Big data is big news on multiple levels. While most businesses think of big data in terms of how it can boost their bottom lines, big data has the power to do a lot more than create more targeted advertising. In fact, big data could solve some of the biggest problems we face on a global scale, including energy waste.

When it comes to clean technology, big data has surpassed alternate energy sources and electric cars in terms of its potential. The ability to collect and interpret massive amounts of data on energy usage has already resulted in breakthrough energy-saving innovations for both consumers and energy providers - and these technologies are poised to become more sophisticated and widespread in the near future.

Big Data and Consumer-Side Energy Efficiency

Energy efficiency is an important issue for many consumers and businesses. The less energy they use, the more money they save, so it literally pays to reduce energy waste. Aside from the everyday energy-saving habits of turning off lights, appliances and home computers when not in use, consumers are turning to energy-efficient models for everything from garage door openers to home heating and cooling systems.

The historic problem with home and business energy efficiency has been a lack of detailed data for energy consumption. Heating and cooling account to roughly 50 percent of all energy usage in the United States, but even that energy usage is seasonal, and the other 50 percent isn’t broken down too far. Monthly utility bills only indicate how much total energy a household has used in 30 days - not how it was used, or where it might be wasted.

That’s where big data comes in. Smart sensors can supply precise data for household energy use, tracking and reporting not only how much energy is used, but when the usage occurs — or even how much it’s costing you to leave your desktop on at home for eight hours while you go to work. This data can be presented through Web and mobile platforms, allowing consumers to spot energy waste and control energy use even when they’re not home.

One popular example is the Nest smart thermostat. Designed by former Apple engineers, the device accomplishes what programmable thermostats were supposed to, but never managed to make user-friendly enough. It lets you keep the thermostat dialed down when no one needs extra heat or cooling, and set it to turn itself to the right temperature when you want it to, such as just before your morning alarm goes off, or when you come home from work. In addition, the Nest thermostat "learns" your preferences and makes automated adjustments based on your historic settings.

This type of technology could be used for smarter lights, refrigerators, garage doors, air conditioners, crock-pots, lawn sprinklers and more. It also shows big data's potential for creating complete smart households running at maximum energy efficiency. (That's part of what's called the Internet of Things. Learn more in What the $#@! Is the Internet of Things?!)

Cutting Industrial Energy Waste

In addition to consumer energy efficiency, big data has the potential to help utilities realize smarter energy management. With the right data, utilities can maximize efficiency for overloaded grids and keep them running smoothly, without the need to sink money into new plants.

Utilities keep the power running 24/7. However, fluctuating power demands require them to have spare capacity to meet spikes in demand, such as in the middle of a hot summer day or through freezing winter nights. The current solution for most utilities is the use of "peaking plants." Dormant for most of the year, and costly to activate, peaking plants can cost up to eight times the number of megawatts/hour than off-peak energy, not to mention the additional pollution they create during operation.

Big data can reduce or eliminate utilities’ reliance on peaking plants. Through smart meters and algorithms that address exterior factors like weather, utilities can shift non-essential electricity use to non-peak times, reducing peak demand spikes and keeping all energy usage on the main grids.

With smarter energy management, utilities could also derive real value from alternative energy sources like wind and solar. Big data feeds can help utilities compensate automatically for periods when natural energy isn’t being generated. Predictive modeling with big data can allow utilities to calculate wind and solar patterns more precisely, and optimize the design and location of wind turbines and solar panels.

The Flip Side: Data Centers and Energy Waste

One of the key issues that could hinder big data’s potential to solve energy waste problems lies in big data itself, or at least, the way big data is generated. These unimaginable amounts of data are produced by data centers, which of course require energy to operate. And many data centers are wasting more energy than they use.

Like utilities, data centers are up and running 24/7. Heat is a serious issue. With hundreds of massive servers generating heat, the facilities must be cooled constantly to prevent a physical meltdown of the infrastructure. Yet most data centers are not running with energy efficiency in mind. In fact, a 2012 report by the New York Times found that instead of compensating for shifting demand, most data centers were running at maximum efficiency around the clock - and wasting 90% or more of the energy drawn from the grid.

Data centers and the digital economy currently consume around 10% of the world’s energy. If big data is to solve the energy waste problem, the industry must practice before it preaches and first turn its efficiency tools on itself, and find ways to reduce power draws and improve overall energy use without risking a lapse in supply.

Despite these obstacles, however, big data's "green" potential is tremendous. Tapping into a greener, more energy-efficient world may just be a matter of better understanding how we use energy and where it's most often wasted.