How do Internet companies make big data?

How Internet companies make big data

Big data is hot, and many companies will not miss the opportunity. Google has developed from a web index to a real-time data center hub, which can measure any measurable data, match the input query with all available data, and determine the information users are looking for; For Facebook, big data is "people", and the company has also used this to become one of the largest companies in the world within ten years.

Amazon matches users with other products and suggestions that may meet their needs by analyzing their habits; LinkedIn helps job seekers to match vacant positions according to their skills and experience, and helps recruiters to find talents that match specific materials. These are typical examples of big data applications, but they are only part of them. More and more data are easy to obtain, and complex tools will emerge. The use of big data can change our personal life and business activities.

nowadays, everyone has heard about how people use big data to cure cancer, end terrorism and feed hungry people to change the world.

Of course, it is also obvious that some people are using it to make big money-it is estimated that by 23, the world economy will increase by $15 trillion.

many people may think, "that's great, but it has nothing to do with me." Only large technology companies with millions of dollars in assets will really benefit. Do you need a lot of data to start a new research?

actually, it's not like this. In fact, it is easy to improve our personal and business life by making use of the great breakthrough in data collection and analysis in recent years. Many people may not have realized this before.

here are some details of big data as a part of daily life tools and services.

Google-Semantic Analysis and User Portrait

Although Google does not advertise itself as a data company, it is actually a data treasure house and a tool for solving problems. It has developed from a web index to a real-time data center hub, which can measure almost any measurable data (such as weather information, travel delay, stocks and shares, shopping … and many other things).

big data analysis-that is, big data will come into play when we search, and tools can be used to classify and understand the data. Google Computing runs complex algorithms designed to match the entered query with all available data. It will try to determine whether you are looking for news, facts, people or statistics, and extract data from the appropriate database.

for more complex operations, such as translation, Google will call other built-in algorithms based on big data. Google's translation service has studied millions of translated texts or speeches in order to provide customers with the most accurate explanation.

People who often use big data for analysis range from the largest enterprises to one-man bands. When they advertise through Google's Adwords, they make use of big data. By analyzing the web pages we browse (obviously we can see what web pages we like), Google can show us advertisements of products and services that we may be interested in. Advertisers use big data analytics when they use other services such as Adwords and Google Analytics to attract people who meet their customer profiles to their websites and stores.

Facebook-image recognition and "people" big data

Although there are huge differences in marketing between Facebook and Google, in fact, their business and data patterns are very similar. As we all know, both companies choose to focus their corporate image positioning on big data.

for Google, big data is online information, data and facts. For Facebook, big data is "people". Facebook makes it more and more convenient for us to keep in touch with friends and family. With this great attraction, the company has become one of the largest companies in the world within ten years. This also means that they collect a lot of data, and we can also use these big data ourselves. When we search for old friends, big data will come into play, matching our search results with the people we are most likely to contact.

The advanced technologies pioneered by Facebook include image recognition, a big data technology that can teach machines to recognize themes or details in pictures or videos by training with millions of other images. Before we tell it who the person in the picture is, the machine can identify the person in the picture by the tag. This is why, when our friends share or "like" pictures, if they find that we like to look at pictures of babies or cats, they will see more pictures of this type in our information flow.

A detailed understanding of people's interests and interests also enables Facebook to sell highly targeted advertisements to any enterprise. Facebook can help enterprises find potential customers according to detailed demographic data and interest data, or it can just let them complete their big data "magic" by finding other customers similar to the existing customers of enterprises.

Amazon-a recommendation engine based on big data

As the largest online store in the world, Amazon is also one of the largest data-driven organizations in the world. The difference between Amazon and other Internet giants mentioned in this article largely depends on marketing. Like Google and Google, Amazon provides a wide range of online services, including information search, following the accounts of friends and family, and advertising, but its brand is based on services originally known for shopping.

Amazon compares the products we browse and buy with millions of other customers around the world. By analyzing our habits, we can match with other products and suggestions that may meet our needs. The application of big data technology in Amazon is the recommendation engine, and Amazon is the originator of the recommendation engine, which is also the most complicated. In addition to shopping, Amazon also allows customers to use their own platforms to make money. Anyone who builds a transaction on his own platform will benefit from data-driven recommendation, which will, in theory, attract the right customers to buy products.

LinkedIn-filtered and accurate big data

If you are an employer or someone looking for a job, LinkedIn will provide some big data that can help you.

job seekers can match vacant positions according to their skills and experience, and even find data about other employees in the company and other employees who may compete for the position.

For recruiters, LinkedIn's big data can find talents that match specific data, such as current employees or former employees.

LinkedIn adopts a "walled garden" approach to its data (note: "walled garden" limits users to a specific range and allows users to access specified content relative to the "completely open" Internet). When you choose where to find and use big data, this difference is worth considering. LinkedIn's recruiters and applicants' services are all carried out by data inside the company and controlled by the service itself, while Google (which also provides recruitment information in the United States) obtains data from a large number of external resources. LinkedIn's method provides potentially higher quality information, but on the other hand, it may not be comprehensive. Google's method provides more data, but the data may or may not be what you want.

these are just a few ways to apply big data-far from being the tools of resource-rich companies and technical elites, but things that most of us have benefited from in our daily lives. As more and more data become easy to obtain, more and more complex tools emerge to gain value from them, and more data will certainly be generated.