{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/410b4ecedb664fc9bb0976f37f07032e\" frameborder=\"0\" width=\"1700\" height=\"1275\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1275,"width":1700,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1275,"thumbnail_width":1700,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/410b4ecedb664fc9bb0976f37f07032e-5231cd1576538a43.gif","duration":300.152,"title":"Building an End-to-End Analytics Pipeline for Customer Churn Analysis","description":"In this video, I walk you through my telco-churn analytics pipeline database, detailing how raw customer churn data flows from S3 to Athena for analysis. We start with raw data in S3, which is processed into Parquet format for improved performance and efficiency. I demonstrate how to query this data using SQL in Athena and highlight key insights, such as higher churn rates for month-to-month contracts. Additionally, I've set up an automation with EventBridge to ensure our processed dataset stays up to date daily. Please take a look at the views I've created and consider how these insights can inform our business decisions."}