AWS Big Data Blog

Introducing AWS Glue Flex jobs: Cost savings on ETL workloads

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Typically, these […]

Forwood Safety uses Amazon QuickSight Q to extend life-saving safety analytics to larger audiences

This is a guest post by Faye Crompton from Forwood Safety. Forwood provides fatality prevention solutions to organizations across the globe. At Forwood Safety, we have a laser focus on saving lives. Our solutions, which provide full content and proven methodology via verification tools and analytical capabilities, have one purpose: eliminating fatalities in the workplace. […]

Walkthrough Overview

Design patterns to manage Amazon EMR on EKS workloads for Apache Spark

Amazon EMR on Amazon EKS enables you to submit Apache Spark jobs on demand on Amazon Elastic Kubernetes Service (Amazon EKS) without provisioning clusters. With EMR on EKS, you can consolidate analytical workloads with your other Kubernetes-based applications on the same Amazon EKS cluster to improve resource utilization and simplify infrastructure management. Kubernetes uses namespaces to provide isolation between […]

Best practices to optimize cost and performance for AWS Glue streaming ETL jobs

AWS Glue streaming extract, transform, and load (ETL) jobs allow you to process and enrich vast amounts of incoming data from systems such as Amazon Kinesis Data Streams, Amazon Managed Streaming for Apache Kafka (Amazon MSK), or any other Apache Kafka cluster. It uses the Spark Structured Streaming framework to perform data processing in near-real […]

Manage data transformations with dbt in Amazon Redshift

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. Amazon Redshift enables you to use your data to acquire new insights for your business and customers while keeping costs low. Together with price-performance, […]

Develop an Amazon Redshift ETL serverless framework using RSQL, AWS Batch, and AWS Step Functions

Amazon Redshift RSQL is a command-line client for interacting with Amazon Redshift clusters and databases. You can connect to an Amazon Redshift cluster, describe database objects, query data, and view query results in various output formats. You can use enhanced control flow commands to replace existing extract, transform, load (ETL) and automation scripts. This post […]

How Epos Now modernized their data platform by building an end-to-end data lake with the AWS Data Lab

Epos Now provides point of sale and payment solutions to over 40,000 hospitality and retailers across 71 countries. Their mission is to help businesses of all sizes reach their full potential through the power of cloud technology, with solutions that are affordable, efficient, and accessible. Their solutions allow businesses to leverage actionable insights, manage their […]

Use SQL queries to define Amazon Redshift datasets in AWS Glue DataBrew

July 2023: This post was reviewed for accuracy. In the post Data preparation using Amazon Redshift with AWS Glue DataBrew, we saw how to create an AWS Glue DataBrew job using a JDBC connection for Amazon Redshift. In this post, we show you how to create a DataBrew profile job and a recipe job using […]

Schedule email reports and configure threshold based-email alerts using Amazon QuickSight

Amazon QuickSight is a cloud-scale business intelligence (BI) service that you can use to deliver easy-to-understand insights to the people you work with, wherever they are. You can build dashboards using combinations of data in the cloud, on premises, in other software as a service (SaaS) apps, and in flat files. Although users can always […]

Accelerate your data warehouse migration to Amazon Redshift – Part 6

This is the sixth in a series of posts. We’re excited to share dozens of new features to automate your schema conversion; preserve your investment in existing scripts, reports, and applications; accelerate query performance; and potentially simplify your migrations from legacy data warehouses to Amazon Redshift. Check out all the previous posts in this series: […]