Why Data Science?

Written by Martin Lucas

We live in an empirical world and data is the fundamental component that helps us understand the cause and effect of human needs and, in turn, how to build mathematical models to make this happen.

Data science is a combination of methodologies with statistical mathematics being the core throughout, with the data source dictating what you are doing with it.

Data can be key to corporate survival and has been this way for centuries; it’s what allowed Scottish Widows to create (and thrive) by calculating the average payouts based on life expectancies, children and partners. This foundation gave us the birth of actuary as a predictive data science. The fundamental of this modelling is profit; you have to make sure you are bringing in enough income, while not paying out too much but still paying enough to beat the competition and ultimately satisfy your customers.

Data is also thriving and going through accelerated growth in the digital world. Analytics is exploding and we do our part to accelerate this as digital data holds the key to personalised experiences because it is generated by the behaviour of individuals. If you analyse mass data you can find all sorts of unique stories that the data is telling you.

We add new data to everything we do using all the other parts of our model to identify new categories for data which make up the reasons why people prefer one product versus another. 

We call this new data type, preferential data and it is anchored on the truth of human desire. When you see past a number and feel the story the humans are telling that is where the data takes on a new 3D look.