What is big data? What's the value?

? "Big data" refers to a huge data set collected from many sources in various forms, often in real time. In the case of business-to-business sales, these data can be obtained from social networks, e-commerce websites, customer visit records and many other sources. These data are not the normal data set of the company's customer relationship management database.

The application of big data has already penetrated into every aspect of people's lives: Amazon uses big data to recommend product information to customers, Ali uses big data to set up micro-financial services group, and Google plans to take over the world with big data? Now many industries are beginning to increase the demand for big data. In the era of big data, we must not only deal with massive data, but also process, disseminate and share these data. Unconsciously, data visualization has spread all over our lives, after all, ordinary users are often more concerned about the display of results. At the end of last year, Baidu Map used LBS to locate the visualized big data of Spring Festival travel rush boom, which caused a heated discussion on news innovation and big data visualization in academic circles.

Big data is an information asset, and its processing mode needs to be updated to have stronger decision-making, insight and process optimization capabilities to adapt to mass, high growth rate and diversification. These information assets derive more valuable information on the basis of objective data.

1. Recommend more suitable products according to the habits and needs of sales expenses, so that enterprises with related services can use big data for precise marketing, thus achieving a win-win and mutually beneficial effect;

2. When enterprises encounter bottlenecks or industries encounter difficulties, SMEs can use big data to respond quickly and transform their services;

3. In the strategic layout and resource allocation of enterprises, we can find a sentence closer to the facts through big data, and at the same time provide an opportunity for traditional enterprises that must be transformed under the pressure of the Internet to keep pace with the times.

Using relevant data and analysis, enterprise organizations can help them achieve the goals of reducing costs, improving efficiency, developing new products and making more informed business decisions. Here are some problems that can be solved by big data applications at present:

? 1, analyzing the root causes of faults, problems and defects in time may save billions of dollars for enterprises every year;

? 2. Plan real-time traffic routes for thousands of express vehicles to avoid congestion;

3. with the goal of maximizing profits, analyze all SKUs and prices and clean up inventory;

4. Push the preferential information that the customer may be interested in according to his buying habits;

5. Quickly identify gold medal customers from a large number of customers;

6. Use clickstream analysis and data mining to avoid fraud.

I. Technical value

Big data is fundamentally inseparable from basic theoretical knowledge such as mathematics, statistics, computer science and data science. The rapid development of technology has brought the most direct leap to the digital field.

The value of App R&D application, database writing application and so on to promote the technological progress of human society comes from the invention and operation of big data.

Big data not only creates new calculation methods and technical processing methods, but also provides a foundation for the research, development, application and landing of other technologies such as artificial intelligence.

The data of transactions between customers and enterprises in big data is the core mapping of the technical value of big data. Customer's trading behavior is saved through the internal system of the enterprise, which is mainly based on "ex post" data.

Transaction data is the first threshold to promote enterprise data-driven business, communicate with customers and obtain effective analysis data. No matter how big data acquisition capacity develops, direct transaction information is always the first effective and worthy of attention.

Taobao's transaction analysis report shows that the proportion of the second purchase order and the second purchase order in the same store after paying the large bill is 25.0% and 16.8% respectively, which is significantly higher than the ordinary bill, that is to say, it is entirely possible to enlarge the amount of the second purchase order after paying the bill for the first time, and it is higher than the ordinary bill.

So as to guide sellers to improve their services, insist on quality, launch bundled recommendations in time, and realize the probability of large orders for similar goods in the same store.

With the processing technology of big data, the transaction behavior can be recorded and analyzed, and the research and development, application and landing of enterprise big data technology can have a foundation, so as to develop and update the enterprise industry that is more suitable for the times.

At present, many traditional enterprises blindly take the road of big data, but in fact, the technical capabilities of big data have not been established. Few people really get valid data and can analyze and use them. Many "buried points" that should be done have not been done, and the statistics of data also lack technical support.

At this time, the technical value of big data will be particularly important, and it is the basis of all values. When one beam falls, the whole house collapses.

? Enterprises that can't innovate independently will turn to some new companies that provide big data services, which has spawned the emergence of various big data companies. As for how these companies serve the traditional transformation, it will be mentioned later.

Second, commercial value.

? In the actual upgrading operation, enterprises accustomed to traditional operation may often be confused by such a basic question: how to improve the operation situation? Who is the target customer? What are the characteristics? What are the competitive advantages compared with competing products? What are the business problems?

However, behind these seemingly simple problems, there is the analysis and mining of massive data: passenger flow data, business data, previous activities related data, store information in venues, and competing products data. Such in-depth dialysis can help enterprises attract potential customers, analyze operations, establish a membership system, and plan the implementation of activities.

? As far as operation is concerned, data, as a measure, can truly reflect the operation status, help enterprises to further understand products, users and channels, and then optimize their operation strategies.