In a recent blog by Alberto Cairo, noted data visualization expert, he argues that data journalism needs to improve its standards industry-wide. Cairo argues that, “data skills shouldn’t be the turf of a small guild of savants – they should permeate journalism in general.” At DataHero, this is exactly what our team strives for, creating a platform where users can learn and exercise data skills to arrive at the answers they need.
As “big data” enters the everyday processes of businesses, it has understandably seeped into data journalism as well. Publications like The Upshot have become more and more common, touting the ability to do everything from predicting World Cup winners to explaining complex health care costs. Thanks to the increasing access to data in all disciplines, many journalists have become fledgling data scientists.
Of course, few journalists are formally trained in data analysis. To be a journalist is to be someone well-versed in a variety of subjects at a shallower level, so he or she has a lot of backgrounds from which to pull. Data analysis is a discipline that requires a more thorough boring into the subject matter. This idea of a loose understanding of many subjects vs. a thorough understanding of one subject is where DataHero fits into the equation.
This notion of people having ever-increasing access to data, but not having the formal training to work with it is where DataHero shines. For example, DataHero analyzes each specific dataset for underlying patterns, then suggests charts based on those patterns. This allows users to easily get over the initial hurdle of wondering how their data should be represented.
Journalists are especially adept at knowing what will interest readers, how to make the connections between seemingly random pieces of information, and how to pull all these ideas into a cohesive piece. Thanks to products that democratize data analysis, like DataHero, journalists are able to focus on these questions, the synthesis of interesting facts, and ultimately creating pieces that will engage their readers.
Returning to this idea of knowing many disciplines vs. knowing one discipline really well, Cairo mentions the fox vs. hedgehog metaphor. “The fox knows many things, but the hedgehog knows one big thing.” Cairo argues that foxes and hedgehogs should partner together. Thus, journalists pair their expansive knowledge with data experts who can analyze the data a strict scientific manner.
Good data journalism merges interesting or trending questions with a solid foundation of data analysis. The data analyst provides the solid foundation, but lacks expansive background from multiple disciplines to ask the interesting questions. The journalist can ask the questions but may arrive at the wrong answers without the foundation in data analysis. Thus the process is a constant give and take between creative narrative and scientific analysis.
Using tools like DataHero doesn’t eliminate the need for a relationship between data scientists and journalists, but allows journalists to get further in their analysis, and potentially answer some of their questions without having to learn R or Python. Importing a dataset and moving through a thought process and the necessary exploration portion of a story is easy with a platform that doesn’t force you to focus on formulas or formatting.
DataHero helps you unmask the answers in your data. There’s nothing to download or install. Simply create an account and connect to the data services you use everyday (like Salesforce, Stripe, MailChimp, Dropbox and Box). DataHero automatically decodes your data and shows you the answers you need through dynamic visualizations.
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