MATHEMETRICA - Our Edge

Our Edge

Most people in large organisations are either Business or IT professionals. At Mathemetrica, we attract and retain experts that are brilliant at not only both, but also Mathematics & Statistics -creating a powerful combination of skills. These skills are then mainly applied to Accounting, Banking, Finance, Investment, Risk Management, across the domains of Data, Systems and Analysis.

"Data storage combined with data analysis isolates new business opportunities"

We also work in many other sectors such as Government Agencies, Telecommunications, Marketing, Manufacturing and other corporates. See our Clients page for more details and Case Studies.

An example of our unique value add is in building a Bank trading portfolio decision engine. Having an army of IT professionals will not help. How can even the best programmer code the necessary mathematics of Options Trading if most programmers do not understand mathematics? How can a mathematician/statistician design the necessary Data Warehouse if these people are mainly academics without the corporate experience to understand Triggers, Database Pages and Clustered Indexes? How can Business people design and build complex IT systems to make their lives easier? Where other firms will fail, Mathemetrica will come to the fore. We provide solutions that are "out of the box" which involve lateral thinking and complete mastery of each of these three core domains of knowledge.

"The importance of mastering all three schools of thought"

Why settle for a great idea that can make you some money when Mathemetrica can find you the optimal solution to make you the most amount of money? Mathemetrica’s edge is that our staff are experts in all aspects of the Data Warehousing, Business Intelligence & Predictive Data Analytics industry. Our value proposition is that through our superior technical advantage and our proven application of these skills to business, we can deliver the complete optimal solution. Our business is in adding value to your business through robust data analysis.