Data-thinking skills

Skills for data driven innovation

Skills for data

Skills for data

Data will be a critical factor inspiring the development and innovation in all sectors, from cars to catering and from holiday destinations to health treatments. Under the governments of the last few years millions of datasets have been released around the world and this could be the beginning of something actually big. The availability of large sets of data with socioeconomic relevance means that capacities to produce and analyse data are going to be essential for many jobs. Professionals will need skills to design and manage data-driven products and services.

“Ensuring that data creates value calls for a re-skilling effort that is at least as much about fostering a data-driven mind-set and analytical culture as it is about adopting new technology”(1). Organisations leading the current times are experiment-focused and have a data-oriented workforce.

What are the skills and knowledge required to exploit this new unlimited raw material?

Skills for making sense of data are a combination of knowledge and expertise that allows unveiling patterns and predicting trends. Data skills are an assortment of science, technology, design and communication involving multidisciplinary approaches. The table below is a summary of the main groups of skills.

  • Formal experimentation: Data requires a scientific approach: propose relevant questions, anticipating reasonable answers and designing robust test to validate scientific hypothesis. These are the basis of the scientific method, which requires such skills as selecting samples or deciding the suitable experiment.
  • Mathematical reasoning: Competencies in the interpretations and use of data are founded on mathematical models and methods. The algebra and calculus that tested us, as teenagers during our first university courses have become now a prerequisite. Not just statistics, but mathematical reasoning, logics and problem solving abilities are keys to play with data.
  • Visualization: Data visualisation techniques are a major part of the job, as quite often data have to be seen. Visualisation allows interpretation and discussion of information gathered from analytical data. New insights and ideas are facilitated as a consequence of the modelling of data through visual presentations and simulations. Do not forget that visualisation is nowadays a multimedia communication skill that combines text and images.
  • Security, reliability and accuracy: Anyone involved has to be responsible for the data used in the jobs, no matter if data are from individuals, corporate or collective. On the other side, organisations have to trust but at the same time verify their workforce.
  • Integrative thinking: Last but not least, data skills are not just about maths methods and tech tools but it is mainly about thinking. A thinking discipline trained to see the big picture and at the same time be careful with details. Considering all possibilities but at the same time pulling apart what is relevant from what is not, and being able to work with alternative ideas.

Any successful organisation requires the combined effort of many people, rather than just some IT professionals combined with elite PhDs or mathematicians.

(1) Data is useless without the skills to analyse it. 2012.



Professor and researcher at UPC.

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Onsanity’s expertise combines technology, design & science to promote collective intelligence in organisations, merging views from experts in economy, health, sociology or mathematics among others.

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Data-thinking skills was last modified: October 13th, 2016 by Josep Mª Monguet