Andreas Bartsch, Head of Service Delivery at PBT Group
Data visualisation enables decision-makers to spot patterns and identify trends and correlations in company data that would otherwise have remained hidden. But contrary to popular belief, it is more a business function than a technological one.
Think of it as the story being told about the data and information relevant to a user group. These user groups can include everyone from executives and managers to sales reps and marketers. As such, it is critical for companies to better understand the profile of the person responsible for creating this visual narrative.
In my experience, many organisations incorrectly use a technologist and position the role as a front-end developer, or even a report developer. These individuals put together graphs, dashboards, and reports, and while this is not wrong as such, it misses the subtle requirements behind true data visualisation.
This includes not necessarily having the business insights or understanding to capture the essence of what the data visualisation narrative must be about. Companies therefore require people who have skills aligned to statistical methods.
For example, they understand concepts like regression modelling, frequency distribution and the impact it has on the visualisation process. Of course, these individuals must also have relevant industry experience as it relates to the sector focused on. For them, it is about having the capability to identify the best tools and mechanisms that represent data in a useful way that makes the most business sense and that can add the most value.
A technologist might have an implicit understanding of the technology itself but would not necessarily understand how the data is analysed. On the other hand, a data visualisation expert is somebody with the right educational background who can use technology as an enabler. With technology significantly more intuitive today than in the past, IT skills in this regard have become less of a priority.
Ultimately, visualisation is meaningless if data is not presented in the correct way.
If companies do not have an accurate view of the skills required for data visualisation, the default is to assign it to the IT department. However, data visualisation could be performed by an expert such as an actuary, a statistical modeller, or even a financial modeller. If a person does not understand the business problem, or the methods to articulate the numbers in a meaningful way, then they will be unable to use the tools available to them to present the information optimally.
Therefore, business needs must be married with technology to ensure visualisation is the most effective it can be. Sending IT personnel on visualisation courses mean little if they are unable the provide effective output because they do not have the right statistical and business background in place. The Data Visualisation Engineer has evolved into a role that requires some statistical background, adequate business acumen, an exposure to data engineering techniques, and the ability to use a variety of visualisation tools in producing visually appealing, sensible output.
In other words, for data visualisation to work it must be driven by those who can translate the raw ‘numbers’ into a data story and deliver real business value to those in the organisation.