I walk you through a solution that implements a CI/CD pipeline for serverless AWS Glue ETL applications supported by AWS Developer Tools (including AWS CodePipeline, AWS CodeCommit, and AWS CodeBuild) and AWS CloudFormation.
Read MoreCreate data science environments on AWS for health analysis using OHDSI
This blog post demonstrates how to combine some of the OHDSI projects (Atlas, Achilles, WebAPI, and the OMOP Common Data Model) with AWS technologies. By doing so, you can quickly and inexpensively implement a health data science and informatics environment.
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