AWS Big Data Blog

Category: AWS Glue

Exploring new ETL and ELT capabilities for Amazon Redshift from the AWS Glue Studio visual editor

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. In particular, we have observed an increasing number of customers who combine and integrate their data into an Amazon Redshift data warehouse to analyze huge data at scale and […]

Accelerate HiveQL with Oozie to Spark SQL migration on Amazon EMR

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. Apache Hive has performed pretty well for a long time. But with advancements in infrastructure such as cloud computing and multicore machines with large RAM, Apache Spark started to gain visibility by […]

Reference guide to build inventory management and forecasting solutions on AWS

Inventory management is a critical function for any business that deals with physical products. The primary challenge businesses face with inventory management is balancing the cost of holding inventory with the need to ensure that products are available when customers demand them. The consequences of poor inventory management can be severe. Overstocking can lead to […]

How Morningstar used tag-based access controls in AWS Lake Formation to manage permissions for an Amazon Redshift data warehouse

This post was co-written by Ashish Prabhu, Stephen Johnston, and Colin Ingarfield at Morningstar and Don Drake, at AWS. With “Empowering Investor Success” as the core motto, Morningstar aims at providing our investors and advisors with the tools and information they need to make informed investment decisions. In this post, Morningstar’s Data Lake Team Leads […]

Architecture Diagram

Implement column-level encryption to protect sensitive data in Amazon Redshift with AWS Glue and AWS Lambda user-defined functions

Amazon Redshift is a massively parallel processing (MPP), fully managed petabyte-scale data warehouse that makes it simple and cost-effective to analyze all your data using existing business intelligence tools. When businesses are modernizing their data warehousing solutions to Amazon Redshift, implementing additional data protection mechanisms for sensitive data, such as personally identifiable information (PII) or […]

Implement slowly changing dimensions in a data lake using AWS Glue and Delta

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. To illustrate an example, in a typical sales domain, customer, time or product are dimensions and sales transactions is a fact. Attributes within the dimension can change over time—a customer can change […]

shows a simplified data mesh architecture with a single producer account, a centralized governance account, and a single consumer account

AWS Glue crawlers support cross-account crawling to support data mesh architecture

Data lakes have come a long way, and there’s been tremendous innovation in this space. Today’s modern data lakes are cloud native, work with multiple data types, and make this data easily available to diverse stakeholders across the business. As time has gone by, data lakes have grown significantly and have evolved to data meshes […]

Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 2: AWS Glue Studio Visual Editor

In the first post of this series, we described how AWS Glue for Apache Spark works with Apache Hudi, Linux Foundation Delta Lake, and Apache Iceberg datasets tables using the native support of those data lake formats. This native support simplifies reading and writing your data for these data lake frameworks so you can more […]

How Infomedia built a serverless data pipeline with change data capture using AWS Glue and Apache Hudi

This is a guest post co-written with Gowtham Dandu from Infomedia. Infomedia Ltd (ASX:IFM) is a leading global provider of DaaS and SaaS solutions that empowers the data-driven automotive ecosystem. Infomedia’s solutions help OEMs, NSCs, dealerships and 3rd party partners manage the vehicle and customer lifecycle. They are used by over 250,000 industry professionals, across […]

Simplify data loading into Type 2 slowly changing dimensions in Amazon Redshift

Thousands of customers rely on Amazon Redshift to build data warehouses to accelerate time to insights with fast, simple, and secure analytics at scale and analyze data from terabytes to petabytes by running complex analytical queries. Organizations create data marts, which are subsets of the data warehouse and usually oriented for gaining analytical insights specific […]