Shulou(Shulou.com)11/24 Report--

With the data warehouse and R & D technical team to maintain a large amount of data, large use of resources, the higher the cost, the greater the optimization pressure. How to actively find ineffective or inefficient use of resources, and can periodically and efficiently carry out active governance has become one of the core demands of team governance goals.

In traditional cases, resource optimization mostly depends on team experience and human consciousness control. With the change of business demand and technical environment, it is difficult to adapt to the change quickly by relying on manual management, which can easily lead to excess or insufficient resources. At the same time, traditional methods lack of data support, can not fully understand the use of resources, and it is difficult to optimize resources scientifically.

At present, the volcano engine big data R & D management suite DataLeap provides resources combined with health sub-monitoring capabilities, which can help enterprises actively optimize problematic resources. By drilling down the healthy sub-market, we can identify the problematic asset bank and the individuals or teams with the greatest impact on resource consumption, and urge them to achieve the purpose of efficient use of service resources and reducing the cost of enterprise resources.

The resource optimization rule base of volcano engine DataLeap can flexibly choose the appropriate overall governance strategy according to the current governance plan of the business. For the governance API role, you can customize rules through DataLeap, such as data tables that are not valid for the data lifecycle and have not been queried for a long time, to improve the overall health score of assets and save storage space. As for the role of the person in charge of governance, you can intelligently plan storage and computing resources through the overall governance of data assets clearly visible in the market, so as to reduce management costs.

The volcano engine DataLeap data governance platform can also provide automatic and regular reminders for long-term stagnation teams. In the end, the team can accept the effect of resource optimization by managing the market, and at the same time precipitate the experience of optimization rules, and general rules can be directly referenced by other teams.

Focusing on cost optimization can help to co-ordinate data assets from a global perspective, improve collaboration efficiency in the governance process, and achieve team-driven and self-execution, thus abandoning complex evaluation and execution systems. In addition to the above governance capabilities, volcano engine DataLeap can also provide data integration, data development, operation and maintenance, assets and other capabilities to help users improve the efficiency of data research and development, reduce management costs, and accelerate the data transformation of enterprises. It has been used in pan-Internet, manufacturing, new retail, automotive and other fields.

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