Breaking ETL barrier with Spark Streaming and Real Time Txn Volume Forecasting

We're excited to announce that we will have two sessions at the next Seattle Spark Meetup - this time in Bellevue at Concur's Bellevue Conference Center

Agenda

• 6:00pm: Networking

• 6:30pm: Breaking ETL Barrier with Spark Streaming

• 7:15pm: Real Time Transaction Volume Forecasting

• 7:40pm: Q&A / Wrap Up

Title: Breaking ETL barrier with Spark Streaming.

Description: Learn how Concur is transforming it's reporting solution from nightly batch processing to realtime using Spark streaming.

Bio: Santosh Sahoo - Santosh is a Principal Architect III at Concur leading the architecture for the data insights team. Prior to Concur he has worked at technical leadership roles at YelloBooks and Microsoft.

Title: Real Time Transaction Volume Forecasting

Description: Spark Streaming has support for streaming machine learning algorithms like linear regression and k-means. We have been experimenting with these to understand their usage, challenges as well as scalability.
In this usecase of forecasting transaction volume in real time, we will showcase how we designed and deployed the infrastructure to run this system. Also, share our experience with streaming analytics.

Bio: Anikate Singh - Anikate is a Data Sciences Engineer at Concur leading their Data Sciences engineering efforts. Prior to joining Concur, Anikate was a researcher at the University of Washington DataLab and a Senior Member Technical Staff at Oracle.

Steve Hastings - Steve is a member of the Data Science Engineering team at Concur working at the interface of engineering and data science. Prior to that, Steve worked as a Biologist at a variety of positions in academia and industry.