AWS Big Data Blog

Category: AWS Glue

How JPMorgan Chase built a data mesh architecture to drive significant value to enhance their enterprise data platform

April 2024: This post was reviewed for accuracy. This is a joint blog post co-authored with Anu Jain, Graham Person, and Paul Conroy from JP Morgan Chase.  Most modern organizations recognize that their data benefits their entire enterprise. Data has value to the individual business process that produces it, but data’s additional potential can be […]

Monitor data quality in your data lake using PyDeequ and AWS Glue

March 2023: You can now use AWS Glue Data Quality to measure and manage the quality of your data. AWS Glue Data Quality is built on DeeQu and it offers a simplified user experience for customers who want to this open-source package. Refer to the blog and documentation for additional details. In our previous post, we […]

Use Grok patterns in AWS Glue to process streaming data into Amazon Elasticsearch Service

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Recently, we launched AWS Glue custom connectors for Amazon OpenSearch Service, which provides the capability to ingest data into Amazon OpenSearch Service with just a few clicks. You can now use Amazon OpenSearch Service as a data store for your […]

How OrthoFi delivers better insights for customers with Amazon Redshift and AWS Glue

This is a guest post by Christa Pierson and Jon Fearer at OrthoFi. OrthoFi is an orthodontic industry leader in revenue cycle management (RCM), and has partnered with more than 550 orthodontic practices across the country, delivering an end-to-end platform that enables orthodontists to bring on more patients and run their businesses more effectively. To […]

Orchestrate AWS Glue DataBrew jobs using Amazon Managed Workflows for Apache Airflow

As the industry grows with more data volume, big data analytics is becoming a common requirement in data analytics and machine learning (ML) use cases. Analysts are building complex data transformation pipelines that include multiple steps for data preparation and cleansing. However, analysts may want a simpler orchestration mechanism with a graphical user interface that […]

Estimate Amazon EC2 Spot Instance cost savings with AWS Glue DataBrew, AWS Glue, and Amazon QuickSight

AWS provides many ways to optimize your workloads and save on costs. For example, services like AWS Cost Explorer and AWS Trusted Advisor provide cost savings recommendations to help you optimize your AWS environments. However, you may also want to estimate cost savings when comparing Amazon Elastic Compute Cloud (Amazon EC2) Spot to On-Demand Instances. […]

The following diagram shows the overall architecture to address our two challenges.

Extract multidimensional data from Microsoft SQL Server Analysis Services using AWS Glue

AWS Glue is fully managed service that makes it easier for you to extract, transform, and load (ETL) data for analytics. You can easily create ETL jobs to connect to backend data sources. There are several natively supported data sources, but what if you need to extract data from an unsupported data source? What if […]

Migrate terabytes of data quickly from Google Cloud to Amazon S3 with AWS Glue Connector for Google BigQuery

This blog post was last updated July, 2022 to update the new version of the connector and details on how to push down queries to Google BigQuery. The cloud is often seen as advantageous for data lakes because of better security, faster time to deployment, better availability, more frequent feature and functionality updates, more elasticity, […]

Doing data preparation using on-premises PostgreSQL databases with AWS Glue DataBrew

Today, with AWS Glue DataBrew, data analysts and data scientists can easily access and visually explore any amount of data across their organization directly from their Amazon Simple Storage Service (Amazon S3) data lake, Amazon Redshift data warehouse, and Amazon Aurora and Amazon Relational Database Service (Amazon RDS) databases. Customers can choose from over 250 […]

Automate dynamic mapping and renaming of column names in data files using AWS Glue: Part 1

A common challenge ETL and big data developers face is working with data files that don’t have proper name header records. They’re tasked with renaming the columns of the data files appropriately so that downstream application and mappings for data load can work seamlessly. One example use case is while working with ORC files and […]