New Approach To Building Big Data Apps: Product Recommendations, Fast Data & ML

Organizer: Big Data (native Hadoop) Ingest and Transform, Raleigh
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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.

Nathan Trueblood, DataTorrent, VP Product Management
Kanad Dixit, Mindstix Labs, VP Data Science

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