Data processing using AWS Glue DataBrew

In the quest to build an end-to-end data platform, IT teams in organizations spend a significant amount of time creating data processing ETL pipelines. Typically, data processing is the responsibility of data engineers, who have to understand the rules of data transformations and then implement them. This means that other personas in the organization, such as data scientists or data analysts, have to rely on data engineers to help them with the structure of data they are looking for in their day-to-day tasks. The change cycles involve ETL, normalizing, cleaning the data, and finally, orchestrating and deploying in automated data pipelines. The whole process takes weeks and sometimes months. This creates a bottleneck and delays the final business outcomes.

AWS Glue DataBrew solves this exact problem by providing a serverless, no-code data preparation service, specifically targeted at data scientists and data analysts. With DataBrew, end users...