diff --git a/_casestudies/any.md b/_casestudies/any.md index 6788e0b..5b3d7a4 100644 --- a/_casestudies/any.md +++ b/_casestudies/any.md @@ -11,7 +11,7 @@ download: casestudy.pdf ## The scene Our client, A&NY Media, is part of dmg::media – a large consumer media organisation with an annual turnover of over £1 billion. They manage the advertising for a number of major web properties, and their analysts needed up to date, detailed data in order to manage that advertising effectively. We used our Kixi cloud-based system to create customised data processing pipelines, which bring together, scrub, and summarise over 10 billion datapoints from 18 different sources overnight each night. @@ -27,9 +27,9 @@ This project embodied three key elements of our approach: ## By the numbers The system contains: - - 12 TB (over 106 billion datapoints in total) of compressed data stored - - Over 70 GB of data added daily from 18 sources via 5 different data vendors via various https web services and files via sftp - - Runs very efficiently: only one ETL server, and 8 database servers at peak times + - over 24 TB managed in AWS Redshift + - Over 170 GB of data added daily from over 45 sources via 8 data vendors via various https web services and files via sftp + - Runs very efficiently: only one ETL server, with on demand spark clusters to do larger pieces of analysis. ## Ongoing support Having built the original system, we also operate the system day to day, including: