Pattern Discovery Technologies Inc. is a pioneer in the field of data mining and predictive analytics.
Founded in 1997 as a spin-off from the world renowned Pattern Analysis and Machine Intelligence (PAMI) Lab at the University of Waterloo, Pattern Discovery continues to push the envelope in developing solutions that tackle the most challenging data mining, analysis and optimization problems for industrial processes.
Our products and services are used by leading companies engaged in complex industrial processes such as petroleum refining, mineral and metal extraction, energy and renewables, food processing, and pharmaceutical operations, to name a few.
Leveraging their existing investments in process instrumentation, these companies search for clues hidden in the volumes of data generated daily that will uncover opportunities for continuous improvement in their operations.
We are also actively expanding our business into new industries, including mineral & metal production, power generation, and water treatment operations.
The ability to characterize key performance factors and forecast events using Intelligent Analytics can return crucial dividends. In operations that are complex and multi-faceted, count on Pattern Discovery’s state-of-the-art technologies to provide the insight needed to take control of the situation.
Discover new & unique relationships that are not intuitively obvious
Optimize processes and resources by understanding and quantifying the key parameters that drive operational efficiencies
Predict results that take into account the interrelationships of complex multi-dimensional factors (forecast events before they happen)
Make decisions that can be acted on more confidently and more consistently, using a basis that is squarely supported by the data that drives the operation (free of assumptions and personal biases)
Leverage existing investments in data collection and aggregation by integrating Discover*e to provide advanced analysis solutions
Predicting with confidence is a powerful tool in any decision making process. To facilitate confident prediction, the descriptive patterns found are then transformed into production rules for predictions. The strength of a rule is measured by Weight of Evidence (WoE), which provides evidence that a specific pattern contributes to a target event. Following this same approach, new data can be classified using the rules established, and the WoE of each rule is accumulative in support of the classification with partial information.
This approach provides a totally unbiased, data driven approach to data mining and predictive analytics. It works with high order relationships, taking into account all of the factors that should be considered in performing analysis of complex datasets. The results of both the data mining exercise and the prediction are descriptive in nature meaning they can be interpreted in plain English by subject matter experts to derive greater insight into their process or investigation. And knowing the reasons why a particular prediction is being made can lead to the establishment of a proper set of actions or decisions based on the predicted result.
Paul is the President and CEO of Pattern Discovery Technologies Inc. He is a graduate of the University of Toronto, Civil Engineering program. He is a veteran of the software industry, having served in executive capacities with both entrepreneurial and established software firms for the past 30 years.
Prior to joining Pattern Discovery in February of 2004, Paul was VP Sales at Sitraka Inc., a recognized leader in the Java development space. He participated in the successful acquisition of Sitraka by Quest Software in November of 2002. Before working with Sitraka, Paul spent 15 years in the Computer Aided Design/Computer Aided Manufacturing (CAD/CAM) marketplace with Auto-trol Technology and Rand Worldwide.
Ed is an active member of Maple Leaf Angels (MLA) since 2014, winning the New Member of the Year award for 2016, and the Angel of the Year award for 2017. Currently Ed is a member of the board, and chairs the Investment Review Committee. Prior to that, Ed was the co-founder and Chief Technology Officer of Sitraka Inc. (formerly KL Group), Canada’s largest self-financed software company prior to its acquisition by Quest Software (now a part of Dell). Sitraka was a six-time winner of Canada’s 50 Best Managed Private Companies, was named as one of Canada’s Top 100 Employers, as well as numerous other awards. Ed has been a member of the board at the St. Joseph’s Health Centre Foundation in Toronto for the past four years. Ed is also active in the startup community, mentoring students at the University of Toronto’s Hatchery program. He holds a MSc in Computer Science from the University of Toronto, and a B Math from the University of Waterloo.