How to build career expertise in data and information analysis

In today's data-driven world, where a staggering 328.77 million terabytes of information are created each day, the influence of data on shaping the landscape of global development has never been more crucial. The ability to decipher, analyze, and draw meaningful insights from vast and complex datasets has become a cornerstone in steering policies, initiatives, and strategies toward sustainable and impactful outcomes. “Data analysis allows us to understand and define priority challenges [and] it allows us to isolate the indicators that are going to move the needle. From there, we can develop a plan or solution to addressing a particular issue,” said Uyi Stewart, chief data and technology officer at Data.org, emphasizing how “data analysis is what empowers the kind of nimble, flexible problem solving that is so desperately needed in global development.” According to Stewart, there are two main categories of work to consider for a professional interested in data for social impact. “The first is data management. Being able to understand the mechanics of data science and having a handle on the process — from data collection to quality assurance to statistical analysis,” he said. Then comes communications. “Data is great, but you need to be able to distill and use it to tell a compelling story that leads to optimal decision-making. You need to align the data to tangible examples and human experiences for it to truly resonate and break through,” Stewart added. In light of this, the sector is seeing a surge in career opportunities, offering professionals an avenue to combine their interest in information analytics with a desire to create positive change. We spoke with various experts about the role of data in global development and how newcomers to the field can get started. Mapping the data analysis space “There is this great need to have professionals who can help us make sense of the data in a timely and meaningful way, so there is really no sector, no role where information analysis isn’t incredibly valuable,” Stewart said. Many young professionals gravitate toward coding, explained Linet Kwamboka, a senior program manager at the Global Partnership for Sustainable Development Data, highlighting how we need diverse skills to build a well-rounded field. She advises those interested in entering the sector to first map out the data space and explore the variety of machine learning skills one is interested in. Jeremy Boy, lead data scientist at the United Nations Development Programme, spoke of two big challenges: “filling in the numerous data gaps, most urgently those related to the Sustainable Development Goal indicators; and making data intelligible for specific global development practitioners and audiences, which is where visualization has a role to play.” Once you carry out the mapping, “find out the path of least resistance,” said Kwamboka. “We want this space to be as holistic as possible.”. Likewise, Stewart stressed that the power of data science is maximized when it is informed and shared by leaders from various sectors who possess domain expertise and practical experience. Drawing on this multifaceted space, Kwamboka outlines a range of sought-after skills. These include individuals specializing in the technical aspects, such as engineers, and those focusing on legislation, adopting a systems-thinking approach to problem-solving, or advancing the transition from traditional statistical reporting to more effective communication through social media. This is a rapidly evolving environment where "reskilling, retooling, and rethinking the methods and data sources being used in a more modern way” is key, said Kwamboka. To stay current with the latest trends, Boy recommended following podcasts such as “Data Stories” and the PolicyViz podcast, David McCandless’ TED talk, any of Moritz Stefaner’s talks, and Tamara Munzner’s online lecture based on her book “Visualization Analysis & Design.” Creating compelling narratives Citing Harvard University’s Weatherhead III University professor Gary King’s views on big data, Kwamboka said that the big data revolution is not merely about the sheer quantity of data but centers around the newfound ability to derive meaningful insights from it. Storytelling is a powerful tool for transforming complex information into a compelling and understandable narrative. It enhances communication, facilitates decision-making, and makes data more relevant and memorable for a diverse audience. Evan Shapīro, Media Universe cartographer and an adjunct professor at New York University Stern School of Business and Fordham Gabelli School of Business, said that early on in his career, he realized that “those who had the attention span to dig deep into the data, and use it to tell a story, had an advantage in the marketplace.” Ultimately, he believes that a good place to start is to “look at the data and find the most interesting, or unseen, story to tell.” According to Shapīro, effective data visualization relies on the inherent narrative within the data. Recalling his initial prominent infographic on the market capitalizations of the world’s most important media companies, Shapīro highlighted the complexity of handling extensive datasets. The dilemma was finding a format that could accommodate copious amounts of data while maintaining a digestible narrative, “the only format that I knew that fit those criteria was a map,” he said. Data visualization “So much important data is either missed or misunderstood,” stated Shapīro, underscoring the significance of data visualization as a powerful tool to convey vital and time-sensitive information to a wider audience that otherwise might not know how to interpret it. Boy's first recommendation for aspiring professionals is to think of visualization as information, not just raw data. “Data are the raw material, not the refined product,” He also suggested developing an understanding of the distinction between exploratory and explanatory visualization and design for the likely situation of the intended audience. “Generally speaking, the prior [exploratory] tends to rely more on open-ended interaction, while the latter [explanatory] more on targeted visual communication,” he said. In terms of building a strong portfolio, Boy recommends developing a personal vocabulary and exploring different graphic styles — he says this is helpful to “go beyond the typical ‘vector graphics’ look of most visualizations.” He recommended the works of Giorgia Lupi and Stephanie Posavec, and Mona Chalabi; looking at anthropographics, and exploring data comics. Shapīro considers data visualization to be the marriage of analytics and storytelling and one that shows great potential as Generation Z grows its influence. “Their attraction to, and talents in, digital storytelling will help us bring the art/science form to another level of communication — influencing people on things like climate change, the plight of refugees, and the fate of human rights,” he said. Regarding resources, Boy recommends following events like Information+ conference, IEEE VIS forum, ACM CHI Conference on Human Factors in Computing Systems, and the Information is Beautiful Awards. For communities, see the Data Visualization Society, and for written resources, “there are the classic books of Edward Tufte and of Alberto Cairo, Ben Fry’s ‘Visualizing Data,’ Jacques Bertin’s ‘Semiology of Graphics,’ and Tamara Munzner’s ‘Visual Analysis & Design,’” he said. Are you actively looking for a job? Or are you just passively open to new opportunities? Either way, don’t forget to update your Devex profile now — hundreds of recruiters are searching for talent on a daily basis in our database of over 1 million global development professionals.