Big data is a new branch of science that is handled to process huge amounts of data that can be used to predict and understand human behavior. Big data can also be called “prediction analysis..
Analysis of Twitter posts, Facebook shares, internet searches, GPS data and ATM machines can be shown as examples of big data. Monitoring security cameras, traffic data, weather history, flight records, entries of cell phone transmitters and heart monitors are some of the data analyzes in this area. While big data is a complex and new branch of science, it can be fully understood by only a handful of people.
Who uses big data for what purposes?
Many companies use big data to increase the satisfaction of their customers by adjusting their services, products and prices. Some examples in this area are:
- Macy Store uses big data to determine the price of more than 70 million products. The company also tries to connect its customers by sending them personal e-mails listing the products they think they may be interested in.
- Boston Marathon Explosion Police Intervention: As a result of large data analysis with video and security camera footage, police managed to narrow the search area for suspects in a short time.
- The Morton Steakhouse restaurant creates a marketing strategy by using big data via Twitter.
- Visa uses big data to identify and capture fraudsters. By tracking millions of data, he can reveal the fraud scheme.
- Facebook uses big data to serve personalized advertising. A careful review of your Facebook likes and browsing habits is the perfect way for the social media giant to learn your tastes. The ads you encounter during your Facebook flow are those that are determined by a highly specific and complex algorithm that tracks your Facebook habits.
Why is Big Data So Important?
There are four prominent titles that make big data important.
1. Massive Data:
Working with data that is too large to fit on a single hard disk drive. The size of this data is too large for the human mind to imagine. What we’re talking about here is billions of times the billions of megabytes of data.
2. Data Used No Complex and Specific Structure:
50 to 80 percent of working with big data is the job of transforming and clearing this data to make it possible to rig and sort. Only a few thousand people in the world know how to clear this data. These experts need customized software such as HPE and Hadoop to do their job. In the next decade, the number of these experts may increase dramatically, but today, the work of hard-to-find big data experts remains a mystery.
3. Data Becomes Sellable Property:
There are data markets where companies and individuals can receive data collected by terabytes of social media or other means. Most of this data is stored with cloud-based technologies. Because the aforementioned data cannot fit on a hard disk. Buying data is usually a process that requires membership and is obliged to connect to the cloud service. * Leading companies in the big data field are Amazon, Google, Facebook and Yahoo. Because these companies offer online services to millions of people and it is no surprise that they have become the leader with the data they collect in return for these services.
4. Almost No Limitations of Big Data:
One day, doctors are not likely to be able to detect patients’ heart attacks weeks before. It is possible to reduce aircraft and automobile accidents by analyzing mechanical, traffic and weather data. Finding peers over the Internet can be much easier thanks to your personal big data specialist. The musicians who understand the changing tastes of the target audience can make appropriate compositions. Nutritionists can predict which food combinations from markets can affect a person’s health, good or bad. Big data has just been scraped off the surface, and every day something new is being discovered in this area.