You don’t have to be a data scientist to interact with big data. Quite the opposite—the world of big data has become so accessible and intertwined in our everyday lives that avoiding big data would be a more impressive accomplishment.
Think about how you check your bank account activity. While the dashboard you check daily is quite simple to interpret and understand, behind the scenes is financial data that needs to be wrangled into place, securely managed, and updated around the clock. Purchasing a flight works similarly. As you (and many others) search for a flight, the backend system is calibrating demand, flight costs, and time of year to generate prices. You might not see the data, but behind those user-friendly interfaces is quite a whole lot of it.
So what are these data-powered technologies called? Quite simply, data applications. Data applications cater to consumers—like bank account owners or flight shoppers—but they can also be built internally for business stakeholders and subject matter experts.
Let’s take a closer look at what data applications are, some real-world examples, and some of the challenges of working with data applications.