About Advanced Analytics

Advanced Analytics is a grouping of analytic techniques used to predict future outcomes. Advanced analytics can include:

Predictive analytics

Simulation

Optimization

Advanced analytics are based on mathematical principals and started as descriptive statistics which are basically used to sum and count past occurrences for what has happened in the past which is useful in a reactive, course correction manner. Advanced analytics allows you to anticipate possible future outcomes and either capitalize on them or adjust now to impact the future.

The traditional technique for building a predictive model is based on hypothesis testing which more of a statistical approach. Data mining is a technique for building predictive models where the data is visually explored and used to determine which predictive model to use to “fit” the data. For example, if the data visually looks linear then a linear regression technique could be applied. However, if the data plots out logarithmically (fancy work for the hockey puck graph we’ve all seen) then a logistic regression technique could be applied.


So, why do we use advanced analytics?

Advanced analytic techniques allow us to create more precise models of the world around us. Models that can be applied throughout our business to help inform better decisions. Advanced analytics allows you to:

Every industry, every area in the business can use advanced analytics to help achieve cost effective, top line revenue growth that translates into real market value for the company.


Think advanced analytics is right for you?

Advanced analytic techniques allow us to create more precise models of the world around us. Models that can be applied throughout our business to help inform better decisions. Advanced analytics allows you to:

Every industry, every area in the business can use advanced analytics to help achieve cost effective, top line revenue growth that translates into real market value for the company.


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