Big data is making big waves in many industries. For example, the airline you flew last month probably analyzed data to ensure your safety. Your favorite chain restaurant looked at big data to create that new specialty item on the menu.
Industries of all shapes and sizes are starting to tap into the power of big data. This bodes well for savvy data scientists who can turn this data into actionable insights. Here are five industries that are being transformed by big data.
Data science is the “next revolution in sustainable agriculture,” according to an article recently published in Ag Professional. That’s because it plays a critical role in helping farmers increase crop yields using the same number of acres, enabling them to meet the growing population’s agricultural needs. By measuring variables such as temperature, wind speed, and rainfall, data scientists help farmers predict potential outcomes as well as make decisions that reduce the impact of field variability and improve yield.
Farmers are also using data analytics to proactively manage dairy production. For a real-world example of this, see the following video, which is viewed and discussed by UW Data Science students in the course DS 745: Visualization and Unstructured Data Analysis.
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“It would be almost impossible to overstate the transformative potential of big data to the travel industry,” writes Thomas H. Davenport in a report titled “At the Big Data Crossroads: Turning Towards a Smarter Travel Experience.” To inform his research, Davenport interviewed 21 different travel companies to learn more about how they use big data to their advantage. For example, KAYAK uses data analytics to enable flight price forecasting that predicts whether the price of a flight will go up or down in the next seven days. It also provides a statistical confidence level behind these predictions. Marriott Hotels uses data analytics to predict the optimal price at which to fill its rooms.
Airbnb uses machine learning to detect host preferences and compute the likelihood that relevant hosts will want to accommodate a guest’s request. Then, Airbnb serves up likely matches more prominently in the search results.
Mark Ferguson, a management professor at the University of South Carolina, told CIO.com that cruise lines usually collect a substantial amount of customer-related data, because they track onboard spending habits over the entire trip. By offering a discounted base price to customers who frequently spend extra money aboard the ship, these companies likely see higher profits overall.
Airlines have also begun to use data science for a variety of purposes. For example, by analyzing data created by jet engines and sensors that monitor the environment (e.g., temperature, humidity, and air pressure), airlines can predict when various parts of a plane are likely to fail so they can take preventative maintenance actions. Following are several other ways in which airlines are starting to use big data:
- Identify profitable new routes by analyzing customer flying patterns
- Avoid accidents and delays by analyzing the geo-location of storms and other severe weather conditions
- Enhance customer service by analyzing a variety of customer data, including travel itineraries, social media, and frequent flyer status to improve front desk and on-board services. Southwest, United Airlines, and Delta are also using data analytics to improve the customer experience, according to the Fortune article “For the Airline Industry, Big Data is Cleared for Take-off.”
Food and Dining
Restaurants are also starting to tap into the power of big data to drive menu changes, improve services, identify new location opportunities, and more. In a report titled, “Big Data and Restaurants: Something to Chew On,” the National Restaurant Association encourages restaurants to take advantage of data analytics. The association says the data from a variety of systems, including point-of-service (POS) (e.g., sales by time, size of party, and menu items), accounting (e.g., payroll expenses, credit card sales versus cash, and gas or electric bills), and employee scheduling is a “vein of gold just waiting to be mined.” Other sources of data to mine include OpenTable, Facebook, Twitter, Yelp, TripAdvisor, Foursquare, Urbanspoon, or Instagram.
Some restaurants are using technology with their POS systems to gather information about customers (e.g., whether someone is a new or repeat customer, what they ordered, what they tipped, and how long they were at the table) and create profiles that include favorite drinks and food so they can target promotions and loyalty programs accordingly.
The association report also features various restaurants that have already taken the leap into the world of big data. For example, Chicago-based Levy’s restaurants use big data to understand the correlation between sporting events and food and beverage purchases. Panera tracks guest purchases and habits through loyalty cards and then leverages this data with primary marketing research and third-party data to guide its brand strategy, drive new customer acquisition, retain existing customers, and assist in real estate planning.
The rising cost of extraction and the turbulent state of international politics are two of the reasons why the oil industry has begun to rely on data analytics to drive business decisions, according to an article published on Forbes. In the article, contributor Bernard Marr writes that Royal Dutch Shell, one of the largest oil and gas companies, has developed a data-driven oilfield that reduces the cost of drilling for oil. The technique requires the ability to monitor low frequency seismic waves beneath the earth’s surface to determine whether they’re distorted as they pass through oil or gas.
“Data from any prospective oil field can then be compared alongside that from thousands of others around the world to enable geologists to make more accurate recommendations about where to drill,” writes Marr.
In addition, oil companies are using big data to monitor and improve machine performance as well as streamline the transport, refinement, and distribution of oil and gas.
According to the McKinsey article “Unleashing the Value of Advanced Analytics in Insurance,” auto insurers already analyze a variety of information, including real-time data about driving habits, to set premium rates and discounts. They also factor behavior-based credit scores from credit bureaus into their analyses, because there is empirical evidence suggesting that people who pay their bills on time are also safer drivers.
Allstate’s Arity unit, an independent subsidiary focused on connected-car data, uses data from telematics initiatives to develop models and products for auto insurance as well as ridesharing and roadside assistance, according to Digital Insurance.
These five big data industries are just a handful of those starting to realize the power of data analytics. (Here are several more.) As we look ahead, the power of big data will become even bigger. Companies both large and small will continually look for ways to capture and analyze customer data to improve profits and drive business intelligence.