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Big Data Applications: Six Under the Radar Examples

November 18, 2017

Big data applications can answer almost any question, assuming you have the right data sources and the right algorithms. Big data was developed specifically to bring together disparate data types that you previously couldn’t analyze together. By definition, big data applications are designed to address statistical problems that are beyond the capabilities of conventional database technology, bringing together datasets that are too large and too complex to deliver easy statistical answers. By bringing together structured data, such that is stored in a data warehouse, with unstructured data, such as social media, email, video, and web content, you can identify trends and traits that were previously invisible, gaining insight to make better decisions.

According to Statistica, big data professionals draw their information from a wide range of sources:

  • Transactions – 88 percent
  • Log data – 73 percent
  • Events – 59 percent
  • Emails – 57 percent
  • Social media – 43 percent
  • Sensors – 42 percent
  • RFID and point of sale data – 41 percent
  • Audio – 38 percent
  • Images and video – 34 percent

Using these various data sources, organizations are developing big data applications for marketing, customer relations, product development, security, supply chain optimization, manufacturing, and a host of business-related uses. However, with a little creativity, you can develop big data applications to analyze almost anything. Here are six examples of big data applications you may never have dreamed of:

1. Insuring Crop Yields

Farming is one of the most uncertain businesses there is, largely because you can never count on the weather. Harnessing big data is all about making better-informed decisions, and if farmers could predict the weather they could make better decisions about what to plant and when. That’s where big data comes in. Climate Corporation, a crop insurance company, uses data from local governments, radar systems, and other sources to collect and analyze data about weather patterns, soil conditions, and other variables to help farmers protect their investments. Climate Corporation is able to offer insurance policies against crop failure that the government can’t because they have more accurate predictive analytics.

2. Pricing Outdoor Advertising

Did you ever consider how companies charge for billboards, bus stations signs, and ads on the sides of transit vehicles? They used to charge “per impression” but there was no way to measure real impact. Using big data applications they now have a metric. Econsultancy explains that Route Research has found a way to analyze advertising space based on visibility, eye tracking studies, audience size, demographics, and other criteria to deliver a metric of “sets of eyeballs” for each ad – a much more accurate way to charge for impressions.

3. Market Predictions

Big data applications are already a big part of finance, but an emerging use of big data science is to monitor financial market forces. For example, analyzing market performance and social media data can generate a real-time “sentiment index.” Big data also can monitor news to determine its impact on market performance. For example, when a fake tweet went out that President Obama was killed in a White House explosion, the S&P Index lost $120 billion in seconds.  Real-time analytics are starting to take the place of high-paid financial analysts to predict market performance.

4. Personal Health

Big data applications are even making their way into our everyday lives. Personal care products like the UP wristband from Jawbone collects data from the users while they exercise, walk, work, and sleep. Using big data analytics the Jawbone app integrates all that data to provide a daily report on the user’s personal health profile.

5. Computational Photography

Computational photography is a new scientific field to capture and manipulate images to enhance image rendering. There are hundreds of labs dedicated to this field of study, which uses ray tracing to decode a scene by sampling rays over time. Computational photography can even render three-dimensional images of objects. Big data applications for photography make it possible to interpret digital information for a more accurate picture than is possible with conventional photography. Consider the potential applications in science or space exploration.

6. Tracking Bigfoot

And just to demonstrate the versatility of big data applications, Joshua Stevens, a graduate student at Penn State, is using 92 years of data to track Bigfoot. Stevens developed analytics to map Bigfoot sightings to geographic data, population densities, and other metrics to create a metric to compare Sasquatch sightings to population density. His findings mesh with those of the Bigfoot Field Researchers Organization, that Bigfoot is "astonishingly adept at avoiding human contact through a process of natural selection."

If you know how to ask the question, big data analytics can find an answer. The challenge is defining the question as the right big data use case (e.g., mapping Sasquatch sightings to population density). How do you see customers applying big data analytics?