The term “big data” sounds imposing, something that only the largest corporations can comprehend, let alone make use of. In actuality, if you ever avoided a traffic backup thanks to a phone-app alert or enjoyed a Netflix movie recommendation, you have already benefited from big data.
What Is Big Data?
Research firm Gartner’s definition of big data remains the standard, with its emphasis on the three V’s: Big data is a collection of high-volume, high-velocity, and/or high-variety information that typically requires processing and analysis before it can be used to improve decision-making and processes. In comparison, small data is easily understood without sophisticated analysis. If the data can be formatted into a simple-to-comprehend Excel spreadsheet, it is small data. Big data, which thanks to the Internet of Things, comes from an ever-increasing number of sources, requires data warehouses for storage and analytics to convert it into actionable information.
Why Is Big Data Important?
This brings us to the question: “What is big data analytics?” This entails managing, organizing, and mining the data so that you can home in on only the information relevant to your immediate concerns. The information that a packaged-goods company’s marketing team needs when deciding where to buy advertising, for instance, is different from the data points that the same company’s logistics team needs to improve the efficiency of its supply chain. Big data analytics not only ensures that each team receives only the information it needs in a comprehensible, actionable format, but it also uncovers and shares relationships among the varied data points that the teams might not have realized were relevant to them.
Network and Location Big Data
Relying on continuous streams of data from multiple satellites, GPS is a prime example of how big data simplifies daily life. When additional data points are layered on top of GPS satellite data, location data becomes even more robust. As noted in the TechRepublic article “GPS Serves a Pivotal Role in Big Data Stickiness,” beyond showing you how to get to your destination, big data integrated into GPS data enables you to find restaurants, gas stations, and other businesses on your route, keep abreast of traffic jams and accidents, and see photos of the route to complement the map—helpful for those who respond better to “Turn left at the big red barn” than to “Turn left on Mulberry Road.”
Adding historic information about crimes, accidents, and medical emergencies onto that same satellite data helps police departments and emergency response departments determine where best to position vehicles and respondents to improve response times. And when telematics data about the individual vehicles is incorporated, companies can keep tabs on the vehicles in their fleet and their drivers’ performance in them, while insurance companies and investigators can determine whether driver behavior played a role in accidents.
Big Data in Business
Telematics is far from the only application of big data in business. Below are just a few other ways various industries and organizations apply big data.
Big data allows for the creation of robust models that accurately quantify risks and help to minimize them. Improved risk management can help with everything from minimizing employee theft and security breaches to determining which markets to invest in or withdraw from.
Applying analytics to big data regarding customers—not only how they behaved on your website but also which sites they visited before and after your site, how they interacted on social media, their in-store purchases, their psychographics and demographics—can enable companies to create accurate audience profiles and segment their audience so that they can provide customers and prospects with more-personalized offers and experiences that are more likely to lead to sales. Small data might inform a business that, say, women ages 25-49 make up the largest segment of their audience; big data could let a company know which women consider their goods high-end and which consider them bargain buys, which ones subscribe to Vogue and which prefer Woman’s Day. All of this helps provide businesses with what is dubbed a 360-degree view of the customer, the holy grail of marketing.
- Proximity Marketing
Sometimes called retail geolocation marketing, this enables brick-and-mortar retailers to use beacons—devices that transmit signals to nearby smartphones so that apps can then relay that phone’s physical location to the retailer. That location data, when augmented with information about the customer’s online behavior and other big data, enables retailers to push personalized offers to customers while they’re in the store. For instance, beacons can alert a grocery store that a shopper is lingering in the ice cream aisle, which could then trigger the texting of a coupon for ice cream to that customer to help close the deal. What’s more, the data gleaned from the beacons can be added to the retailer’s existing big data—if the beacons reveal that people are skirting certain sections of the store, the retailer might want to reconsider the physical layout. Proximity marketing can also increase traffic to stores; among the big data examples cited by CMO by Adobe, a convenience-food chain has used beacons and big data to push coupons to people who were heading to nearby competitors, luring them to its own shops instead.
Big Data in Healthcare
Now that the vast majority of healthcare providers have switched to electronic health records (EHRs), clinicians, researchers, administrators, and pharmaceutical and biotech firms can tap into the aggregated data to improve the effectiveness of their efforts. Big data has enabled researchers to discover more risks and benefits resulting from drug trials than they had in the past. Analyzing years of big data has also led some organizations to better determine risk factors for opioid abuse. On a smaller, but still significant, scale, big data analytics can help hospitals and clinics schedule staff more effectively, leading to improved patient care.
Big Data in Technology
Like other businesses, tech firms use big data to assess risks more accurately and to better target their customers. Big data has also led to an increased need for data analysts, engineers, scientists, and architects; security engineers; and database managers and administrators. And it has facilitated the use of artificial intelligence (AI) and machine learning, taking those disciplines out of the realm of science fiction and making them viable tools.