Customer References


With over 600,000 names in BluePages, IBM’s employee directory, and over 500,000 queries daily, the average search session takes two minutes. IBM needed a faster, more efficient application. Using Apache open source technologies, the IBM CIO Lab Analytics team developed a new people-search application that allows flexible queries and returns as many results as possible, as fast as possible.


Vestas uses one of the largest supercomputers worldwide along with a new big data modeling solution to slice weeks from data processing times and support 10 times the amount of data for more accurate turbine placement decisions. 


Using a high-performance data warehouse appliance from IBM for advanced analytics, Merkle is transforming its clients’ raw data into unprecedented insight that influences the marketing process and helps staff predict customer preferences with incredible accuracy. 

University of Maryland, Baltimore County (UMBC)

University of Maryland, Baltimore County (UBMC) aimed to create a powerful new solution to analyze the wildfire smoke patterns to promote informed decisions for public evacuations and health alerts. Researchers needed a sophisticated analysis platform with powerful real-time processing capabilities for tracking how fire and smoke spread. The UMBC research team is using advanced predictive analytics to outsmart wildfires. The analysis solution draws from surface, aerial and satellite sensors to pinpoint the movement and impact of wildfires in real time. 


A U.S. Department of Energy National Lab turned to IBM Business Partner, TerraEchos, to implement an advanced, covert security and surveillance system, based on the TerraEchos Adelos S4 System and IBM technology. Because the solution captures and transmits real-time, streaming acoustical data from around the lab premises, security staff has unprecedented insight into any event and can “hear” what is going on—even when the disturbance is miles away.  


MediaMath needed serious analytical power to help ad buyers optimize performance for any advertiser, campaign or marketing objective. To gain a transparent view of every impression and factor affecting performance of over 13 billion ad impressions per day, the company selected the IBM Netezza Data Warehouse Appliance.

State University of New York (SUNY) at Buffalo

SUNY Buffalo researchers used IBM Netezza and Revolution Analytics to power the study of exponentially large gene interaction associated with multiple sclerosis. The solution helped researches consolidate all reporting and analysis in one location to improve the efficiency, sophistication and impact of their research.

Barnes & Noble

Barnes & Noble improved communications with suppliers by deploying a web-based sales and inventory portal on a pre-integrated, pre-optimized data warehouse appliance from IBM. Publishers log on to get metrics on sales and inventory, then use the information to optimize inventory levels and avoid costly returns and stock-outs.


Working with IBM, Fiserv is turning billions of transactions into actionable insights that help small and midsize banks and credit unions better target offers and maximize their marketing dollars to grow profitable customer relationships while competing with the analytic capabilities of new mega banks. 


TEOCO wanted to analyze 500 TB of data from call detail records and inter-carrier invoices daily to help communication service providers (CSPs) identify cost savings and improve services. TEOCO’s assurance and analytics solutions, powered by the IBM Netezza data warehouse appliance, enable CSPs to access and analyze massive amounts of data to uncover the source of cost and network issues.