AWS Big Data Blog

Category: AWS Glue

The following architecture diagram shows SingleStore connecting with AWS Glue for an ETL job.

Building fast ETL using SingleStore and AWS Glue

Disparate data systems have become a norm in many companies. The reasons for this vary: different teams in the organization select data system best suited for its primary function, the responsibility for choosing these data systems may have been decentralized across different departments, a merged company may still use separate data systems from the formerly […]

Validate, evolve, and control schemas in Amazon MSK and Amazon Kinesis Data Streams with AWS Glue Schema Registry

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Data streaming technologies like Apache Kafka and Amazon Kinesis Data Streams capture and distribute data generated by thousands or millions of applications, websites, or machines. These technologies […]

The state machine transforms data using AWS Glue.

Building complex workflows with Amazon MWAA, AWS Step Functions, AWS Glue, and Amazon EMR

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a fully managed service that makes it easy to run open-source versions of Apache Airflow on AWS and build workflows to run your extract, transform, and load (ETL) jobs and data pipelines. You can use AWS Step Functions as a serverless function orchestrator to build scalable […]

The following image shows how a player is positioned based on this data.

Estimating scoring probabilities by preparing soccer matches data with AWS Glue DataBrew

In soccer (or football outside of the US), players decide to take shots when they think they can score. But how do they make that determination vs. when to pass or dribble? In a fraction of a second, in motion, while chased from multiple directions by other professional athletes, they think about their distance from […]

We use Amazon SNS for sending notifications to users, and EventBridge is integrated to schedule running the Step Functions workflow.

Orchestrating an AWS Glue DataBrew job and Amazon Athena query with AWS Step Functions

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. Also, as we start building complex data engineering or data analytics pipelines, we look for a simpler orchestration mechanism with graphical user interface-based ETL (extract, transform, load) tools. Recently, AWS […]

Let’s look at PyDeequ’s main components, and how they relate to Deequ (shown in the following diagram)

Testing data quality at scale with PyDeequ

June 2024: This post was reviewed and updated to add instructions for using PyDeequ with Amazon SageMaker Notebook, SageMaker Studio, EMR, and updated the examples against a new dataset. 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 […]

As illustrated in the following architecture diagram, the DQAF exclusively uses serverless AWS technology.

Building a serverless data quality and analysis framework with Deequ 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. With ever-increasing amounts of data […]

This blog covers use case based walkthroughs of how we can achieve the top 7 among those transformations in AWS Glue DataBrew.

7 most common data preparation transformations in AWS Glue DataBrew

For all analytics and ML modeling use cases, data analysts and data scientists spend a bulk of their time running data preparation tasks manually to get a clean and formatted data to meet their needs. We ran a survey among data scientists and data analysts to understand the most frequently used transformations in their data […]

The following diagram shows the workflow to connect Apache Airflow to Amazon EMR.

Dream11’s journey to building their Data Highway on AWS

This is a guest post co-authored by Pradip Thoke of Dream11. In their own words, “Dream11, the flagship brand of Dream Sports, is India’s biggest fantasy sports platform, with more than 100 million users. We have infused the latest technologies of analytics, machine learning, social networks, and media technologies to enhance our users’ experience. Dream11 […]

We’ll walk through a solution that takes sets up a recurring Profile job to determine data quality metrics, and using your defined business rules.

Setting up automated data quality workflows and alerts using AWS Glue DataBrew and AWS Lambda

Proper data management is critical to successful, data-driven decision-making. An increasingly large number of customers are adopting data lakes to realize deeper insights from big data. As part of this, you need clean and trusted data in order to gain insights that lead to improvements in your business. As the saying goes, garbage in is […]