Modern, data- driven organizations consume massive amounts of data in search of any slight improvement in productivity or mission effectiveness that may prove to be crucial in gaining an advantage over a competitor. Unfortunately, the agility that organizations hope to gain by leveraging all their data assets is impacted by the poor scalability characteristics modern data analytics, the tools that extract useful knowledge from raw data, exhibit.

Treeminer is pioneering a new approach to data mining analytics that focuses on organizing data for speed of knowledge extraction. By organizing data in thin vertical strips, analytics become dramatically more efficient as datasets scale.

The Data Explosion

Data collection is exploding. It has been anecdotally reported that this year alone, more data will be collected than in the previous 5,000 years of human existence! The sheer volume of this data, couple with the need for ever increasing accuracy in mining methodologies has created an analysis bottleneck. The response by industry has been to either reduce the scope of the data to analyze by sampling, or to add farms of servers to process the ever increasing load, not a sustainable path.

Treeminer's Vertical Data mining technology represents the next evolutionary step in knowledge discovery. By organizing data vertically, we end up with highly compressed, lossless representations of the original data, with calculations for popular data mining tasks reduced to simple logical operations on the compressed vertical data structures. What results is dramatically improved performance, without impacting (and sometimes improving) the accuracy of the results.

Solid Academic Heritage

Treeminer is building off of the years of research that has gone into this technology, as evidenced by dozens of peer reviewed academic papers and successful demonstrations in signficant global competitions against the best analytics methods out there, we are developing and bringing to market software products designed to produce analytics results "in human time".

Over the years, vertical methods have been successfully demonstrated in a variety of data mining applications including Association Rule Mining (ARM), Classification (neural networks, SVM-like hyperplane methods, nearest neighbors), and Clustering approaches. What makes Treeminer unique is not only our ability to dramatically speed analytics performance by storing data in a way that makes it incredibly efficient to mine, but also our in house expertise to conceive and develop analytics algoritms designed to meet today's most difficult data mining challenges.

It's no longer necessary to trade off accuracy against speed when mining data: Introducing Treeminer, the Vertical Data Mining Company.

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