AWS Big Data Blog

Category: Amazon Simple Storage Service (S3)

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

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. 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, […]

Use AWS Glue ETL to perform merge, partition evolution, and schema evolution on Apache Iceberg

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. However, altering schema and table partitions in traditional data lakes can be a disruptive and time-consuming task, requiring renaming or recreating entire tables and reprocessing large datasets. […]

Backup and Restore - Pre

Disaster recovery strategies for Amazon MWAA – Part 1

In the dynamic world of cloud computing, ensuring the resilience and availability of critical applications is paramount. Disaster recovery (DR) is the process by which an organization anticipates and addresses technology-related disasters. For organizations implementing critical workload orchestration using Amazon Managed Workflows for Apache Airflow (Amazon MWAA), it is crucial to have a DR plan […]

How HR&A uses Amazon Redshift spatial analytics on Amazon Redshift Serverless to measure digital equity in states across the US

In our increasingly digital world, affordable access to high-speed broadband is a necessity to fully participate in our society, yet there are still millions of American households without internet access. HR&A Advisors—a multi-disciplinary consultancy with extensive work in the broadband and digital equity space is helping its state, county, and municipal clients deliver affordable internet […]

Prepare and load Amazon S3 data into Teradata using AWS Glue through its native connector for Teradata Vantage

In this post, we explore how to use the AWS Glue native connector for Teradata Vantage to streamline data integrations and unlock the full potential of your data. Businesses often rely on Amazon Simple Storage Service (Amazon S3) for storing large amounts of data from various data sources in a cost-effective and secure manner. For […]

Use Amazon EMR with S3 Access Grants to scale Spark access to Amazon S3

Amazon EMR is pleased to announce integration with Amazon Simple Storage Service (Amazon S3) Access Grants that simplifies Amazon S3 permission management and allows you to enforce granular access at scale. With this integration, you can scale job-based Amazon S3 access for Apache Spark jobs across all Amazon EMR deployment options and enforce granular Amazon […]

Unstructured Data Management - AWS Native Architecture

Unstructured data management and governance using AWS AI/ML and analytics services

In this post, we discuss how AWS can help you successfully address the challenges of extracting insights from unstructured data. We discuss various design patterns and architectures for extracting and cataloging valuable insights from unstructured data using AWS. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.

How healthcare organizations can analyze and create insights using price transparency data

In recent years, there has been a growing emphasis on price transparency in the healthcare industry. Under the Transparency in Coverage (TCR) rule, hospitals and payors to publish their pricing data in a machine-readable format. With this move, patients can compare prices between different hospitals and make informed healthcare decisions. For more information, refer to […]

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

In today’s digital age, data is at the heart of every organization’s success. One of the most commonly used formats for exchanging data is XML. Analyzing XML files is crucial for several reasons. Firstly, XML files are used in many industries, including finance, healthcare, and government. Analyzing XML files can help organizations gain insights into […]

Operational Data Processing Framework for Modern Data Architectures

Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS has invested in native service integration with Apache Hudi and published technical contents to enable you to use Apache Hudi with AWS Glue (for example, refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 1: Getting Started). In AWS ProServe-led customer engagements, the use cases we work on usually come with technical complexity and scalability requirements. In this post, we discuss a common use case in relation to operational data processing and the solution we built using Apache Hudi and AWS Glue.