How to make money on Big Data


Our site helps to make money sharing your Internet. You sell unused bandwidth, and the buyers are mostly companies and business communities located in more than one hundred countries. They look for the new markets, compare prices, check the accuracy of advertising or the legality of using owned trademarks.

The larger the research, the more traffic it requires. And the more profitable it becomes to those who sell bandwidth for money. Big Data is involved here. That term means the collection, processing and analysis of a large amount of data. This industry has been developing since 2011, and among other things, it is a possibility to make money sharing your Internet even if you’re not a specialist in Big Data. 

What is Big Data?

Big Data is large data arrays (there's no precise definition, but it usually varies from 100-150 Gb per day). They are collected and processed by automated means. Analysts then study Big Data by making reports and forecasts.

This technology is universal. It is suitable, for example, for:

  • searching for new planets, 
  • fighting bank fraud, 
  • scheduling city buses, 
  • curing diseases,
  • predicting earthquakes, and more. 

Therefore, the popularity of Big Data is growing. For those who seek to sell bandwidth for money, it’s more important to know about the use of such methods on the Internet.

How does Big Data work on the Internet?

Social networks and trading platforms provide a lot of information that becomes a part of Big Data. In social networks the researchers are interested in the characteristics of users, the number of friends, as well as interests. In impersonal form behavior, opinions, topics of communication, as well as top media on the Web are recorded. These include music, video, mobile games and apps. While exploring online stores using Big Data, marketers try to find patterns connecting people's purchases and their lifestyle.

This is necessary in order to predict further customer requests, get ahead of supply and demand and be ahead of competitors. Big Data is an expensive and cost-effective process. Some of these costs are used to pay for servers and high-speed Internet connection. Among other things it allows even non-specialists to make money sharing your Internet.

How is information collected for Big Data?

The main way to get a basis for analysis is scraping, or parsing. This is an automated process. Searching robots visit thousands of services and web pages, scan and select data of interest to researchers. It has millions of text lines and Gb’s of media content. All this data is then entered into huge databases and subjected to scrutiny. For example, requests “how to sell unused bandwidth” on the Internet without any investments. Another way to get an array of necessary data is to record the activity of Internet users during communication.

How does Big Data help to make money?

Specialists in the field of Big Data are in demand in the labor market. But even without a specialized education or skills, you can sell bandwidth for money.

The fact is that the reliability and accuracy of information is extremely important. The slightest distortion of the collected information will lead Big Data to incorrect research results. At a minimum, it means financial losses for customers. And in the case of analyzing medical or transport data, it could even be dangerous.

It’s too expensive, furthermore, to place special research centers all around the world. But there are still cases when you need to get data via the Internet from hundreds of geo locations on different sides of the Pacific and Atlantic oceans. By selling unused bandwidth you help Big Data services to receive reliable and correct information. At the same time, your personal data remains safe: our app doesn’t ask for access to personal folders, records or media files. 

That’s why Peer2Profit remains a reliable way to make money sharing your Internet. Income grows due to the number of users you invite by referral link, as well as the growing number of connected devices, including proxies.