In a Marketplace Where Tech is Ubiquitous, Individuals and Companies Need to Address the Prevalence of Big Data

Data science and data visualization are hot career choices and popular career development topics. In the last four years, Data Scientist has ranked as the #1 job in America, based on Glassdoor’s annual jobs report. Most of LinkedIn’s Top Startups in 2018 feature a significant reliance on data science and visualization. And CEOs are pitching their firm’s core competencies as generating, analyzing and selling data, seemingly for every business.

Companies and Careers Are Increasingly Driven By Data Science

In a recent conference I attended in Boston, the point was made by Carter Williams, Managing Director of iSelect Fund, that all companies and all industries are becoming tech companies. Data science is closely related to tech, and is already radically changing the marketplace. While industry digitalization and tech adoption are already greater in some industries than others, as the below McKinsey chart shows, the impact will be felt in across the board.

What’s Your Plan to Incorporate Data Science and Data Visualization into Your Career?

Thinking through the role of data and data science becomes important for everyone, from individual in their careers to CEOs and strategic planning in the C-suite. Communicating findings – visualization of the data – is also critical.  

Data Visualization Challenges Inhibit Communication

In everyday corporate environments, data is routinely visualized using a variety of tools, from PowerPoint Charts with embedded Excel to Tableau, Qlikview, dashboards, and others. The demand for effective data visualization continues to increase, and the tools appear to make it easy to meet that demand.  

What’s Your Plan to Incorporate Data Science and Data Visualization into Your Career?

However, more visualization doesn’t necessarily lead to better comprehension as, in my experience, users frequently struggle to quickly interpret the data from more complex visuals like Marimekko charts.  Similarly, interpretation can be manipulated. For instance, a common tactic is distorting the scale on graphs, so that small changes look to be more significant than they are. 

Data scientists and others working with data can improve data visualization. A classic work on the data visualization topic is Professor Edward Tufte’s beautiful book, The Visual Display of Quantitative Information.  A gem within this book is Minard’s Visualization of Napoleon’s 1812 March, efficiently showing multiple dimensions in one chart. 

What’s Your Plan to Incorporate Data Science and Data Visualization into Your Career?

Anyone who is planning their next career move or planning to lead their company into the future needs to think through how data science and data visualization fits into the picture. No one can ignore the huge influence of big data across fields and industries and achieve long-term success. We have powerful, new decision-making tools, and we need to adopt them.