Data analytics is simply the process of examining enormous amounts of information to uncover trends, hidden patterns and correlations that organizations can use to improve operations. Using 21st century computing technology, data scientists can gather billions of data points and spot patterns that would have been invisible to traditional intelligence systems in the past.

Analytics can help data-driven organizations understand problems, improve productivity, save money, use resources more efficiently and gain insights about their processes.

Here are a few impressive examples:

• Macy’s used inventory and demand data to adjust pricing in real time for 73 million items.
• British grocery store chain Tesco Plc used predictive analytics to save 100 million pounds of food from going to waste.
• Express Scripts identified patients most likely to forget to reorder their prescriptions and added customized reminders to their pill-bottle caps. Google used its search data last year to identify flu outbreaks around the world.
• By analyzing data from its trucks, UPS eliminated 5.3 million miles from its routes, reduced engine idling time by almost 10 million minutes, saved 650,000 gallons of fuel, and reduced carbon emissions by more than 6,500 metric tons.