Under the background of localization, how can enterprises stabilize the data base?

The State Council recently issued the "14th Five-Year Plan for Digital Economy Development", emphasizing the need to enhance key technological innovation capabilities and build a safe and controllable technological innovation system.

With the acceleration of the localization trend of , the development of industry has also begun to cover more extensive fields such as big data platforms from the core chip, operating system, database and other fields. As the first industry to start the practice of , the financial industry is one of the more typical ones, and it is the earliest company that incorporates the realization of stable innovation and independent control into the scope of , and even regards it as an important goal of IT infrastructure construction.

At the same time, in typical business scenarios such as risk control and precision marketing, with the increasing amount of data, financial institutions are increasingly dependent on big data platforms. Therefore, more and more financial institutions will propose the need for autonomous and controllable platform capabilities.

In addition to the above two points, there are still several practical problems that are driving the financial and even other industries to put the migration the big data platform on the agenda.

One is the timeliness of bug fixes, and the other is the support of after-sales service. First of all, financial institutions are very sensitive to the vulnerabilities of software platforms, they will conduct vulnerability scans on a regular basis, and hope to be fixed in time. The development strategy of foreign software platforms is relatively fixed. Three versions may be released every year, and there will be a time difference of 1-2 months to fix bugs, which will affect the iterative cycle of the entire function. Secondly, in the after-sales service process of most foreign manufacturers, there is generally a customer service transfer technical expert, and then the technical expert evaluates the process of obtaining a solution, and the response is relatively delayed.

Even so, there are several reasons for completing the localization migration that need to be carefully considered: First, after the migration, the fully localized underlying platform and the original upper-level system may not be compatible with , and the new platform cannot seamlessly its own business. Taking database migration as an example, if an enterprise only needs to replace Oracle itself, it only needs to find a database that supports the same performance as Oracle. But there are still many products on Oracle that are developed based on it and have their own ecology. If replaced could result in total paralysis above. The same is true on the big data platform. If the replaced data platform is not compatible, many upper-level main products may not be able to operate, and it is difficult for to ensure the continuity of services.

Secondly, although most financial institutions have strong big data technical capabilities and teams, mostly focus on upper-level data assets, data governance, etc., and have relatively little R&D investment in the underlying platform. wants to migrate to a new data platform, it will face many uncontrollable factors, and enterprises will also worry about subsequent maintenance issues.

One side is the demand for localization, and the other side is to maintain the stability and continuity of the business. How to balance the two ends of this balance?

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