Ottawa, ON, Canada - (NewMediaWire) - September 25, 2015 - MediaMiser, a leading provider of media monitoring and analysis software is proud to be nominated for a 2015 Data Impact Awards, presented by Cloudera, in the category of Most Admirable Architectures (Operational Analytics).

This awards program recognizes organizations running applications built using Hadoop, to share best practices for achieving big data success, and to showcase the impact projects are having on the organization, business, and/or society at large. The program highlights achievements in nine categories classified into three overarching themes: Biggest Business Metrics, Best Business Stories and Most Admirable Architectures.

MediaMiser’s Mercury platform was nominated for its unique approach in leveraging an analytic aggregate as part of an online application that acts in real time to support media monitoring.

"We've been building on top of Hadoop for more than 4 years now. After consulting and working with Cloudera engineers on our future plans, we are very pleased with this nomination and recognition. We will soon be turning more news into knowledge" says David Nadeau, Chief Technology Officer for MediaMiser.

The winners of the Data Impact Awards are appointed by an esteemed panel of influencers in the data management and analytics industry. Cloudera will announce award winners at Strata + Hadoop World 2015 in New York City, NY during an invitation-only dinner event on Tuesday, September 29, 2015.

About MediaMiser MediaMiser (https://mediamiser.com) is a leading provider of media monitoring and analysis software and professional services for organizations of all sizes. Through innovative web-based and mobile solutions, MediaMiser reduces the time and effort it takes to gather, analyze and distribute valuable business intelligence extracted from traditional and social media sources. For organizations that prefer to outsource, MediaMiser also provides detailed analysis reports and daily media briefings through an expert client services team.