Data security has been a major concern throughout society. Data leaks not only expose individuals to security risks, but also, for businesses, endanger the security and stability of their data assets.

In general, there are two sources of data security: first, data security problems resulting from internal mismanagement; and secondly, security issues arising from external malicious attacks. According to the relevant reports, data losses and data damage caused by the former far outweigh the latter’s incidence and impact.

There are also frequent cases in press coverage where a research and development worker has the bank’s competence, which, in the course of the data writing process, results in the mismatch of the entire bank data and endangers the enterprise’s data assets.

Data security is also a growing concern for happiness in the area of increasingly warm properties. This paper will describe the practice of building a system of data competence from 0 to 1 in happiness.

It was noted that in happiness data security management, the main features of the problem were: the ease of the data of the staff and the data team and the urgent need for recycling of competencies; the need for sensitive data to be manned to avoid omissions and mistakes; and the presence of unpatriated assets by the disturbers, leading to the point of authorization for tables, columns, data sets, etc., and the failure of the mandate after its expiry due to the lack of renewal.

Therefore, the happiness data governance team urgently needs to build a set of data security management norms and to include tribal land through relevant tools.

The development of a suite of governance products as data derived from the experience of intra-territorial practice, volcano engine DataLeap provides data control, data protection services, technical capabilities such as rapid access to data assets and automatic construction of full-chain kinship, efficient security of large-scale enterprise data assets, and has become the preferred place for happiness in several areas, such as the pan-Internet.

In the management of the movement of persons, the introduction of the volcano engine DataLeap addresses the problem of separations, the rapid transfer of data on the staff, and easy access. The transferee of authority is required only to select all competences in DataLeap’s “Administration of Competences” - “Men’s Competence” - “Ourrent Competences”, and to select “applications for the replacement of another person” to apply for the transferee’s corresponding competence, which, when all authorizations have been completed, can be arranged, assigned, effectively enhances the efficiency and accessibility of the transfer.

Volcano engine DataLeap application process

In order to minimize the competencies of staff and team data, happi teams obtain records of nearly 90 days of staff visits, then verify the accuracy of user and schedule competencies through the blood relations map of DataLeap Metadata, in bulk, channel the competencies of the user’s tables into DataLeap data security, complete the collection of treasury competencies and control data to a minimum extent.

Finally, in order to ensure the day-to-day monitoring and management of data competencies, to facilitate timely processing of problems, happi teams create data sets and lead to the storage and search of volcano engine data holes, DataWind, which will eventually allow for visualization of monitoring indicators and showcases through dashboards.

Data Wind is a one-stop data analysis and collaborative platform launched by the volcanic engine. After happi access to DataWind, team personnel can clearly see the additions, omissions and applications that are sensitive, such as volume of applications, volume of applications, cancellations, cases of non-adoption, etc., as well as the availability of data assets for the movement of persons, which will greatly facilitate data security monitoring.

Only three months ago, the happiness built a standardized data competence management system through the product mix of Volcano engine DataLeap, DataWind, culminating in a variety of processes, such as competency recovery, sensitive configurations, excision management, achieving the goal of efficient data security management, and adding a “security lock” to its own data.