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This article mainly explains "how to understand the data management process". The content of the explanation in the article is simple and clear, and it is easy to learn and understand. let's study and learn "how to understand the data management process"!

I. basic thinking

Data can be said to be the core topic in the Internet industry, the value of data has been called assets, most Internet applications will continue to generate all kinds of data, how to manage and use these data, let these seemingly ordinary data produce greater value, has always been a hot field of exploration. For example, common risk control, marketing, promotion and other businesses need to rely on a large number of user behavior data in order to accurately analyze and judge the relevant processes.

Data management is a complex and huge project, which takes a lot of time and cost. It is commonly said that the effective data of users are collected, stored, analyzed, built business models, secondary business applications, so as to make the data play a greater value.

When enterprises consider data precipitation management, there is usually a basic consideration: whether the amount of data is huge and whether the benefits brought by the data management system can cover the costs; for enterprises, many things are done right, but not necessarily beneficial to their own development; if data management can bring more business benefits, then this huge project is naturally worth investing in.

II. Business and data

Here, let's look at this problem from the perspective of the actual process. Usually at the beginning of development, a project will adopt a fast iterative approach to save costs and upgrade rapidly based on product design and user usage analysis. in this process, it is also a process of continuous accumulation of data, a basic process of product development with a clear direction: realization of product core functions, enrichment and optimization of processes, and data reporting of product analysis. This is the basic initial process of a project development. if the product is not successful, the process is basically over, and the cost will not be too high. of course, if the product is successful, how to determine the development direction of the follow-up product is another big topic.

The follow-up direction of the stable product is usually considered from two aspects: 1. Draw lessons from similar products on the market to analyze the reasons for success; 2. Judge the bright and bad points of the product based on the data generated by the existing business process. Usually, the analysis based on the existing data of the product is the most common operation. In the actual Internet products, there are living cases:

Media APP will recommend information according to users' browsing behavior, and the content you are interested in will continue to push; e-commerce APP will recommend specific goods according to season or date or search behavior to increase trading volume; social APP will make corresponding advertising placement and accurate distribution based on multi-latitude usage data.

The above practical cases are all very common operations in Internet products, which are based on the product business process, constantly accumulate data, and then do secondary data analysis according to the precipitation of their own data. it is applied to the business layer again to produce very high value.

III. Automating processes

The process of data management needs to be automated, which is the most basic operation. If the data-based process is not automatic, it is totally unnecessary, for example, the complete cycle of data is generated from business data, analysis and precipitation, visual analysis, secondary application, where only automatic management can provide stable services. One of the core factors in data management is efficiency, and the pursuit of efficiency depends on automatic process. Take a simple case: today's weather is very cold, users browse cold-proof goods, and if the products do not respond quickly, do a good job of relevant analysis and recommendation services, it is very likely that after today, users have no intention to buy, or have placed orders on other platforms, and most of the users' behavior is timely. This is especially important for transactional products. For social products or information flow products, the user behavior profile is very important, based on automatic behavior analysis, continue to enrich user behavior portraits, so as to more accurately judge the user psychology and improve the stickiness of the product.

So the final product form of data management, intelligent analysis of tools, process automation management, rapid judgment of user behavior, accurate response, which can maximize the value of business data.

IV. Service upgrading

Any product, if a steady stream of users sign up to use, generate a lot of data, it is easy to develop into a super application, or ecological platform. These services are supported by users and user data. For example, social products provide accurate marketing service platform; financial products provide risk control analysis; e-commerce products provide consumption capacity analysis; these services are based on huge amounts of user behavior data, analysis and speculation, once these ecological relationships are formed, the product will inevitably develop into a platform. For the same data, it is a feature of data management that it can provide multiple services. For example, if a platform knows users' precise purchase intention, then how many businesses this data can serve depends on how many businesses there are on this platform. This is the multiple business benefits generated by a user analyzing data.

Therefore, many phenomenal products first have their own data management system, first serve their own business lines, and then smoothly develop into a platform, open service capabilities, and obtain more customers or users, and then constantly optimize and upgrade service capabilities to enter a good development cycle.

Fifth, source code address GitHub address https://github.com/cicadasmileGitEE address https://gitee.com/cicadasmile thank you for reading, the above is the content of "how to understand the data management process", after the study of this article, I believe you have a deeper understanding of how to understand the data management process, the specific use of the situation also needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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