Journalism and data analytics are similar in more ways than one. In both cases, you need critical thinking skills, intellectual curiosity, and a passion for uncovering the truth. Here are four ways journalism and data analysis are similar:
- Questions, questions, questions. Journalists are tasked with getting to the bottom of what’s going on. To do that, they ask lots of questions, specifically who, what, where, when, why and how. Data analysts also start with questions. What does the client want to know? What are the variables that are being studied? How are they related?
- Facts and details are vital. In my former career, I spent many sleepless nights worrying about whether I spelled a name wrong. I made more frantic telephone calls than I’d like to admit to chase down last-minute details to complete a story. And I constantly had other people in the newsroom reading headlines over my shoulder before they were published on the homepage. We all rely on journalists to ensure that the news is as correct as possible. In data analysis, you also need to make sure that you’re working with information that is as correct as possible. Errors in a data set, like items being coded incorrectly or “California,” “CA” and “Calif.” being counted as three different locations, will put your analysis on the wrong track and impact your results.
- People are at the heart of everything. Many different sources supply the facts that make a news story, but interviews with people bring the story to life. A story about the Iowa caucuses that is solely based on the results may have the correct information, but it will lack depth and meaning. It’s the same way with data analysis. While analysts spend quite a lot of quality time with numbers and computers, their work doesn’t mean much without talking to people about how those numbers affect them. Stakeholders in a data engagement indicate what is important, as well as reveal details that can make the numbers more interesting and meaningful.
- It’s all about telling a story that is informative and easy to understand. News stories should be written using language and sentence construction that could be understood by a fourth-grader. Journalists use short sentences and plain – yet descriptive – language to make the complex topics they write about accessible to everyone. The same principle applies directly to data analysis. Yes, the work behind it is very complicated. The average person may not understand programming and data queries. Thinking about standard deviations, regression analysis and medians may make people who haven’t done complex math in years queasy. However, the data story itself can be told in a very simple fashion. Interactive visualizations cut through all of the complexities and reveal the meaning behind the data in a way anyone can understand.