We develop advanced statistical processes, routines and algorithms to create “computational quality” of data — the elimination of suspect or bad data not appropriate for analysis. We then apply proprietary filters and processes that remove outliers, eliminate data-bias and overly influential data to increase the “analytic quality” of data — the statistically improved quality of data appropriate for analysis. This leads to the highest level of “data survivability” — increases in the volume of source data remaining after our data analytics are applied. The result is we can deliver to customers the capability to achieve more accurate predictions of relative value.
Our analytics are dynamic, therefore, as the inputs change, so do our models. The technology of our platform was developed with future performance as a consideration. It is native C-language and an object-oriented .Net web-services, that we expect to function as a development platform.
We are able to target and apply our analytics to diverse markets. We can do this for two reasons. The first is because our analytics were originally conceived to address data and statistical challenges, not the challenges of a specific market or application. The result is our ValuelyticEngine™ is virtually ‘data agnostic’ — we are not concerned with the market, source, quality or characteristic of the data. As long as the data is comparable data in a digital format, we can unlock more value from that data for customers.
The second reason is that we designed our ValuelyticEngine as a technology platform. Our object-oriented architecture enables us to select the elements of our analytic technology that are best tuned to the market and data to achieve one purpose — to drive the best results for the customer. Often times we can rapidly create a new user-interface through a simple Excel™ add-in, or custom design a user-interface for a specific market. That’s the flexibility we have through this platform technology.
ValuelyticEngine™ is the Company’s patented technology platform from which we develop our proprietary solutions and applications. Our ValuelyticEngine is a dynamic algorithm in the sense that the predictive models are not pre-determined by a static or fixed statistical presumption. The resulting models are as much a function of the data our ValuelyticEngine encounters as they are the proprietary analytic processes and routines we employ. In this regard we are data-agnostic, as such, this approach opens our ValuelyticEngine to a wide array of markets and applications where we can add value. We give the user flexibility to determine which inputs from their data are employed creating a powerful “What if” capability that enables important insights to the data profile. And we accept data in the most common data formats interfacing with the vast majority of commercial data bases, proprietary databases and aggregations of data for user-specific decision support purposes.
Key Features
All of Valuelytics modules are currently deployed through a Microsoft Excel® Add-In that provides extremely fast calculations. It includes Excel Add-In functions (XLA files), customizable Excel templates and documentation. When installed, Valuelytics XLAs add functions to Excel that are intuitively familiar to users.
