Learn how a mobile advertising company builds streaming pipelines on AWS using Upsolver’s Visual SQL IDE and automated data lake engineering.
In this webinar you will learn:
– The cost and analytics delays AppsFlyer struggled with using BigQuery
– How AppsFlyer’s shift to an AWS data lake saved them $1M a year on a single use case
– How AppsFlyer maintained query performance and analytics agility using Upsolver’s no-code data lake engineering platform
AppsFlyer develops a mobile ad attribution and marketing analytics platform that allows advertisers and marketing professionals to analyze which campaigns drive the best results, giving brands a holistic view of every user journey across platforms, channels, and devices.
Managing their enormous flow of data in Google BigQuery had become exceedingly expensive and time-consuming, leading to cost overruns and a growing backlog of analytics jobs that hampered the productivity of data practitioners in the company. To reduce costs and become more agile, they decided to shift to an AWS data lake, using Amazon Athena as the query engine and Upsolver to simplify data lake processing.