Originally posted on business2community.com.
Big Data is a broad term referring to the ever growing amount of digital information being collected and stored, as well as the analytical procedures being developed to understand this data. Predictive, statistical modelling is attainable due to measuring and understanding as much as we possibly can about the past, so we can work out what will happen in the future.
Just about every industry is taking advantage of this method to propel their business forward.
Traditional TV is being replaced with online streaming services as viewers demand personalization and simplification. In a world of intense competition and fickle consumers, we’ve all become spoiled by choices. By having the right customers insights and data, streaming services are at a definite advantage.
There are so many opportunities to learn something important about your content and what your customers really think. Every video stream, every “like” on social media, every upload to YouTube–these data points build profiles for your customers and allow you to cater to their specific habits. Combine this with more traditional influences like the competitors, the news and regional specifications and you start to have a real understanding of consumers. For example, WatchOnline is an online guide that gathers data and analyzes it to help users quickly and easily decide what should they should watch.
For the last few years, the music industry — as you might know — has billions of dollars due to free music streaming and sharing sites. Fortunately, experts are confident that big data analytics can save the music industry and make up for lost revenue.
Essentially, big data has the ability to reconnect consumers with the music industry in new ways, ultimately increasing music engagement. There is a lot of detailed information today about who is listening to what music and when. This data allows recommendation engines that create playlists based on consumer analytics to function. For example, the Musical Genome Project uses automated algorithms to structure music data based on various factors like gender of the vocalist, instruments used, rhythm speed, etc.
The Internet of Things is also pushing the music industry. At Taylor Swift’s concert this past year, attendees were given LED bracelets controlled by RFID technology that change color and pulse in sync with the music. This is a great example of creative ways the music industry can engage consumers in the new Internet era.
Believe it or not, big data analytics is coming to revamp the hotel industry as well. Think about how much data each hotel stores: customer records, purchasing preferences,
Hotels cater to tons of travellers every day. Every single one of those travellers plan their trip with their own distinct set of expectations. By meeting those expectations, you’re building a positive and lasting impression that will encourage people to return. More hotel operators are looking to advanced analytics solutions for signs to keep their customers happy. Additionally, guests spending habits have a direct impact on the hotel’s sustainability. A high-rolling customer who spends frivolously for a celebration may seem like a valuable customer to a hotel but maybe that was a one time thing. Compare this to a frugal businessman who frequents the hotel for years and you’ll find that the latter has a more positive impact on the business. This is where the help of big data analytics comes in handy.
Customers have a data trail from the minute they book their hotel until they check out, and analysts are starting to turn all of that data into actionable observations.
Today, big data is taking over the automotive industry in an exciting science fiction fantasy: self-driving cars. In specific, the technology behind driverless cars are powered by the Internet of Things, or IoT. They’ve recently received a lot of hype, seeing that the benefits include: less traffic, increased safety, and lower environmental impacts.
Perhaps most well-known is the Google prototype, which lacks both pedals and a steering wheel. Google hopes that by 2020, which is in just 4 short years, their prototype will be available to the public. In specific, the Big Data elements come into the machine learning, or the parts of the car that recognizes images (like pedestrians, other cars, potholes, and street signs), processes those images, and then maneuvers and manages around them.
Still, because government regulations, especially in California, are restricting the prevalence of autonomous vehicles, we’ll just have to stay tuned to find out how this sci-fi movie ends.