Transactions have given rise to a complex data-selling ecosystem. At the heart of it are credit card processing networks, including Visa, American Express, and Mastercard, the latter of which took in $4.1 billion in 2019 for services that include marketing analytics as well as fraud detection.
Joshua Smith, 2019 Iron Viz co-champion, used data provided by Pitney Bowes to create a dashboard about how international cuisine shapes food identity in the US. The visualization tells a story of what is on American tables using tile maps that display the prevalence of international cuisines by state, compared to the national average.
There is always that one country on America’s collective conscious. After looking at 741,681 section front headlines of The New York Times, Russell Goldenberg found out which countries around the world have preoccupied Americans the most each month since 1900.
Driving around your city, you’re probably somewhat aware of Avenues and Boulevards and Streets and Roads and so on. However, it’s hard to get an overall view of how all these road designations knit together. By coloring them, we can suddenly see a new, stunning view of what we normally take for granted.
American citizens are inundated with political messages—on social networks, in their news feeds, through email, text messages, and phone calls. If you live in the US, you’re almost certainly being tracked by political organizations. They know a lot about you—but some data is just guesswork.
Humans generate far more actionable information than is encoded in all of our combined genetic material, and we carry much of it into the future. The data outside of our biological selves—call it the dataome—could actually represent the grander scaffolding for complex life.
AI will tell you who to cast and predict how much money you’ll make. Despite skepticism about specific applications, the tide might be turning. A single factor has convinced Hollywood to stop dismissing big data: Netflix.
Big data is poised to transform society. Yet big data also exacerbates a very old problem: relying on the numbers when they are far more fallible than we think. Nothing underscores the consequences of data analysis gone awry more than the story of Robert McNamara.
How Cambridge Analytica used your Facebook data to help the Donald Trump campaign in the 2016 election. A then little-known British company sent out a press release: “We are thrilled that our revolutionary approach to data-driven communication has played such an integral part in President-elect Trump’s extraordinary win.”
Kinshasa is now bigger than Paris. Guangzhou, Hong Kong, and Shenzhen are forming an epic, 40 million-person super city. Over the past 30 years, the scale of population change is hard to grasp. How do you even visualize 10 million people?
Palantir is one of the most significant and secretive companies in big data analysis. The company acts as an information management service for Immigrations and Customs Enforcement, corporations like JP Morgan and Airbus, and dozens of other local, state, and federal agencies.
One of the most important economic stories of the past couple of decades is the rise of economic inequality in the United States and around the world. Since 1980, economists say, wage growth for the highest-paid workers has been roughly triple that for the lowest paid. In some cities, the disparity is wider.
Most transport apps have become walled gardens, each hoping you will choose one brand for all your getting-around needs. The more important battle is raging under the surface: A battle not over how you get from A to B, but over who gets to manage your journey.
Reading classic literature is like going for a 6am jog. It has its loyal fans but few enjoy it. Curious to learn about what classics people actually enjoy, Daniel Frank delved into the Goodreads data to find what classics users love and hate the most.
