AWS Big Data Blog
Category: Learning Levels
Near-real-time fraud detection using Amazon Redshift Streaming Ingestion with Amazon Kinesis Data Streams and Amazon Redshift ML
The importance of data warehouses and analytics performed on data warehouse platforms has been increasing steadily over the years, with many businesses coming to rely on these systems as mission-critical for both short-term operational decision-making and long-term strategic planning. Traditionally, data warehouses are refreshed in batch cycles, for example, monthly, weekly, or daily, so that […]
How Novo Nordisk built a modern data architecture on AWS
Novo Nordisk is a leading global pharmaceutical company, responsible for producing life-saving medicines that reach more than 34 million patients each day. They do this following their triple bottom line—that they must strive to be environmentally sustainable, socially sustainable, and financially sustainable. The combination of using AWS and data supports all these targets. Data is […]
Create your own reusable visual transforms for AWS Glue Studio
AWS Glue Studio has recently added the possibility of adding custom transforms that you can use to build visual jobs to use them in combination with the AWS Glue Studio components provided out of the box. You can now define custom visual transform by simply dropping a JSON file and a Python script onto Amazon […]
Impact of infrastructure failures on shards in Amazon OpenSearch Service
Amazon OpenSearch Service is a managed service that makes it easy to secure, deploy, and operate OpenSearch and legacy Elasticsearch clusters at scale in the AWS Cloud. Amazon OpenSearch Service provisions all the resources for your cluster, launches it, and automatically detects and replaces failed nodes, reducing the overhead of self-managed infrastructures. The service makes […]
Stream VPC flow logs to Amazon OpenSearch Service via Amazon Kinesis Data Firehose
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Amazon Virtual Private Cloud (Amazon VPC) flow logs enable you to track the IP traffic going to and from the network interfaces in your VPC for your workloads. Analyzing VPC logs helps […]
How to get best price performance from your Amazon Redshift Data Sharing deployment
Amazon Redshift is a fast, scalable, secure, and fully-managed data warehouse that enables you to analyze all of your data using standard SQL easily and cost-effectively. Amazon Redshift Data Sharing allows customers to securely share live, transactionally consistent data in one Amazon Redshift cluster with another Amazon Redshift cluster across accounts and regions without needing to […]
Monitor AWS workloads without a single line of code with Logz.io and Kinesis Firehose
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Observability data provides near real-time insights into the health and performance of AWS workloads, so that engineers can quickly address production issues and troubleshoot them before widespread customer impact. As AWS workloads […]
Introducing native Delta Lake table support with AWS Glue crawlers
June 2023: This post was reviewed and updated for accuracy. Delta Lake is an open-source project that helps implement modern data lake architectures commonly built on Amazon S3 or other cloud storages. With Delta Lake, you can achieve ACID transactions, time travel queries, CDC, and other common use cases on the cloud. Delta Lake is […]
Getting started with AWS Glue Data Quality for ETL Pipelines
June 2023: This post was reviewed and updated with the latest release from AWS Glue Data Catalog. Today, hundreds of thousands of customers use data lakes for analytics and machine learning. However, data engineers have to cleanse and prepare this data before it can be used. The underlying data has to be accurate and recent […]
Amazon EMR Serverless cost estimator
Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run applications using open-source big data analytics frameworks such as Apache Spark and Hive without configuring, managing, and scaling clusters or servers. You get all the features of the latest open-source frameworks with the performance-optimized […]









