A New Approach To Building Big Data Apps: Product Recommendations Using Fast Data & Machine Learning

Fast big data is the next wave in big data. New use cases that require faster insight and action by analyzing data in motion before it lands in a data lake are emerging every day. Big data is a big part of how modern retail works. One use case is Product Recommendation apps using machine learning and fast data analytics.

DataTorrent, a leader in building fast big data apps is teaming with Mindstix Software Labs, experts in big data retail solution delivery, to present a real-life use case and demo that features the latest in fast analytics, data science, and machine learning for retail applications that delivers real-time product and services recommendations.

DataTorrent is redefining how to build and deploy big data apps with a focus on data-in-motion analytics, enterprise-ready and fast time to value. We work across all industries to help organizations get in front of fast big data to achieve their business outcomes.

Presenters:

Nathan Trueblood, DataTorrent, VP Product Management

Kanad Dixit, Mindstix Labs, VP Data Science