Have you ever wondered how Amazon knows what products you might be interested in? How Goodreads is able to recommend a book that’s absolutely perfect for you? How Pandora’s playlists are usually spot on? Each of these services taps into the power of big data.
What do you often do when Amazon recommends a product to you? Oftentimes, you’ll ignore the recommendation. However, if you’re like most people, you’ll also click the Buy Now button periodically. Score one for big data. Big data provides businesses with the insights needed to understand what their customers want. If a business can figure out what customers want and then present those customers with an irresistible offer, that business has a competitive advantage over businesses that merely guess.
Big data isn’t just about increasing sales. It can also be used to predict other behaviors such as fraud or plan more efficient business processes. For example, banks use big data to look for signs of fraudulent activities while package delivery services use big data to plan more efficient delivery routes. If you’ve read the book Moneyball or watched the movie, you’ll recognize big data’s role in identifying talented, but undervalued, athletes.
Where does all this big data come from?
We are in the information age where data is constantly being generated in huge volumes. Large companies such as Amazon and Netflix often need look no further than their own customer databases. For example, if you regularly watch chick flicks on Netflix, that tells Netflix something about what you like. Not only will Netflix look at your viewing habits, it will look at the viewing habits of people like you.
Other companies look to external sources of big data to gather their insights. For example, insurance companies often look at crime and accident statistics based on ZIP codes when pricing their homeowners or auto insurance policies.
How do companies make sense of big data?
If you’ve ever had to work even a moderately sized database, you know that data can be hard to understand. At the same time, you know that there are important insights that can be gleaned from that data. While spreadsheets can get the job done for small data sets, they become clumsy as data grows. When data is huge, such as the case is with big data, spreadsheets become difficult to deal with. After all, who has time to comb through tens of thousands, hundreds of thousands, or millions of records? Without a dedicated business intelligence solution, all of this data becomes a meaningless jumble of numbers.
Fortunately, business intelligence tools exist, allowing you to visualize the data in a more meaningful manner. Data visualizations and dashboards are particularly useful. Whether you want to look a geographic data on a map, climate data over time, fuel efficiency by model type, sales orders by region, sales targets by sales rep, or anything else for that matter, data visualizations convert sheer numbers into meaningful graphical representations that make sense.
Big data is powerful indeed, but only if you have a means of making sense of it.
- Kansas City Business Journal, “Big data: A powerful tool for businesses,” – http://www.bizjournals.com/kansascity/news/2014/11/12/big-data-a-powerful-tool-for-businesses.html
- CNN, “Moneyball: How businesses are using data to outsmart their rivals,” – http://edition.cnn.com/2014/10/13/business/moneyball-businesses-outsmarting-rivals/
- InetSoft, “Data Mining Big Data for Business Intelligence,” – https://www.inetsoft.com/blog/2014/10/data-mining-big-data-for-business-intelligence/
- BrightPlanet, “2014 BIG DATA PREDICTION #2: BIG DATA WILL GO EXTERNAL,” – http://www.brightplanet.com/2014/02/big-data-prediction-2-big-data-will-go-external/