Looking forward into the future

Data Science is a collection of principles and techniques applied for data intensive analyses that investigate phenomenons, gather new knowledge, and correct or integrate existing knowledge by measuring the correctness, completeness and efficiency of the derived results, either by a predetermined (top-down) or an open (bottom-up) specification, query or hypothesis. [1]

Our skills

For a considerable time, the processes within the human mind have been the subject of scientific research. While the actual organ, when considered purely from the physical side, has been comprehensively studied and understood, we are still largely in the dark in respect of a more global understanding of the individual perception of the human mind and its respective interaction with the (notably ever more complex) environment.

 

Over the course of human evolution, visual perception in particular has proven to be beneficial to survival. Without any effort we can see and interpret objects and with the help of our memory we adjust our perception of the respective object through our stored experiences.


“I never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”

Sir Arthur Conan Doyle



The Magical Number Seven, Plus or Minus Two

On the other hand, there is the fact that the understanding of complex processes clearly was not beneficial and, therefore, does not form part of our capabilities or skills. Perhaps the most well known example of this insight is the article by George A. Miller, which was published in 1956. In a nutshell, Miller argued that the total number of objects an average human mind can process is limited to seven [2].

Modern Tools

The complexity of Pi

The complexity of Pi

In a surprisingly short time, taking into account the entire history of mankind, we have created tools which can explain and influence the world around us. This influence has a self-reinforcing effect and results in shorter innovation cycles.

 

Fundamental concepts like mathematics needed to be developed over thousands of years. At the same time, theories on the understanding of the world required hundreds of years. Industrialisation has influenced our lives for many decades. However, the continuing digitisation of our society has been taking place over the course of just a handful of years with ever increasing leaps in innovation.

 

It is the coming together of the availability of data and expanding technical possibilities, which not only brought about a renaissance of tried and tested concepts, but also the creation of completely new concepts that helped the creation of this company: We trade exclusively in data. Statistical data analysis, business intelligence, data warehouses, big data, AI, KDD and many more concepts which pursue similar goals and often use the same tools or procedures are currently experiencing a revival.

 

Vision & Mission

Our role is to consolidate results and progress in the field of data science. Besides, we develop process models to secure a practical realisation within the scope of analytical activity up to integrating the results into business operations with the goal of understanding the world by means of data.


[1] translated from a sefinition of Dr. M. L. Brodie in Understanding Data Science: An Emerging Discipline for Data-Intensive Discovery, in Shannon Cutt (ed.), Getting Data Right: Tackling The Challenges of Big Data Volume and Variety, O’Reilly Media, Sebastopol, CA, USA, June 2015

[2] (George A. Miller: "The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information". In: The Psychological Review. Band 63, 1956, S. 81–97).