Data Visualisation: The Google Translate Between Business and Data Teams?

Published 20 May 2021

By Maggie Chan



Data visualisation has come a long way since the era of making column and bar charts on excel. New visualisation tools like Tableau and Google Charts offer a user-friendly solution that caters to a range of users of varying skills. Translating bland tables of data into graphical modules of data and information has helped accelerate the trend of ‘data-driven’ decisions across organisations.

Economic output in U.S Counties Check out this interactive data visualisation on Tableau Public!

Lost in translation: data scientists and business decision makers.

With 97.2% of executives investing in data-driven businesses NewVantage Partners, why is it that only 28.3% of organisations claim to have data-centric culture? One reason (among many others) may be that somewhere along the way, the communication between key business decision makers and data scientists is lost in translation.

You would think that using data visualisation solves the problem, right? Well… not completely. “Numbers don’t lie… but people do.”. Converting a set of data into pretty graphs might seem like a simple task, but without a clear understanding of business needs, the insights could be rendered useless. At the end of the day, insights derived from the data are presented to business executives, each with their own objectives, aims and goals. Producing a data visualisation without a comprehensive understanding of its desired audience and business motive is like providing an answer to a question that you do not know. Chances are… your answer will not be correct!

So where to from here?

  • Close the language gap between business and data teams through clear visualisations and briefings.
  • Understand the business context, motives, and strategies before the charts.
  • Know your audience – you do not want them to be unengaged and dozing off with your technical language. Re-frame your expressions to make sure they are aligned and onboard.

“The vast majority of my guests tell (me) that the key skills for data scientists are….the abilities to learn on the fly and to communicate well in order to answer business questions, explaining complex results to nontechnical stakeholders.”

-Hugo Bowne-Anderson (Harvard Business Review)

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Tags: data science data visualisation