Caryl Yuhas is a Solutions Architect at Databricks, where she provides consultative and technical support for companies looking to optimize their data pipelines with Apache Spark and Databricks. Previously, as a Product Manager at MediaMath, Caryl worked on a solution for measuring the incremental return of advertisers’ digital media investments. It was during this project that she first began to work with distributed data processing and developed a passion for Spark and cloud computing. She is an alumna of the University of Pennsylvania, where she received a B.S.E. in Chemical and Biomolecular Engineering.
Companies doing any kind of advertising typically have an attribution process that joins users' conversions with the impressions that they were served or that they clicked on. The standard workflow is typically a batch job that runs every few hours or once a day. However, as technology gets more sophisticated, advertisers are looking for more real-time reporting and results. This talk presents an example of a foundational architecture for near real-time attribution and advanced analytics against real-time impression and conversion data using Structured Streaming and Databricks Delta. Session hashtag: #ExpSAIS13