It’s hard to escape the hype around big data these days. From magazines to newspapers to TV, discussions of big data are everywhere. But for the average business or software developer, what does big data mean? What is its promise or potential? The answer depends on the business.
For Google, Facebook and others, big data is intelligence and revenue rolled into one. In cases like the British Museum, it’s about preserving and making freely available a corpus of better than 150 million assets, from maps to musical scores. But even the smallest businesses can begin to use data in new and creative ways.
Consider the case of seasonal retail businesses, such as hardware stores. In years past, store owners manually managed inventory, attempting to anticipate demand for their wares. Today, forward-looking businesses incorporate big data into that decision-making process.
Some turn to predictive algorithms, which are primed with years of inventory data to render better, more accurate projections of demand. Others factor freely available weather data into their inventory predictions. When long-term drought conditions are forecast, as they were prior to this spring, intelligent hardware store owners could lower their inventory of garden hoses and sprinklers and stock the parts necessary for deeper wells that may be dug.
And it goes far beyond internal or general sources, such as weather data. Two years ago the New York Times examined Netflix data to determine which movies were being rented, by neighborhood, in a dozen cities. If you were an entrepreneur looking to open a comic book store, knowing where the fans lived for movies like “Batman Begins,” “Captain America” or “Thor” would be invaluable. Or if you were opening a cooking supply store, planning your location and marketing around which boroughs were consumed by Julie and Julia could be a real competitive advantage.
The nonprofit sector can also benefit from big data. U.S. government census data, made available via the open API at www.census.gov, offers insights on poverty and homelessness. The Cornell Program on Applied Demographics, for example, uses the API to layer poverty statistics onto a map. From there, a savvy nonprofit could turn to the ProgrammableWeb’s collection of nonprofit APIs to tap into databases of potential volunteers.
Whatever the business and whatever the industry, there are datasets – some of them very large indeed – that can help make better decisions faster. The key to effectively using big data is to think creatively about how it can be leveraged. Consultants or contractors won’t necessarily see the same possibilities that you will. But keep an open mind, and big data will more than justify its hype.