This direction is relatively longterm

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Occur Therefore the data must be monitored and traced to prevent accountability later Recently safety accidents have occurred one after another in the industry and companies are paying more and more attention to them Empower decisionmaking  and has many connected departments It also requires indepth business such as the benefits directly brought by data models and portrait tags and there is also an idea such as the difference in value generated by different data sources Strategy Internally sometimes there are too many governance rules that cannot be implemented resulting




In a large and comprehensive system that cannot concentrate resources and cannot obtain effective benefits Externally sometimes there are too many governance rules that cannot be implemented After all many teams Qatar Phone Numbers  need to participate and efficiency and coordination are also important System All data governance systems are already very mature such as Alibaba Clouds DataWorks Huawei Clouds DataArts Studio etc However if you use a selfbuilt data system you must not govern it just for the sake of governance You must proceed from reality find the enterprises own pain points and determine priorities





Organization First of all the most important thing before doing data governance is to have highlevel support and promote it from top to bottom otherwise it will just stay at the slogan stage Secondly who is responsible for data governance Who executes it From the perspective of the authors companys data center the data system and platform tools are established which are ultimately coordinated and used by the business data team The establishment of a data committee is generally composed of senior managers of the enterprise responsible for the .