This blog post discusses optimizing data pipelines in cloud environments using AWS services. It outlines a typical serverless data pipeline architecture, including AWS Glue for ETL processes, Amazon S3 for data lake storage, and Amazon QuickSight for analytics. The article emphasizes the importance of efficient data delivery and provides strategies for optimizing AWS Glue jobs, such as scaling cluster capacity and minimizing data scans. It also covers the use of AWS Glue Workflows for orchestrating ETL pipelines and QuickSight’s SPICE for fast data insights. The post concludes by demonstrating how to automate the entire process using AWS Step Functions and CloudWatch event triggering, ensuring timely and ordered updates of QuickSight datasets for up-to-date insights.