The * umBlog - worth knowing from the world of data and insights into our unbelievable company.

Awesome Data Thinkers – new roles and new skills for the Data Enterprise

Big Data and Data Science are established and well understood, but the demands on them have grown significantly. The objective of companies is no longer only to translate data into business value, but to become digitally sovereign and sustainably successful. This requires a new role with awesome skills: the Data Thinker. Here is a definition.

The Awesome Data Thinker (c) The unbelievable Machine Company

A good start

When Big Data and Data Science came onto the scene in 2010, Drew Conway used a pioneering diagram to define data science as an interdisciplinary field and a data scientist as somebody who possesses the appropriate skills and expertise. In 2012 Hilary Mason added important aspects and coined the legendary term "awesome nerds" for Data Science buffs.

Since then a lot has happened. The definition of data science is widely accepted, while the diverse roles involved are fundamentally understood and have been added to: Data Engineering, Data Operations, Data Visualization and even Data Arts. With these roles it is possible to work and plan, build and develop teams – and ultimately advance an organization and its Data Enterprise, too.

So far, so no longer enough

The thing missing from all of these profiles is the relation to business. All of the jobs named above are more or less IT jobs – programmers, modelers, tests, deployments, agile teams and, to cut to the chase, software development. Business itself has changed very little over the course of the decade. There are still the same project leaders, product managers and experts in areas such as marking and CRM, and these people are finding it difficult to understand data end-to-end and to make use of new solutions.

Klaas Bollhoefer, *um Chief Data Scientist, and Florian Dohmann, *um Senior Data Scientist, noticed this some time ago. And what’s more, they recognized that there is a gap waiting to be filled by service providers.

In this gap it is necessary to approach things "from a data point of view", in a creative and value-adding manner – opening up new methods, possibilities and, what’s more, a new culture with new leadership. This begins with the fundamental way of thinking – e.g. how a business can use data – and extends all the way to implementation into the organization. In order to achieve this goal, companies need competent pioneers and companions. They require their own experts who are masters of not just buzzword bingo but the actual subject matter in hand, and who offer comprehensive orientation on the path to Data Enterprise.

All of this comes under the umbrella of Data Thinking. From a service provider’s view: new consultation services addressing data, algorithms, technology and mindset. From a company’s view: the need to create time and scope for development and innovation. By implementing these changes it is possible to concentrate on and get to grips with the various facets of digital development – and in doing so continue to "think" and to develop an existing process or concept in the company.

The thing missing here is a new role. The established definition of data science and data scientists is no longer enough. Therefore, Klaas Bollhoefer and Florian Dohmann are now describing and labeling a new interdisciplinary expertise:

The "Awesome Data Thinker" – bringing together Data Science, Business Innovation, Facilitation and Arts

Here is an explanation of how the pair see these roles, without describing them in full detail – just as Conway and Mason also chose to do – since it is important to have scope for interpretation in order to be and remain creative and agile.

Data Science
The original interdisciplinary expertise, as previously described with the diagram.

Business Innovation
Consciously changing an existing business model or creating a new one. Includes general management expertise from the fields of innovations management, business development and strategic planning.

Managing and developing dynamic group processes and company processes. Using dynamics of groups, networks, organizations and communities in achieving common objectives. This requires allowing scope for setting out the framework and taking on a moderating role to ensure that everything heads in the same direction.

Being prepared and able to think in new ways and in any direction. This includes specifically reflecting on things we perceive as difficult to change and dismantling them in order to turn them into something new. It also concerns designing (or redesigning) organizations, processes and routines – generally using the existing ones but also considering its components and merging them to create a new product.

Where each two disciplines come together there are competences and expertise that already exist in the context of developing organizations.

The awesomeness is the key

As all disciplines, competences and roles come together, the key is something new and important. A new scope. The human form of Data Thinking: the Data Thinker. "Awesome" because he is able to think differently about data science and data, the business world and organization, innovation and strategy, and then combine them creatively. Because he is able to build bridges to reach completely new possibilities and opportunities. Because as a coach and moderator he is able to remove hurdles, point out alternatives and positively influence the dynamic processes within an organization. And because he is able to promote data – a varied and dimensional topic – in the context of an organization, drive new developments and, in doing so, open up new opportunities.

Did you know...? Data Thinker is actually "the sexiest job in the world" today.


Here’s something else that may interest you:
What is Big Data? – A definition with five Vs
Where does Big Data begin? – Many perspectives, one classification

Download Data Thinking White Paper

Social Media

Latest Blog Posts


The unbelievable Machine
Company GmbH
Grolmanstr. 40
D-10623 Berlin

+49-30-889 26 56-0 +49-30-889 26 56-11

Free Whitepaper

"Hadoop 2: How to realize big data projects successfully" (German version)

To Whitepaper Download

Working at *um:

Go to the Career Page