Big data has taken over the world. Once upon a time, terabytes were a useful measure of volume for the world's data. Now that volume has stretched to petabytes and even zettabytes, much of which exists outside company research and transaction systems.
In fact, in the time it takes you to read a few paragraphs in this article, over 50 hours of video will have been uploaded to YouTube, millions of searches will be launched on search engines, and millions of dollars will be transacted via e-commerce. The increase in big data isn't limited to just tech companies. This great flood of data is impacting nearly every industry.
It's long been known that there are many big data applications, such as more personalized marketing or predictive inventory ordering, but most businesses haven't been able to organize their big data in a way that's useful.
But what exactly is big data? It's a phenomenon where more information is being generated than can be processed with your current data management systems. Or, in other words, it's when your company is data rich but information poor.
Having large stockpiles of data can be game-changing when it's being used to generate breakthrough insights that inform smart business decisions. However, without the tools to interpret that data, you're left with an overwhelmingly large database that’s just waiting to be utilized.
The solution to big data is a new concept: data applications.
What exactly are data applications and how do they work?
Data applications, as a concept, are still relatively new. There isn’t even an agreed-upon definition for them yet. And all apps could technically be called data-driven applications because they require data to function.
However, in the business intelligence and analytics world, data applications are characterized by a graphical user interface (GUI) that reveals the resources that are available in databases to users. It enables users like business analysts to run custom queries to a database to help them make more informed decisions.
Put more simply, data applications (not to be confused with database applications) are a mix between data visualizations and web applications in that they allow end users (decision-makers, subject matter experts, and even consumers) to visualize and effectively manipulate large sets of data.
Travel booking websites are a good example. Sites like Orbitz and Kayak deal with a significant amount of data that has to be moved around and visualized in an interactive way so it’s easy for consumers to find a flight they want and book it.
Imagine if you used these sites and were only able to look at the flight information and then had to call a travel agent to actually book the flight for you. That would be a lot more work and not very convenient.
But, this scenario is similar to what many organizations are doing with their own stockpiles of big data. The data application movement is about transitioning from an environment where end users merely look and report on data to an environment where anyone can easily visualize, interact with, and interpret big data as part of their everyday work.
